p7cs.CR

Category

cs.CR

525 papers

On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses

Anish Athalye, Nicholas Carlini

1804.03286

Deduplicating Training Data Mitigates Privacy Risks in Language Models

Nikhil Kandpal, Eric Wallace, Colin Raffel

2202.06539

Membership Inference Attacks From First Principles

Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, Florian Tramer

2112.03570

On the Importance of Difficulty Calibration in Membership Inference Attacks

Lauren Watson, Chuan Guo, Graham Cormode, Alex Sablayrolles

2111.08440

The Hidden Vulnerability of Distributed Learning in Byzantium

El Mahdi El Mhamdi, Rachid Guerraoui, Sébastien Rouault

1802.07927

Extracting Training Data from Large Language Models

Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, Colin Raffel

2012.07805

Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning

Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Nicholas Carlini

2101.04535

Red Teaming Language Models with Language Models

Ethan Perez, Saffron Huang, Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, Geoffrey Irving

2202.03286

Auditing Differentially Private Machine Learning: How Private is Private SGD?

Matthew Jagielski, Jonathan Ullman, Alina Oprea

2006.07709

Label-Only Membership Inference Attacks

Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot

2007.14321

Opacus: User-Friendly Differential Privacy Library in PyTorch

Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, Ilya Mironov

2109.12298

Universal and Transferable Adversarial Attacks on Aligned Language Models

Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, Matt Fredrikson

2307.15043

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, Yang Zhang

2308.03825

Optimization-based Prompt Injection Attack to LLM-as-a-Judge

Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, Neil Zhenqiang Gong

2403.17710

Verifiable Fully Homomorphic Encryption

Alexander Viand, Christian Knabenhans, Anwar Hithnawi

2301.07041

Radioactive data: tracing through training

Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Hervé Jégou

2002.00937

Rényi Differential Privacy of the Sampled Gaussian Mechanism

Ilya Mironov, Kunal Talwar, Li Zhang

1908.10530

Jailbroken: How Does LLM Safety Training Fail?

Alexander Wei, Nika Haghtalab, Jacob Steinhardt

2307.02483

On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping

Sanghyun Hong, Varun Chandrasekaran, Yiğitcan Kaya, Tudor Dumitraş, Nicolas Papernot

2002.11497

Malla: Demystifying Real-world Large Language Model Integrated Malicious Services

Zilong Lin, Jian Cui, Xiaojing Liao, XiaoFeng Wang

2401.03315

Data Poisoning against Differentially-Private Learners: Attacks and Defenses

Yuzhe Ma, Xiaojin Zhu, Justin Hsu

1903.09860

Differentially Private Model Publishing for Deep Learning

Lei Yu, Ling Liu, Calton Pu, Mehmet Emre Gursoy, Stacey Truex

1904.02200

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li

2306.11698

SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models

Lijun Li, Bowen Dong, Ruohui Wang, Xuhao Hu, Wangmeng Zuo, Dahua Lin, Yu Qiao, Jing Shao

2402.05044

Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents

Wenkai Yang, Xiaohan Bi, Yankai Lin, Sishuo Chen, Jie Zhou, Xu Sun

2402.11208

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, Amin Karbasi

2312.02119

Privacy Odometers and Filters: Pay-as-you-Go Composition

Ryan Rogers, Aaron Roth, Jonathan Ullman, Salil Vadhan

1605.08294

Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds

Mark Bun, Thomas Steinke

1605.02065

Renyi Differential Privacy

Ilya Mironov

1702.07476

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Ahmed Salem, Yang Zhang, Mathias Humbert, Pascal Berrang, Mario Fritz, Michael Backes

1806.01246

How To Backdoor Federated Learning

Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, Vitaly Shmatikov

1807.00459

Deep Learning with Differential Privacy

Martín Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang

1607.00133

Analyzing Federated Learning through an Adversarial Lens

Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, Seraphin Calo

1811.12470

Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM

Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen

2309.14348

From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy

Maanak Gupta, CharanKumar Akiri, Kshitiz Aryal, Eli Parker, Lopamudra Praharaj

2307.00691

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Zeming Wei, Yifei Wang, Ang Li, Yichuan Mo, Yisen Wang

2310.06387

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen

2310.06987

A Little Is Enough: Circumventing Defenses For Distributed Learning

Moran Baruch, Gilad Baruch, Yoav Goldberg

1902.06156

Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li

1804.00308

Differentially Private Release and Learning of Threshold Functions

Mark Bun, Kobbi Nissim, Uri Stemmer, Salil Vadhan

1504.07553

STRIP: A Defence Against Trojan Attacks on Deep Neural Networks

Yansong Gao, Chang Xu, Derui Wang, Shiping Chen, Damith C. Ranasinghe, Surya Nepal

1902.06531

Algorithmic Stability for Adaptive Data Analysis

Raef Bassily, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, Jonathan Ullman

1511.02513

Between Pure and Approximate Differential Privacy

Thomas Steinke, Jonathan Ullman

1501.06095

Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates

Dong Yin, Yudong Chen, Kannan Ramchandran, Peter Bartlett

1803.01498

Baseline Defenses for Adversarial Attacks Against Aligned Language Models

Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein

2309.00614

Certifying LLM Safety against Adversarial Prompting

Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Aaron Jiaxun Li, Soheil Feizi, Himabindu Lakkaraju

2309.02705

Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, Dawn Song

1712.05526

FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces

Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu

1909.06122

Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms

Saeed Mahloujifar, Alexandre Sablayrolles, Graham Cormode, Somesh Jha

2204.06106

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu

1909.12962

TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Wenbo Guo, Lun Wang, Xinyu Xing, Min Du, Dawn Song

1908.01763

Private Learning and Sanitization: Pure vs. Approximate Differential Privacy

Amos Beimel, Kobbi Nissim, Uri Stemmer

1407.2674

Mitigating Sybils in Federated Learning Poisoning

Clement Fung, Chris J. M. Yoon, Ivan Beschastnikh

1808.04866

The Composition Theorem for Differential Privacy

Peter Kairouz, Sewoong Oh, Pramod Viswanath

1311.0776

Fingerprinting Codes and the Price of Approximate Differential Privacy

Mark Bun, Jonathan Ullman, Salil Vadhan

1311.3158

Spectral Signatures in Backdoor Attacks

Brandon Tran, Jerry Li, Aleksander Madry

1811.00636

Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy, Biplav Srivastava

1811.03728

SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems

Edward Chou, Florian Tramèr, Giancarlo Pellegrino

1812.00292

Universal Jailbreak Backdoors from Poisoned Human Feedback

Javier Rando, Florian Tramèr

2311.14455

Learning from Untrusted Data

Moses Charikar, Jacob Steinhardt, Gregory Valiant

1611.02315

Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models

Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, Dahua Lin

2310.02949

Faceless Person Recognition; Privacy Implications in Social Media

Seong Joon Oh, Rodrigo Benenson, Mario Fritz, Bernt Schiele

1607.08438

Answering n^{2+o(1)} Counting Queries with Differential Privacy is Hard

Jonathan Ullman

1207.6945

Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks

Ali Shafahi, W. Ronny Huang, Mahyar Najibi, Octavian Suciu, Christoph Studer, Tudor Dumitras, Tom Goldstein

1804.00792

TextBugger: Generating Adversarial Text Against Real-world Applications

Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, Ting Wang

1812.05271

Parseval Networks: Improving Robustness to Adversarial Examples

Moustapha Cisse, Piotr Bojanowski, Edouard Grave, Yann Dauphin, Nicolas Usunier

1704.08847

Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks

Kang Liu, Brendan Dolan-Gavitt, Siddharth Garg

1805.12185

Practical Secure Aggregation for Federated Learning on User-Held Data

Keith Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth

1611.04482

cpSGD: Communication-efficient and differentially-private distributed SGD

Naman Agarwal, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, H. Brendan Mcmahan

1805.10559

Query-limited Black-box Attacks to Classifiers

Fnu Suya, Yuan Tian, David Evans, Paolo Papotti

1712.08713

Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks

Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto

2302.05733

Poisoning Language Models During Instruction Tuning

Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein

2305.00944

Adversarial Attacks on Neural Networks for Graph Data

Daniel Zügner, Amir Akbarnejad, Stephan Günnemann

1805.07984

Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction

Jacob Steinhardt, Gregory Valiant, Moses Charikar

1606.05374

Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle

Yu-Xiang Wang, Jing Lei, Stephen E. Fienberg

1502.06309

Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks

Octavian Suciu, Radu Mărginean, Yiğitcan Kaya, Hal Daumé, Tudor Dumitraş

1803.06975

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

Anish Athalye, Nicholas Carlini, David Wagner

1802.00420

Certified Defenses for Data Poisoning Attacks

Jacob Steinhardt, Pang Wei Koh, Percy Liang

1706.03691

Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery

Thomas Steinke, Jonathan Ullman

1410.1228

Neural Trojans

Yuntao Liu, Yang Xie, Ankur Srivastava

1710.00942

Towards Evaluating the Robustness of Neural Networks

Nicholas Carlini, David Wagner

1608.04644

Practical Black-Box Attacks against Machine Learning

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami

1602.02697

ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models

Pin-Yu Chen, Huan Zhang, Yash Sharma, Jinfeng Yi, Cho-Jui Hsieh

1708.03999

Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey

1801.02613

Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods

Nicholas Carlini, David Wagner

1705.07263

Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks

Weilin Xu, David Evans, Yanjun Qi

1704.01155

Adversarial examples in the physical world

Alexey Kurakin, Ian Goodfellow, Samy Bengio

1607.02533

Adversarial Attacks on Neural Network Policies

Sandy Huang, Nicolas Papernot, Ian Goodfellow, Yan Duan, Pieter Abbeel

1702.02284

Generative Poisoning Attack Method Against Neural Networks

Chaofei Yang, Qing Wu, Hai Li, Yiran Chen

1703.01340

Robust Physical-World Attacks on Deep Learning Models

Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno, Dawn Song

1707.08945

Black-Box Attacks against RNN based Malware Detection Algorithms

Weiwei Hu, Ying Tan

1705.08131

Enhancing Robustness of Machine Learning Systems via Data Transformations

Arjun Nitin Bhagoji, Daniel Cullina, Chawin Sitawarin, Prateek Mittal

1704.02654

MagNet: a Two-Pronged Defense against Adversarial Examples

Dongyu Meng, Hao Chen

1705.09064

NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles

Jiajun Lu, Hussein Sibai, Evan Fabry, David Forsyth

1707.03501

Adversarial Machine Learning at Scale

Alexey Kurakin, Ian Goodfellow, Samy Bengio

1611.01236

Houdini: Fooling Deep Structured Prediction Models

Moustapha Cisse, Yossi Adi, Natalia Neverova, Joseph Keshet

1707.05373

Automated Software Vulnerability Assessment with Concept Drift

Triet H. M. Le, Bushra Sabir, M. Ali Babar

2103.11316

Multi-step Jailbreaking Privacy Attacks on ChatGPT

Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, Jie Huang, Fanpu Meng, Yangqiu Song

2304.05197

Red-Teaming the Stable Diffusion Safety Filter

Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, Florian Tramèr

2210.04610

Bayesian Estimation of Differential Privacy

Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Rühle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones

2206.05199

Concentrated Differential Privacy

Cynthia Dwork, Guy N. Rothblum

1603.01887

A Watermark for Large Language Models

John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein

2301.10226

On the Reliability of Watermarks for Large Language Models

John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein

2306.04634

ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms

Minzhou Pan, Yi Zeng, Lingjuan Lyu, Xue Lin, Ruoxi Jia

2302.11408

Antipodes of Label Differential Privacy: PATE and ALIBI

Mani Malek, Ilya Mironov, Karthik Prasad, Igor Shilov, Florian Tramèr

2106.03408

Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions

Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

2207.04380

Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models

Jiashu Xu, Mingyu Derek Ma, Fei Wang, Chaowei Xiao, Muhao Chen

2305.14710

Sparse DNNs with Improved Adversarial Robustness

Yiwen Guo, Chao Zhang, Changshui Zhang, Yurong Chen

1810.09619

Logit Pairing Methods Can Fool Gradient-Based Attacks

Marius Mosbach, Maksym Andriushchenko, Thomas Trost, Matthias Hein, Dietrich Klakow

1810.12042

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, Ananthram Swami

1511.04508

Stealing Machine Learning Models via Prediction APIs

Florian Tramèr, Fan Zhang, Ari Juels, Michael K. Reiter, Thomas Ristenpart

1609.02943

The Limitations of Deep Learning in Adversarial Settings

Nicolas Papernot, Patrick McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, Ananthram Swami

1511.07528

Interactive Privacy via the Median Mechanism

Aaron Roth, Tim Roughgarden

0911.1813

Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability

Kai Y. Xiao, Vincent Tjeng, Nur Muhammad Shafiullah, Aleksander Madry

1809.03008

A Learning Theory Approach to Non-Interactive Database Privacy

Avrim Blum, Katrina Ligett, Aaron Roth

1109.2229

Towards Fast Computation of Certified Robustness for ReLU Networks

Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane Boning, Inderjit S. Dhillon, Luca Daniel

1804.09699

On the (Statistical) Detection of Adversarial Examples

Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, Patrick McDaniel

1702.06280

Keeping the Bad Guys Out: Protecting and Vaccinating Deep Learning with JPEG Compression

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Li Chen, Michael E. Kounavis, Duen Horng Chau

1705.02900

Efficient Neural Network Robustness Certification with General Activation Functions

Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel

1811.00866

On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy Mann, Pushmeet Kohli

1810.12715

Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images

Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz

1703.10660

JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramer, Hamed Hassani, Eric Wong

2404.01318

Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

Evan Crothers, Nathalie Japkowicz, Herna Viktor

2210.07321

A General Framework for Auditing Differentially Private Machine Learning

Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa

2210.08643

Enhanced Membership Inference Attacks against Machine Learning Models

Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler, Reza Shokri

2111.09679

Numerical Composition of Differential Privacy

Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz

2106.02848

CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks

Xuanli He, Qiongkai Xu, Yi Zeng, Lingjuan Lyu, Fangzhao Wu, Jiwei Li, Ruoxi Jia

2209.08773

Protecting Intellectual Property of Language Generation APIs with Lexical Watermark

Xuanli He, Qiongkai Xu, Lingjuan Lyu, Fangzhao Wu, Chenguang Wang

2112.02701

The Curse of Recursion: Training on Generated Data Makes Models Forget

Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross Anderson

2305.17493

Hidden Backdoors in Human-Centric Language Models

Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, Jialiang Lu

2105.00164

Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers

Jacob Steinhardt, Moses Charikar, Gregory Valiant

1703.04940

On the Geometry of Differential Privacy

Moritz Hardt, Kunal Talwar

0907.3754

Privacy Risks of Securing Machine Learning Models against Adversarial Examples

Liwei Song, Reza Shokri, Prateek Mittal

1905.10291

Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference

Klas Leino, Matt Fredrikson

1906.11798

Understanding Gradient Clipping in Private SGD: A Geometric Perspective

Xiangyi Chen, Zhiwei Steven Wu, Mingyi Hong

2006.15429

Scalable Extraction of Training Data from (Production) Language Models

Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, Katherine Lee

2311.17035

Revisiting Membership Inference Under Realistic Assumptions

Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer, Quanquan Gu, David Evans

2005.10881

PPP-Completeness with Connections to Cryptography

Katerina Sotiraki, Manolis Zampetakis, Giorgos Zirdelis

1808.06407

Defensive Prompt Patch: A Robust and Interpretable Defense of LLMs against Jailbreak Attacks

Chen Xiong, Xiangyu Qi, Pin-Yu Chen, Tsung-Yi Ho

2405.20099

Get my drift? Catching LLM Task Drift with Activation Deltas

Sahar Abdelnabi, Aideen Fay, Giovanni Cherubin, Ahmed Salem, Mario Fritz, Andrew Paverd

2406.00799

On the `Semantics' of Differential Privacy: A Bayesian Formulation

Shiva Prasad Kasiviswanathan, Adam Smith

0803.3946

Fast and Memory Efficient Differentially Private-SGD via JL Projections

Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat

2102.03013

Diffusion Models for Adversarial Purification

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar

2205.07460

Diffprivlib: The IBM Differential Privacy Library

Naoise Holohan, Stefano Braghin, Pól Mac Aonghusa, Killian Levacher

1907.02444

Poisoning Web-Scale Training Datasets is Practical

Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum Anderson, Andreas Terzis, Kurt Thomas, Florian Tramèr

2302.10149

The Power of Linear Reconstruction Attacks

Shiva Prasad Kasiviswanathan, Mark Rudelson, Adam Smith

1210.2381

Are aligned neural networks adversarially aligned?

Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramer, Ludwig Schmidt

2306.15447

Spatially Transformed Adversarial Examples

Chaowei Xiao, Jun-Yan Zhu, Bo Li, Warren He, Mingyan Liu, Dawn Song

1801.02612

Evaluating and Understanding the Robustness of Adversarial Logit Pairing

Logan Engstrom, Andrew Ilyas, Anish Athalye

1807.10272

A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly

Yifan Yao, Jinhao Duan, Kaidi Xu, Yuanfang Cai, Zhibo Sun, Yue Zhang

2312.02003

Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow

1605.07277

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, Peter Henderson

2310.03693

The Robust Manifold Defense: Adversarial Training using Generative Models

Ajil Jalal, Andrew Ilyas, Constantinos Daskalakis, Alexandros G. Dimakis

1712.09196

Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers

Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi

1801.04354

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

Battista Biggio, Fabio Roli

1712.03141

Thieves on Sesame Street! Model Extraction of BERT-based APIs

Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, Mohit Iyyer

1910.12366

Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel

1801.10578

Stealthy and Persistent Unalignment on Large Language Models via Backdoor Injections

Yuanpu Cao, Bochuan Cao, Jinghui Chen

2312.00027

Differentially Private Fine-tuning of Language Models

Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang

2110.06500

Adversarial Perturbations Against Deep Neural Networks for Malware Classification

Kathrin Grosse, Nicolas Papernot, Praveen Manoharan, Michael Backes, Patrick McDaniel

1606.04435

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

Pin-Yu Chen, Yash Sharma, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh

1709.04114

Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients

Andrew Slavin Ross, Finale Doshi-Velez

1711.09404

White-box vs Black-box: Bayes Optimal Strategies for Membership Inference

Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier, Cordelia Schmid, Hervé Jégou

1908.11229

A Robust Semantics-based Watermark for Large Language Model against Paraphrasing

Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang

2311.08721

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training

Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez

2401.05566

Robust Distortion-free Watermarks for Language Models

Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang

2307.15593

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images

Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu

2401.11170

Deep Text Classification Can be Fooled

Bin Liang, Hongcheng Li, Miaoqiang Su, Pan Bian, Xirong Li, Wenchang Shi

1704.08006

BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models

Zhen Xiang, Fengqing Jiang, Zidi Xiong, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li

2401.12242

Threats to Pre-trained Language Models: Survey and Taxonomy

Shangwei Guo, Chunlong Xie, Jiwei Li, Lingjuan Lyu, Tianwei Zhang

2202.06862

SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders

Tianshuo Cong, Xinlei He, Yang Zhang

2201.11692

Membership Inference Attacks against Machine Learning Models

Reza Shokri, Marco Stronati, Congzheng Song, Vitaly Shmatikov

1610.05820

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Yue Zhang, Neil Zhenqiang Gong, Xing Xie

2306.04528

Machine Learning Models that Remember Too Much

Congzheng Song, Thomas Ristenpart, Vitaly Shmatikov

1709.07886

Input-Aware Dynamic Backdoor Attack

Anh Nguyen, Anh Tran

2010.08138

Jailbreaking GPT-4V via Self-Adversarial Attacks with System Prompts

Yuanwei Wu, Xiang Li, Yixin Liu, Pan Zhou, Lichao Sun

2311.09127

CrypTen: Secure Multi-Party Computation Meets Machine Learning

Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten

2109.00984

Are Diffusion Models Vulnerable to Membership Inference Attacks?

Jinhao Duan, Fei Kong, Shiqi Wang, Xiaoshuang Shi, Kaidi Xu

2302.01316

Physical Adversarial Examples for Object Detectors

Kevin Eykholt, Ivan Evtimov, Earlence Fernandes, Bo Li, Amir Rahmati, Florian Tramer, Atul Prakash, Tadayoshi Kohno, Dawn Song

1807.07769

Dissecting Adversarial Robustness of Multimodal LM Agents

Chen Henry Wu, Rishi Shah, Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried, Aditi Raghunathan

2406.12814

Adversarial Attacks and Defences Competition

Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe

1804.00097

Deep Learning with Gaussian Differential Privacy

Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su

1911.11607

Low Rank Mechanism for Optimizing Batch Queries under Differential Privacy

Ganzhao Yuan, Zhenjie Zhang, Marianne Winslett, Xiaokui Xiao, Yin Yang, Zhifeng Hao

1212.2309

Adversarial Unlearning of Backdoors via Implicit Hypergradient

Yi Zeng, Si Chen, Won Park, Z. Morley Mao, Ming Jin, Ruoxi Jia

2110.03735

Individual Privacy Accounting via a Renyi Filter

Vitaly Feldman, Tijana Zrnic

2008.11193

Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks

Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion

2404.02151

The relativistic discriminator: a key element missing from standard GAN

Alexia Jolicoeur-Martineau

1807.00734

Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, Kunal Talwar

1610.05755

Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets

Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, Nicholas Carlini

2204.00032

Verifiable Encodings for Secure Homomorphic Analytics

Sylvain Chatel, Christian Knabenhans, Apostolos Pyrgelis, Carmela Troncoso, Jean-Pierre Hubaux

2207.14071

Model-Reuse Attacks on Deep Learning Systems

Yujie Ji, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang

1812.00483

Iterative Constructions and Private Data Release

Anupam Gupta, Aaron Roth, Jonathan Ullman

1107.3731

Systematic Evaluation of Privacy Risks of Machine Learning Models

Liwei Song, Prateek Mittal

2003.10595

Information Leakage in Embedding Models

Congzheng Song, Ananth Raghunathan

2004.00053

Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization

Pranav Subramani, Nicholas Vadivelu, Gautam Kamath

2010.09063

Fairness in the Eyes of the Data: Certifying Machine-Learning Models

Shahar Segal, Yossi Adi, Benny Pinkas, Carsten Baum, Chaya Ganesh, Joseph Keshet

2009.01534

Can Adversarial Weight Perturbations Inject Neural Backdoors?

Siddhant Garg, Adarsh Kumar, Vibhor Goel, Yingyu Liang

2008.01761

MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, Neil Zhenqiang Gong

1909.10594

BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT

Jiawen Shi, Yixin Liu, Pan Zhou, Lichao Sun

2304.12298

StruQ: Defending Against Prompt Injection with Structured Queries

Sizhe Chen, Julien Piet, Chawin Sitawarin, David Wagner

2402.06363

On Evaluating Adversarial Robustness

Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Madry, Alexey Kurakin

1902.06705

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT

Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela

2006.07134

Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust

Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein

2305.20030

Stronger Data Poisoning Attacks Break Data Sanitization Defenses

Pang Wei Koh, Jacob Steinhardt, Percy Liang

1811.00741

Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information

Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, Ruoxi Jia

2204.05255

Extracting Training Data from Diffusion Models

Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, Eric Wallace

2301.13188

Tactics of Adversarial Attack on Deep Reinforcement Learning Agents

Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, Min Sun

1703.06748

The Space of Transferable Adversarial Examples

Florian Tramèr, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

1704.03453

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

Milad Nasr, Reza Shokri, Amir Houmansadr

1812.00910

Audio Adversarial Examples: Targeted Attacks on Speech-to-Text

Nicholas Carlini, David Wagner

1801.01944

Trojaning Language Models for Fun and Profit

Xinyang Zhang, Zheng Zhang, Shouling Ji, Ting Wang

2008.00312

Optimal Accounting of Differential Privacy via Characteristic Function

Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang

2106.08567

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein

2012.10544

Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

Yaqin Zhou, Shangqing Liu, Jingkai Siow, Xiaoning Du, Yang Liu

1909.03496

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, Mingwei Xu

2101.02644

The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices

Wanlun Ma, Derui Wang, Ruoxi Sun, Minhui Xue, Sheng Wen, Yang Xiang

2209.11715

Are Large Pre-Trained Language Models Leaking Your Personal Information?

Jie Huang, Hanyin Shao, Kevin Chen-Chuan Chang

2205.12628

Differential Privacy Has Disparate Impact on Model Accuracy

Eugene Bagdasaryan, Vitaly Shmatikov

1905.12101

F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption (Extended Version)

Axel Feldmann, Nikola Samardzic, Aleksandar Krastev, Srini Devadas, Ron Dreslinski, Karim Eldefrawy, Nicholas Genise, Chris Peikert, Daniel Sanchez

2109.05371

Simple Black-Box Adversarial Perturbations for Deep Networks

Nina Narodytska, Shiva Prasad Kasiviswanathan

1612.06299

Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Briland Hitaj, Giuseppe Ateniese, Fernando Perez-Cruz

1702.07464

Visual Adversarial Examples Jailbreak Aligned Large Language Models

Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, Prateek Mittal

2306.13213

Adversarial Semantic Collisions

Congzheng Song, Alexander M. Rush, Vitaly Shmatikov

2011.04743

Understanding and Mitigating Copying in Diffusion Models

Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein

2305.20086

Towards A Proactive ML Approach for Detecting Backdoor Poison Samples

Xiangyu Qi, Tinghao Xie, Jiachen T. Wang, Tong Wu, Saeed Mahloujifar, Prateek Mittal

2205.13616

Overcoming Forgetting in Federated Learning on Non-IID Data

Neta Shoham, Tomer Avidor, Aviv Keren, Nadav Israel, Daniel Benditkis, Liron Mor-Yosef, Itai Zeitak

1910.07796

Differentially Private Coordinate Descent for Composite Empirical Risk Minimization

Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi

2110.11688

Towards the Science of Security and Privacy in Machine Learning

Nicolas Papernot, Patrick McDaniel, Arunesh Sinha, Michael Wellman

1611.03814

Understanding Membership Inferences on Well-Generalized Learning Models

Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiaofeng Wang, Haixu Tang, Carl A. Gunter, Kai Chen

1802.04889

What Can We Learn Privately?

Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, Adam Smith

0803.0924

DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han

2311.03191

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses

Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Jing Jiang, Min Lin

2406.01288

Lower bounds in differential privacy

Anindya De

1107.2183

Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya Razenshteyn, Sebastien Bubeck

1906.04584

Low-Resource Languages Jailbreak GPT-4

Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach

2310.02446

Metric Learning for Adversarial Robustness

Chengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray

1909.00900

Backdoor Pre-trained Models Can Transfer to All

Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, Ting Wang

2111.00197

Dynamic Backdoor Attacks Against Machine Learning Models

Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, Yang Zhang

2003.03675

Auditing Membership Leakages of Multi-Exit Networks

Zheng Li, Yiyong Liu, Xinlei He, Ning Yu, Michael Backes, Yang Zhang

2208.11180

Optimizing Histogram Queries under Differential Privacy

Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, Andrew McGregor

0912.4742

Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification

Yingxue Zhou, Zhiwei Steven Wu, Arindam Banerjee

2007.03813

How Robust is Google's Bard to Adversarial Image Attacks?

Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu

2309.11751

Harnessing large-language models to generate private synthetic text

Alexey Kurakin, Natalia Ponomareva, Umar Syed, Liam MacDermed, Andreas Terzis

2306.01684

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection

Bingzhe Wu, Shiwan Zhao, ChaoChao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou

1908.07882

Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification

Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein

2202.00580

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Sijun Tan, Brian Knott, Yuan Tian, David J. Wu

2104.10949

An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning

Zhiying Xu, Shuyu Shi, Alex X. Liu, Jun Zhao, Lin Chen

1912.09150

Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models

Shawn Shan, Jenna Cryan, Emily Wenger, Haitao Zheng, Rana Hanocka, Ben Y. Zhao

2302.04222

Simple Black-box Adversarial Attacks

Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger

1905.07121

Ensemble Adversarial Training: Attacks and Defenses

Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

1705.07204

Prompt Injection attack against LLM-integrated Applications

Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, Zihao Wang, Xiaofeng Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, Leo Yu Zhang, Yang Liu

2306.05499

NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models

Kai Mei, Zheng Li, Zhenting Wang, Yang Zhang, Shiqing Ma

2305.17826

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

Edoardo Debenedetti, Jie Zhang, Mislav Balunović, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr

2406.13352

Differentially Private Federated Learning: A Client Level Perspective

Robin C. Geyer, Tassilo Klein, Moin Nabi

1712.07557

An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks

Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu

2006.08131

Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness

Lingjuan Lyu, Xuanli He, Yitong Li

2010.01285

Invisible Backdoor Attack with Sample-Specific Triggers

Yuezun Li, Yiming Li, Baoyuan Wu, Longkang Li, Ran He, Siwei Lyu

2012.03816

Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models

Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin

2312.09601

Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data

Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan

1805.12316

GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models

Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz

1909.03935

Copyright Protection in Generative AI: A Technical Perspective

Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Pei Huang, Lingjuan Lyu, Hui Liu, Yi Chang, Jiliang Tang

2402.02333

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

Ren Wang, Gaoyuan Zhang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong, Meng Wang

2007.15802

Delving into the Adversarial Robustness of Federated Learning

Jie Zhang, Bo Li, Chen Chen, Lingjuan Lyu, Shuang Wu, Shouhong Ding, Chao Wu

2302.09479

Anti-DreamBooth: Protecting users from personalized text-to-image synthesis

Thanh Van Le, Hao Phung, Thuan Hoang Nguyen, Quan Dao, Ngoc Tran, Anh Tran

2303.15433

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models

Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song

2112.05588

Privacy Implications of Retrieval-Based Language Models

Yangsibo Huang, Samyak Gupta, Zexuan Zhong, Kai Li, Danqi Chen

2305.14888

Adversarial Attacks on Stochastic Bandits

Kwang-Sung Jun, Lihong Li, Yuzhe Ma, Xiaojin Zhu

1810.12188

Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents

Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar, Tu Trinh, Scale Red Team, Elaine Chang, Vaughn Robinson, Sean Hendryx, Shuyan Zhou, Matt Fredrikson, Summer Yue, Zifan Wang

2410.13886

Security Risks in Deep Learning Implementations

Qixue Xiao, Kang Li, Deyue Zhang, Weilin Xu

1711.11008

Rademacher Complexity for Adversarially Robust Generalization

Dong Yin, Kannan Ramchandran, Peter Bartlett

1810.11914

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, Alex Beutel

2404.13208

Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment

Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Yangsibo Huang, Matthew Jagielski, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang

2304.06929

Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots

Wai Man Si, Michael Backes, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Savvas Zannettou, Yang Zhang

2209.03463

Backdoor Attack in the Physical World

Yiming Li, Tongqing Zhai, Yong Jiang, Zhifeng Li, Shu-Tao Xia

2104.02361

Practical and Private (Deep) Learning without Sampling or Shuffling

Peter Kairouz, Brendan McMahan, Shuang Song, Om Thakkar, Abhradeep Thakurta, Zheng Xu

2103.00039

$μ$VulDeePecker: A Deep Learning-Based System for Multiclass Vulnerability Detection

Deqing Zou, Sujuan Wang, Shouhuai Xu, Zhen Li, Hai Jin

2001.02334

Adversarial Texts with Gradient Methods

Zhitao Gong, Wenlu Wang, Bo Li, Dawn Song, Wei-Shinn Ku

1801.07175

EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage

Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, Huan Sun

2409.11295

When the Curious Abandon Honesty: Federated Learning Is Not Private

Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot

2112.02918

IBM Federated Learning: an Enterprise Framework White Paper V0.1

Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Whitherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay

2007.10987

Differentially Private Synthetic Data via Foundation Model APIs 1: Images

Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

2305.15560

Natural Backdoor Attack on Text Data

Lichao Sun

2006.16176

Scalable and Privacy-Preserving Federated Principal Component Analysis

David Froelicher, Hyunghoon Cho, Manaswitha Edupalli, Joao Sa Sousa, Jean-Philippe Bossuat, Apostolos Pyrgelis, Juan R. Troncoso-Pastoriza, Bonnie Berger, Jean-Pierre Hubaux

2304.00129

GenAttack: Practical Black-box Attacks with Gradient-Free Optimization

Moustafa Alzantot, Yash Sharma, Supriyo Chakraborty, Huan Zhang, Cho-Jui Hsieh, Mani Srivastava

1805.11090

High Accuracy and High Fidelity Extraction of Neural Networks

Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, Nicolas Papernot

1909.01838

Certified Robustness to Adversarial Examples with Differential Privacy

Mathias Lecuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana

1802.03471

EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning

Hongbin Liu, Jinyuan Jia, Wenjie Qu, Neil Zhenqiang Gong

2108.11023

Model Stealing Attacks Against Inductive Graph Neural Networks

Yun Shen, Xinlei He, Yufei Han, Yang Zhang

2112.08331

Differentially Private Diffusion Models Generate Useful Synthetic Images

Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle

2302.13861

Towards Robust Neural Networks via Random Self-ensemble

Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh

1712.00673

Rethinking the Trigger of Backdoor Attack

Yiming Li, Tongqing Zhai, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shutao Xia

2004.04692

AdaCliP: Adaptive Clipping for Private SGD

Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

1908.07643

Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

1912.04977

Undetectable Watermarks for Language Models

Miranda Christ, Sam Gunn, Or Zamir

2306.09194

Privacy Amplification via Random Check-Ins

Borja Balle, Peter Kairouz, H. Brendan McMahan, Om Thakkar, Abhradeep Thakurta

2007.06605

DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

Han Qiu, Yi Zeng, Shangwei Guo, Tianwei Zhang, Meikang Qiu, Bhavani Thuraisingham

2012.07006

Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs

Eugene Bagdasaryan, Tsung-Yin Hsieh, Ben Nassi, Vitaly Shmatikov

2307.10490

MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots

Gelei Deng, Yi Liu, Yuekang Li, Kailong Wang, Ying Zhang, Zefeng Li, Haoyu Wang, Tianwei Zhang, Yang Liu

2307.08715

BLAZE: Blazing Fast Privacy-Preserving Machine Learning

Arpita Patra, Ajith Suresh

2005.09042

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Hamza Harkous, Kassem Fawaz, Rémi Lebret, Florian Schaub, Kang G. Shin, Karl Aberer

1802.02561

Provably Minimally-Distorted Adversarial Examples

Nicholas Carlini, Guy Katz, Clark Barrett, David L. Dill

1709.10207

AirGapAgent: Protecting Privacy-Conscious Conversational Agents

Eugene Bagdasarian, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage

2405.05175

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

Wieland Brendel, Jonas Rauber, Matthias Bethge

1712.04248

Backdoor Defense via Decoupling the Training Process

Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, Kui Ren

2202.03423

Privately Releasing Conjunctions and the Statistical Query Barrier

Anupam Gupta, Moritz Hardt, Aaron Roth, Jonathan Ullman

1011.1296

On Certifying Robustness against Backdoor Attacks via Randomized Smoothing

Binghui Wang, Xiaoyu Cao, Jinyuan jia, Neil Zhenqiang Gong

2002.11750

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance

Renjie Pi, Tianyang Han, Jianshu Zhang, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang

2401.02906

Composition Attacks and Auxiliary Information in Data Privacy

Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, Adam Smith

0803.0032

Image Hijacks: Adversarial Images can Control Generative Models at Runtime

Luke Bailey, Euan Ong, Stuart Russell, Scott Emmons

2309.00236

Model Agnostic Defence against Backdoor Attacks in Machine Learning

Sakshi Udeshi, Shanshan Peng, Gerald Woo, Lionell Loh, Louth Rawshan, Sudipta Chattopadhyay

1908.02203

BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning

Jinyuan Jia, Yupei Liu, Neil Zhenqiang Gong

2108.00352

Differentially Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds

Raef Bassily, Adam Smith, Abhradeep Thakurta

1405.7085

DAWN: Dynamic Adversarial Watermarking of Neural Networks

Sebastian Szyller, Buse Gul Atli, Samuel Marchal, N. Asokan

1906.00830

DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass

Minxin Du, Xiang Yue, Sherman S. M. Chow, Tianhao Wang, Chenyu Huang, Huan Sun

2309.06746

Membership Inference Attacks Against Text-to-image Generation Models

Yixin Wu, Ning Yu, Zheng Li, Michael Backes, Yang Zhang

2210.00968

Protecting Language Generation Models via Invisible Watermarking

Xuandong Zhao, Yu-Xiang Wang, Lei Li

2302.03162

Adversarial Frontier Stitching for Remote Neural Network Watermarking

Erwan Le Merrer, Patrick Perez, Gilles Trédan

1711.01894

Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters

Haibo Jin, Andy Zhou, Joe D. Menke, Haohan Wang

2405.20413

A Security Risk Taxonomy for Prompt-Based Interaction With Large Language Models

Erik Derner, Kristina Batistič, Jan Zahálka, Robert Babuška

2311.11415

Semidefinite relaxations for certifying robustness to adversarial examples

Aditi Raghunathan, Jacob Steinhardt, Percy Liang

1811.01057

Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity

Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Abhradeep Thakurta

1811.12469

Explanations can be manipulated and geometry is to blame

Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel

1906.07983

A Cross-Architecture Instruction Embedding Model for Natural Language Processing-Inspired Binary Code Analysis

Kimberly Redmond, Lannan Luo, Qiang Zeng

1812.09652

Towards Differentially Private Text Representations

Lingjuan Lyu, Yitong Li, Xuanli He, Tong Xiao

2006.14170

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification

Xiaoyu Cao, Neil Zhenqiang Gong

1709.05583

Backdoor Attacks for In-Context Learning with Language Models

Nikhil Kandpal, Matthew Jagielski, Florian Tramèr, Nicholas Carlini

2307.14692

The Limitations of Adversarial Training and the Blind-Spot Attack

Huan Zhang, Hongge Chen, Zhao Song, Duane Boning, Inderjit S. Dhillon, Cho-Jui Hsieh

1901.04684

Safety Alignment Should Be Made More Than Just a Few Tokens Deep

Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, Peter Henderson

2406.05946

ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector

Shang-Tse Chen, Cory Cornelius, Jason Martin, Duen Horng Chau

1804.05810

Dataset Inference: Ownership Resolution in Machine Learning

Pratyush Maini, Mohammad Yaghini, Nicolas Papernot

2104.10706

Scalable Private Learning with PATE

Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson

1802.08908

Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks

Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu

1904.02884

DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models

Bita Darvish Rouhani, Huili Chen, Farinaz Koushanfar

1804.00750

InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents

Qiusi Zhan, Zhixiang Liang, Zifan Ying, Daniel Kang

2403.02691

Property Inference Attacks Against GANs

Junhao Zhou, Yufei Chen, Chao Shen, Yang Zhang

2111.07608

Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences

Borja Balle, Gilles Barthe, Marco Gaboardi

1807.01647

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe

Xiang Yue, Huseyin A. Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Hoda Shajari, Huan Sun, David Levitan, Robert Sim

2210.14348

Reconstruction and Membership Inference Attacks against Generative Models

Benjamin Hilprecht, Martin Härterich, Daniel Bernau

1906.03006

Adversarial Perturbations Against Real-Time Video Classification Systems

Shasha Li, Ajaya Neupane, Sujoy Paul, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy Chowdhury, Ananthram Swami

1807.00458

Can Adversarially Robust Learning Leverage Computational Hardness?

Saeed Mahloujifar, Mohammad Mahmoody

1810.01407

Stealing Hyperparameters in Machine Learning

Binghui Wang, Neil Zhenqiang Gong

1802.05351

SoK: Privacy-Preserving Data Synthesis

Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David Forsyth, Bo Li, Dawn Song

2307.02106

DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations

Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein

2103.02079

SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning

Nishat Koti, Mahak Pancholi, Arpita Patra, Ajith Suresh

2005.10296

Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release

Liam Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein

2103.02683

Signed-Prompt: A New Approach to Prevent Prompt Injection Attacks Against LLM-Integrated Applications

Xuchen Suo

2401.07612

Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning

Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, Yang Zhang

1904.01067

Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game

Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

2311.01011

Locally Differentially Private Sparse Vector Aggregation

Mingxun Zhou, Tianhao Wang, T-H. Hubert Chan, Giulia Fanti, Elaine Shi

2112.03449

A Self-Supervised Descriptor for Image Copy Detection

Ed Pizzi, Sreya Dutta Roy, Sugosh Nagavara Ravindra, Priya Goyal, Matthijs Douze

2202.10261

Adversarial Risk and the Dangers of Evaluating Against Weak Attacks

Jonathan Uesato, Brendan O'Donoghue, Aaron van den Oord, Pushmeet Kohli

1802.05666

Blind Backdoors in Deep Learning Models

Eugene Bagdasaryan, Vitaly Shmatikov

2005.03823

Reconstructing Training Data from Trained Neural Networks

Niv Haim, Gal Vardi, Gilad Yehudai, Ohad Shamir, Michal Irani

2206.07758

A Novel Attribute Reconstruction Attack in Federated Learning

Lingjuan Lyu, Chen Chen

2108.06910

A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems

Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick McDaniel, Chaowei Xiao

2402.18649

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey

Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim Furkan Tekin, Ling Liu

2409.18169

T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification

Ahmadreza Azizi, Ibrahim Asadullah Tahmid, Asim Waheed, Neal Mangaokar, Jiameng Pu, Mobin Javed, Chandan K. Reddy, Bimal Viswanath

2103.04264

Discovering the Hidden Vocabulary of DALLE-2

Giannis Daras, Alexandros G. Dimakis

2206.00169

Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack

Adnan Siraj Rakin, Zhezhi He, Deliang Fan

1811.09310

Stealing Neural Networks via Timing Side Channels

Vasisht Duddu, Debasis Samanta, D Vijay Rao, Valentina E. Balas

1812.11720

Black-box Adversarial Attacks with Limited Queries and Information

Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin

1804.08598

Exploiting Unintended Feature Leakage in Collaborative Learning

Luca Melis, Congzheng Song, Emiliano De Cristofaro, Vitaly Shmatikov

1805.04049

Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning

Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi, Josh Kimball, Ling Liu

2408.09600

A New Analysis of Differential Privacy's Generalization Guarantees

Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Moshe Shenfeld

1909.03577

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks

Pu Zhao, Siyue Wang, Cheng Gongye, Yanzhi Wang, Yunsi Fei, Xue Lin

1905.12032

Federated Model Distillation with Noise-Free Differential Privacy

Lichao Sun, Lingjuan Lyu

2009.05537

Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models

Xinlei He, Zheng Li, Weilin Xu, Cory Cornelius, Yang Zhang

2208.10445

Label-Consistent Backdoor Attacks

Alexander Turner, Dimitris Tsipras, Aleksander Madry

1912.02771

Training with More Confidence: Mitigating Injected and Natural Backdoors During Training

Zhenting Wang, Hailun Ding, Juan Zhai, Shiqing Ma

2202.06382

Quantifying and Mitigating Privacy Risks of Contrastive Learning

Xinlei He, Yang Zhang

2102.04140

InstaHide: Instance-hiding Schemes for Private Distributed Learning

Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora

2010.02772

Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks

Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong

2008.04495

Securify: Practical Security Analysis of Smart Contracts

Petar Tsankov, Andrei Dan, Dana Drachsler Cohen, Arthur Gervais, Florian Buenzli, Martin Vechev

1806.01143

Backdoor Attacks to Graph Neural Networks

Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong

2006.11165

Issues Encountered Deploying Differential Privacy

Simson L. Garfinkel, John M. Abowd, Sarah Powazek

1809.02201

Deepfake Text Detection: Limitations and Opportunities

Jiameng Pu, Zain Sarwar, Sifat Muhammad Abdullah, Abdullah Rehman, Yoonjin Kim, Parantapa Bhattacharya, Mobin Javed, Bimal Viswanath

2210.09421

Differentially Private Empirical Risk Minimization

Kamalika Chaudhuri, Claire Monteleoni, Anand D. Sarwate

0912.0071

The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models

Zihui Wu, Haichang Gao, Jianping He, Ping Wang

2407.17915

Contamination Attacks and Mitigation in Multi-Party Machine Learning

Jamie Hayes, Olga Ohrimenko

1901.02402

Crafting Adversarial Examples For Speech Paralinguistics Applications

Yuan Gong, Christian Poellabauer

1711.03280

Turn the Combination Lock: Learnable Textual Backdoor Attacks via Word Substitution

Fanchao Qi, Yuan Yao, Sophia Xu, Zhiyuan Liu, Maosong Sun

2106.06361

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy

Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Thakurta

2303.00654

Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference

Brandon Reagen, Wooseok Choi, Yeongil Ko, Vincent Lee, Gu-Yeon Wei, Hsien-Hsin S. Lee, David Brooks

2006.00505

Quantitative Verification of Neural Networks And its Security Applications

Teodora Baluta, Shiqi Shen, Shweta Shinde, Kuldeep S. Meel, Prateek Saxena

1906.10395

Composition of Differential Privacy & Privacy Amplification by Subsampling

Thomas Steinke

2210.00597

Jatmo: Prompt Injection Defense by Task-Specific Finetuning

Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen, Zeming Wei, Elizabeth Sun, Basel Alomair, David Wagner

2312.17673

Local Differential Privacy and Its Applications: A Comprehensive Survey

Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam

2008.03686

Differentially Private Learning Needs Better Features (or Much More Data)

Florian Tramèr, Dan Boneh

2011.11660

On Lattices, Learning with Errors, Random Linear Codes, and Cryptography

Oded Regev

2401.03703

Weight Poisoning Attacks on Pre-trained Models

Keita Kurita, Paul Michel, Graham Neubig

2004.06660

Graph Backdoor

Zhaohan Xi, Ren Pang, Shouling Ji, Ting Wang

2006.11890

Unlearnable Examples: Making Personal Data Unexploitable

Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang

2101.04898

Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors

Andrew Ilyas, Logan Engstrom, Aleksander Madry

1807.07978

Generating Phishing Attacks using ChatGPT

Sayak Saha Roy, Krishna Vamsi Naragam, Shirin Nilizadeh

2305.05133

Secure Evaluation of Quantized Neural Networks

Anders Dalskov, Daniel Escudero, Marcel Keller

1910.12435

Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors

Timothy Stevens, Christian Skalka, Christelle Vincent, John Ring, Samuel Clark, Joseph Near

2112.06872

Differentially Private Optimization on Large Model at Small Cost

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

2210.00038

Membership Inference of Diffusion Models

Hailong Hu, Jun Pang

2301.09956

Enhanced Security and Privacy via Fragmented Federated Learning

Najeeb Moharram Jebreel, Josep Domingo-Ferrer, Alberto Blanco-Justicia, David Sanchez

2207.05978

Learning Rate Adaptation for Federated and Differentially Private Learning

Antti Koskela, Antti Honkela

1809.03832

A Data Augmentation-based Defense Method Against Adversarial Attacks in Neural Networks

Yi Zeng, Han Qiu, Gerard Memmi, Meikang Qiu

2007.15290

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias

Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

2304.00010

The Discrete Gaussian for Differential Privacy

Clément L. Canonne, Gautam Kamath, Thomas Steinke

2004.00010

MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples

Nicholas Carlini, David Wagner

1711.08478

Towards Stable and Efficient Training of Verifiably Robust Neural Networks

Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane Boning, Cho-Jui Hsieh

1906.06316

Privacy Amplification by Iteration

Vitaly Feldman, Ilya Mironov, Kunal Talwar, Abhradeep Thakurta

1808.06651

How to Manipulate CNNs to Make Them Lie: the GradCAM Case

Tom Viering, Ziqi Wang, Marco Loog, Elmar Eisemann

1907.10901

Subsampled Rényi Differential Privacy and Analytical Moments Accountant

Yu-Xiang Wang, Borja Balle, Shiva Kasiviswanathan

1808.00087

KNG: The K-Norm Gradient Mechanism

Matthew Reimherr, Jordan Awan

1905.09436

Attack of the Tails: Yes, You Really Can Backdoor Federated Learning

Hongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris Papailiopoulos

2007.05084

CrypTFlow: Secure TensorFlow Inference

Nishant Kumar, Mayank Rathee, Nishanth Chandran, Divya Gupta, Aseem Rastogi, Rahul Sharma

1909.07814

LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale

Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad

2002.05839

Cryptanalytic Extraction of Neural Network Models

Nicholas Carlini, Matthew Jagielski, Ilya Mironov

2003.04884

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson

2007.14191

On the Adversarial Robustness of Multi-Modal Foundation Models

Christian Schlarmann, Matthias Hein

2308.10741

When Does Differentially Private Learning Not Suffer in High Dimensions?

Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta

2207.00160

Improving Adversarial Transferability via Neuron Attribution-Based Attacks

Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu

2204.00008

An Undetectable Watermark for Generative Image Models

Sam Gunn, Xuandong Zhao, Dawn Song

2410.07369

Adversarial Training for Free!

Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein

1904.12843

Multi-granularity Textual Adversarial Attack with Behavior Cloning

Yangyi Chen, Jin Su, Wei Wei

2109.04367

Concurrent Composition Theorems for Differential Privacy

Salil Vadhan, Wanrong Zhang

2207.08335

Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling

Vitaly Feldman, Audra McMillan, Kunal Talwar

2012.12803

Stronger Privacy Amplification by Shuffling for Rényi and Approximate Differential Privacy

Vitaly Feldman, Audra McMillan, Kunal Talwar

2208.04591

How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN

Zheng Li, Chengyu Hu, Yang Zhang, Shanqing Guo

1903.01743

Attacks on Deidentification's Defenses

Aloni Cohen

2202.13470

HEAX: An Architecture for Computing on Encrypted Data

M. Sadegh Riazi, Kim Laine, Blake Pelton, Wei Dai

1909.09731

ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies

Bao Wang, Binjie Yuan, Zuoqiang Shi, Stanley J. Osher

1811.10745

Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing

Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong

1912.09899

ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction

Harsh Chaudhari, Ashish Choudhury, Arpita Patra, Ajith Suresh

1912.02592

Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets

Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma

2002.05990

Knockoff Nets: Stealing Functionality of Black-Box Models

Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz

1812.02766

Private Selection from Private Candidates

Jingcheng Liu, Kunal Talwar

1811.07971

Membership Inference Attack on Graph Neural Networks

Iyiola E. Olatunji, Wolfgang Nejdl, Megha Khosla

2101.06570

Membership Inference Attacks Against Recommender Systems

Minxing Zhang, Zhaochun Ren, Zihan Wang, Pengjie Ren, Zhumin Chen, Pengfei Hu, Yang Zhang

2109.08045

TEM: High Utility Metric Differential Privacy on Text

Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan

2107.07928

Sponge Examples: Energy-Latency Attacks on Neural Networks

Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert Mullins, Ross Anderson

2006.03463

Universal Adversarial Training

Ali Shafahi, Mahyar Najibi, Zheng Xu, John Dickerson, Larry S. Davis, Tom Goldstein

1811.11304

Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks

Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz

1906.10908

Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation

Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, Pushmeet Kohli

1909.01492

Smartphone Sensors for Modeling Human-Computer Interaction: General Outlook and Research Datasets for User Authentication

Alejandro Acien, Aythami Morales, Ruben Vera-Rodriguez, Julian Fierrez

2006.00790

Private Adaptive Gradient Methods for Convex Optimization

Hilal Asi, John Duchi, Alireza Fallah, Omid Javidbakht, Kunal Talwar

2106.13756

One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries

Itay Zloczower, Eyal Lenga, Gilad Gressel, Yisroel Mirsky

2605.14605

Data Poisoning Attacks Against Federated Learning Systems

Vale Tolpegin, Stacey Truex, Mehmet Emre Gursoy, Ling Liu

2007.08432

One-shot Empirical Privacy Estimation for Federated Learning

Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar

2302.03098

Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search

Adnan Siraj Rakin, Zhezhi He, Deliang Fan

1903.12269

Adversarial Demonstration Attacks on Large Language Models

Jiongxiao Wang, Zichen Liu, Keun Hee Park, Zhuojun Jiang, Zhaoheng Zheng, Zhuofeng Wu, Muhao Chen, Chaowei Xiao

2305.14950

Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent

Pu Zhao, Pin-Yu Chen, Siyue Wang, Xue Lin

2002.07891

Bypassing Backdoor Detection Algorithms in Deep Learning

Te Juin Lester Tan, Reza Shokri

1905.13409

Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning

Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft

0911.5708

Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks

Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David Kaeli, Peter Chin, Xue Lin

1809.05165

Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models

Yihong Dong, Xue Jiang, Huanyu Liu, Zhi Jin, Bin Gu, Mengfei Yang, Ge Li

2402.15938

MMA-Diffusion: MultiModal Attack on Diffusion Models

Yijun Yang, Ruiyuan Gao, Xiaosen Wang, Tsung-Yi Ho, Nan Xu, Qiang Xu

2311.17516

Trustworthy AI

Richa Singh, Mayank Vatsa, Nalini Ratha

2011.02272

How to 0wn NAS in Your Spare Time

Sanghyun Hong, Michael Davinroy, Yiğitcan Kaya, Dana Dachman-Soled, Tudor Dumitraş

2002.06776

CodedPrivateML: A Fast and Privacy-Preserving Framework for Distributed Machine Learning

Jinhyun So, Basak Guler, A. Salman Avestimehr

1902.00641

Certified Robustness to Label-Flipping Attacks via Randomized Smoothing

Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, J. Zico Kolter

2002.03018

PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action

Yijia Shao, Tianshi Li, Weiyan Shi, Yanchen Liu, Diyi Yang

2409.00138

Targeted Adversarial Examples for Black Box Audio Systems

Rohan Taori, Amog Kamsetty, Brenton Chu, Nikita Vemuri

1805.07820

The Structure of Optimal Private Tests for Simple Hypotheses

Clément L. Canonne, Gautam Kamath, Audra McMillan, Adam Smith, Jonathan Ullman

1811.11148

Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions

Alberto Blanco-Justicia, Josep Domingo-Ferrer, Sergio Martínez, David Sánchez, Adrian Flanagan, Kuan Eeik Tan

2012.06810

Differentially Private SQL with Bounded User Contribution

Royce J Wilson, Celia Yuxin Zhang, William Lam, Damien Desfontaines, Daniel Simmons-Marengo, Bryant Gipson

1909.01917

Differential Privacy for Text Analytics via Natural Text Sanitization

Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, Sherman S. M. Chow

2106.01221

Multi-Armed Bandits with Local Differential Privacy

Wenbo Ren, Xingyu Zhou, Jia Liu, Ness B. Shroff

2007.03121

Targeted Phishing Campaigns using Large Scale Language Models

Rabimba Karanjai

2301.00665

Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff

Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta

2011.09527

Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems

Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko

2112.05307

Gaussian Shading: Provable Performance-Lossless Image Watermarking for Diffusion Models

Zijin Yang, Kai Zeng, Kejiang Chen, Han Fang, Weiming Zhang, Nenghai Yu

2404.04956

PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously

Songze Li, Mingchao Yu, Chien-Sheng Yang, A. Salman Avestimehr, Sreeram Kannan, Pramod Viswanath

1809.10361

Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression

Nilaksh Das, Madhuri Shanbhogue, Shang-Tse Chen, Fred Hohman, Siwei Li, Li Chen, Michael E. Kounavis, Duen Horng Chau

1802.06816

AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting

Yu Wang, Xiaogeng Liu, Yu Li, Muhao Chen, Chaowei Xiao

2403.09513

Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces

Chaofei Yang, Lei Ding, Yiran Chen, Hai Li

2006.07421

Google COVID-19 Community Mobility Reports: Anonymization Process Description (version 1.1)

Ahmet Aktay, Shailesh Bavadekar, Gwen Cossoul, John Davis, Damien Desfontaines, Alex Fabrikant, Evgeniy Gabrilovich, Krishna Gadepalli, Bryant Gipson, Miguel Guevara, Chaitanya Kamath, Mansi Kansal, Ali Lange, Chinmoy Mandayam, Andrew Oplinger, Christopher Pluntke, Thomas Roessler, Arran Schlosberg, Tomer Shekel, Swapnil Vispute, Mia Vu, Gregory Wellenius, Brian Williams, Royce J Wilson

2004.04145

Calibrating Noise to Variance in Adaptive Data Analysis

Vitaly Feldman, Thomas Steinke

1712.07196

Composition Theorems for Interactive Differential Privacy

Xin Lyu

2207.09397

Towards Sparse Federated Analytics: Location Heatmaps under Distributed Differential Privacy with Secure Aggregation

Eugene Bagdasaryan, Peter Kairouz, Stefan Mellem, Adrià Gascón, Kallista Bonawitz, Deborah Estrin, Marco Gruteser

2111.02356

Pseudorandom Error-Correcting Codes

Miranda Christ, Sam Gunn

2402.09370

Reconstructing Training Data with Informed Adversaries

Borja Balle, Giovanni Cherubin, Jamie Hayes

2201.04845

Attributing Image Generative Models using Latent Fingerprints

Guangyu Nie, Changhoon Kim, Yezhou Yang, Yi Ren

2304.09752

EIFFeL: Ensuring Integrity for Federated Learning

Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten

2112.12727

Secure Deep Graph Generation with Link Differential Privacy

Carl Yang, Haonan Wang, Ke Zhang, Liang Chen, Lichao Sun

2005.00455

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection

Shuhao Chen, Weisen Jiang, Yeqi Gong, Shengda Luo, Chengxiang Zhuo, Zang Li, James T. Kwok, Yu Zhang

2605.28030

Formalizing and Benchmarking Prompt Injection Attacks and Defenses

Yupei Liu, Yuqi Jia, Runpeng Geng, Jinyuan Jia, Neil Zhenqiang Gong

2310.12815

Probe before You Talk: Towards Black-box Defense against Backdoor Unalignment for Large Language Models

Biao Yi, Tiansheng Huang, Sishuo Chen, Tong Li, Zheli Liu, Zhixuan Chu, Yiming Li

2506.16447

Inverting Gradients -- How easy is it to break privacy in federated learning?

Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller

2003.14053

CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning

Biao Yi, Tiansheng Huang, Baolei Zhang, Tong Li, Lihai Nie, Zheli Liu, Li Shen

2505.16559

Subpopulation Data Poisoning Attacks

Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea

2006.14026

Membership Leakage in Label-Only Exposures

Zheng Li, Yang Zhang

2007.15528

(Amplified) Banded Matrix Factorization: A unified approach to private training

Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Keith Rush, Abhradeep Thakurta, Zheng Xu

2306.08153

MetaPoison: Practical General-purpose Clean-label Data Poisoning

W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein

2004.00225

Transferable Clean-Label Poisoning Attacks on Deep Neural Nets

Chen Zhu, W. Ronny Huang, Ali Shafahi, Hengduo Li, Gavin Taylor, Christoph Studer, Tom Goldstein

1905.05897

Deep Leakage from Gradients

Ligeng Zhu, Zhijian Liu, Song Han

1906.08935

Did you hear that? Adversarial Examples Against Automatic Speech Recognition

Moustafa Alzantot, Bharathan Balaji, Mani Srivastava

1801.00554

Private Convex Optimization via Exponential Mechanism

Sivakanth Gopi, Yin Tat Lee, Daogao Liu

2203.00263

A backdoor attack against LSTM-based text classification systems

Jiazhu Dai, Chuanshuai Chen

1905.12457

Privacy Auditing with One (1) Training Run

Thomas Steinke, Milad Nasr, Matthew Jagielski

2305.08846

Robust Aggregation for Federated Learning

Krishna Pillutla, Sham M. Kakade, Zaid Harchaoui

1912.13445

Byzantine-Resilient Secure Federated Learning

Jinhyun So, Basak Guler, A. Salman Avestimehr

2007.11115

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, Hyrum Anderson, Heather Roff, Gregory C. Allen, Jacob Steinhardt, Carrick Flynn, Seán Ó hÉigeartaigh, SJ Beard, Haydn Belfield, Sebastian Farquhar, Clare Lyle, Rebecca Crootof, Owain Evans, Michael Page, Joanna Bryson, Roman Yampolskiy, Dario Amodei

1802.07228

Large Scale Transfer Learning for Differentially Private Image Classification

Harsh Mehta, Abhradeep Thakurta, Alexey Kurakin, Ashok Cutkosky

2205.02973

The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)

Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia

2011.02352

Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks

Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, Pedram Zaree, Yue Dong, Nael Abu-Ghazaleh

2310.10844

Digital image splicing detection based on Markov features in QDCT and QWT domain

Ruxin Wang, Wei Lu, Shijun Xiang, Xianfeng Zhao, Jinwei Wang

1708.08245

Assessing Prompt Injection Risks in 200+ Custom GPTs

Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, Sabrina Yang, Xinyu Xing

2311.11538

Permute-and-Flip: A new mechanism for differentially private selection

Ryan McKenna, Daniel Sheldon

2010.12603

CodeChameleon: Personalized Encryption Framework for Jailbreaking Large Language Models

Huijie Lv, Xiao Wang, Yuansen Zhang, Caishuang Huang, Shihan Dou, Junjie Ye, Tao Gui, Qi Zhang, Xuanjing Huang

2402.16717

Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger

Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis

2206.07136

Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense

Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer

2303.13408

AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks

Chun-Chen Tu, Paishun Ting, Pin-Yu Chen, Sijia Liu, Huan Zhang, Jinfeng Yi, Cho-Jui Hsieh, Shin-Ming Cheng

1805.11770

SoK: Certified Robustness for Deep Neural Networks

Linyi Li, Tao Xie, Bo Li

2009.04131

Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks

Jinyuan Jia, Yupei Liu, Xiaoyu Cao, Neil Zhenqiang Gong

2012.03765

Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors

Zuxuan Wu, Ser-Nam Lim, Larry Davis, Tom Goldstein

1910.14667

Robust and Differentially Private Mean Estimation

Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh

2102.09159

The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure

Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody

1809.03063

Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning

Hyrum S. Anderson, Anant Kharkar, Bobby Filar, David Evans, Phil Roth

1801.08917

Evading Classifiers by Morphing in the Dark

Hung Dang, Yue Huang, Ee-Chien Chang

1705.07535

DeepDGA: Adversarially-Tuned Domain Generation and Detection

Hyrum S. Anderson, Jonathan Woodbridge, Bobby Filar

1610.01969

Adversarial Deep Learning for Robust Detection of Binary Encoded Malware

Abdullah Al-Dujaili, Alex Huang, Erik Hemberg, Una-May O'Reilly

1801.02950

Adversarial vulnerability for any classifier

Alhussein Fawzi, Hamza Fawzi, Omar Fawzi

1802.08686

Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li

2111.02840

CoinPress: Practical Private Mean and Covariance Estimation

Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman

2006.06618

On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians

Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath

2010.09929

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory

Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi

2310.17884

Revisiting Differentially Private Hypothesis Tests for Categorical Data

Yue Wang, Jaewoo Lee, Daniel Kifer

1511.03376

Federated Machine Learning: Concept and Applications

Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong

1902.04885

A Semantic Invariant Robust Watermark for Large Language Models

Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen

2310.06356