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The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

22 February 2018

Papers citing "The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks"

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On the Practicality of Differential Privacy in Federated Learning by Tuning Iteration Times Yao Fu Yipeng Zhou Di Wu Shui Yu Yonggang Wen Chao Li FedML 144 12 0 11 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine LearningIEEE Symposium on Security and Privacy (IEEE S&P), 2021 Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 315 261 0 11 Jan 2021
Investigating Memorization of Conspiracy Theories in Text GenerationFindings (Findings), 2021 Sharon Levy Michael Stephen Saxon Wenjie Wang 149 21 0 02 Jan 2021
KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models Yuta Nakamura S. Hanaoka Y. Nomura Naoto Hayashi O. Abe Shuntaro Yada Shoko Wakamiya Nara Institute of Science MIACV 268 8 0 31 Dec 2020
Extracting Training Data from Large Language ModelsUSENIX Security Symposium (USENIX Security), 2020 Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 1.1K 2,422 0 14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning?Symposium on the Theory of Computing (STOC), 2020 Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 535 115 0 11 Dec 2020
Modifying Memories in Transformer Models Chen Zhu A. S. Rawat Manzil Zaheer Srinadh Bhojanapalli Daliang Li Felix X. Yu Sanjiv Kumar KELM 281 242 0 01 Dec 2020
Revolutionizing Medical Data Sharing Using Advanced Privacy Enhancing Technologies: Technical, Legal and Ethical SynthesisJournal of Medical Internet Research (JMIR), 2020 J. Scheibner J. Raisaro J. Troncoso-Pastoriza M. Ienca J. Fellay E. Vayena Jean-Pierre Hubaux 86 92 0 27 Oct 2020
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries Seng Pei Liew Tsubasa Takahashi MIACV FedML 157 10 0 27 Oct 2020
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity AnalysisUSENIX Security Symposium (USENIX Security), 2020 Xudong Pan Mi Zhang Yifan Yan Jiaming Zhu Zhemin Yang AAML 183 24 0 26 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 663 806 0 19 Oct 2020
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and VectorizationNeural Information Processing Systems (NeurIPS), 2020 P. Subramani Nicholas Vadivelu Gautam Kamath 301 86 0 18 Oct 2020
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep LearningACM Symposium on Applied Computing (SAC), 2020 Vasisht Duddu A. Boutet Virat Shejwalkar GNN 169 4 0 02 Oct 2020
Quantifying Privacy Leakage in Graph EmbeddingInternational Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous), 2020 Vasisht Duddu A. Boutet Virat Shejwalkar MIACV 187 145 0 02 Oct 2020
Oblivious Sampling Algorithms for Private Data Analysis Sajin Sasy O. Ohrimenko FedML 148 19 0 28 Sep 2020
STAN: Synthetic Network Traffic Generation with Generative Neural Models Shengzhe Xu Manish Marwah M. Arlitt Naren Ramakrishnan DiffM AI4TS 102 37 0 27 Sep 2020
RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language ModelsFindings (Findings), 2020 Samuel Gehman Suchin Gururangan Maarten Sap Yejin Choi Noah A. Smith 655 1,440 0 24 Sep 2020
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning S. Kadhe Nived Rajaraman O. O. Koyluoglu Kannan Ramchandran FedML 224 187 0 23 Sep 2020
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images Ming Y. Lu Dehan Kong Jana Lipkova Richard J. Chen Rajendra Singh Drew F. K. Williamson Tiffany Y. Chen Faisal Mahmood FedML MedIm 243 207 0 21 Sep 2020
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data HidingIEEE Symposium on Security and Privacy (IEEE S&P), 2020 Sahar Abdelnabi Mario Fritz WaLM 284 182 0 07 Sep 2020
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model S. Hahn Junghye Lee FedML 113 2 0 29 Aug 2020
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching Farzin Haddadpour Belhal Karimi Ping Li Xiaoyun Li FedML 132 35 0 11 Aug 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 272 62 0 29 Jul 2020
Label-Only Membership Inference AttacksInternational Conference on Machine Learning (ICML), 2020 Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 502 589 0 28 Jul 2020
Tempered Sigmoid Activations for Deep Learning with Differential PrivacyAAAI Conference on Artificial Intelligence (AAAI), 2020 Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 333 194 0 28 Jul 2020
ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning S. K. Murakonda Reza Shokri 147 96 0 18 Jul 2020
A Survey of Privacy Attacks in Machine LearningACM Computing Surveys (ACM CSUR), 2020 M. Rigaki Sebastian Garcia PILM AAML 263 280 0 15 Jul 2020
The Trade-Offs of Private Prediction Laurens van der Maaten Awni Y. Hannun 161 27 0 09 Jul 2020
Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment Abhishek Gupta Erick Galinkin 64 4 0 09 Jul 2020
Private Speech Classification with Secure Multiparty Computation Kyle Bittner Martine De Cock Rafael Dowsley 202 1 0 01 Jul 2020
Measuring Memorization Effect in Word-Level Neural Networks Probing Rudolf Rosa Tomáš Musil David Marevcek 171 4 0 29 Jun 2020
Best-Effort Adversarial Approximation of Black-Box Malware Classifiers A. Ali Birhanu Eshete AAML 115 7 0 28 Jun 2020
Free-rider Attacks on Model Aggregation in Federated Learning Yann Fraboni Richard Vidal Marco Lorenzi FedML 291 153 0 21 Jun 2020
Flexible Dataset Distillation: Learn Labels Instead of Images Ondrej Bohdal Yongxin Yang Timothy M. Hospedales DD 261 119 0 15 Jun 2020
Auditing Differentially Private Machine Learning: How Private is Private SGD?Neural Information Processing Systems (NeurIPS), 2020 Matthew Jagielski Jonathan R. Ullman Alina Oprea FedML 129 294 0 13 Jun 2020
Report from the NSF Future Directions Workshop, Toward User-Oriented Agents: Research Directions and Challenges M. Eskénazi Tiancheng Zhao LLMAG AI4TS AI4CE 190 9 0 10 Jun 2020
Trade-offs between membership privacy & adversarially robust learning Jamie Hayes SILM 172 3 0 08 Jun 2020
On the Difficulty of Membership Inference Attacks Shahbaz Rezaei Xin Liu MIACV 151 15 0 27 May 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated LearningACM Transactions on Knowledge Discovery from Data (TKDD), 2020 Xinjian Luo Xiangqi Zhu FedML 610 29 0 27 Apr 2020
Have you forgotten? A method to assess if machine learning models have forgotten data Xiao Liu Sotirios A. Tsaftaris FedML OOD MU 104 27 0 21 Apr 2020
Information Leakage in Embedding ModelsConference on Computer and Communications Security (CCS), 2020 Congzheng Song A. Raghunathan MIACV 373 317 0 31 Mar 2020
Learn to Forget: Machine Unlearning via Neuron MaskingIEEE Transactions on Dependable and Secure Computing (TDSC), 2020 Yang Liu Zhuo Ma Ximeng Liu Jian Liu Zhongyuan Jiang Jianfeng Ma Philip Yu K. Ren MU 175 80 0 24 Mar 2020
Systematic Evaluation of Privacy Risks of Machine Learning ModelsUSENIX Security Symposium (USENIX Security), 2020 Liwei Song Prateek Mittal MIACV 611 445 0 24 Mar 2020
The Future of Digital Health with Federated Learningnpj Digital Medicine (NPJ Digit Med), 2020 Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 415 2,226 0 18 Mar 2020
Cryptanalytic Extraction of Neural Network ModelsAnnual International Cryptology Conference (CRYPTO), 2020 Nicholas Carlini Matthew Jagielski Ilya Mironov FedML MLAU MIACV AAML 411 151 0 10 Mar 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 334 80 0 09 Mar 2020
Federating Recommendations Using Differentially Private PrototypesPattern Recognition (Pattern Recognit.), 2020 Mónica Ribero Jette Henderson Sinead Williamson H. Vikalo FedML 133 42 0 01 Mar 2020
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping Sanghyun Hong Varun Chandrasekaran Yigitcan Kaya Tudor Dumitras Nicolas Papernot AAML 167 148 0 26 Feb 2020
Approximate Data Deletion from Machine Learning ModelsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Zachary Izzo Mary Anne Smart Kamalika Chaudhuri James Zou MU 226 310 0 24 Feb 2020
Differentially Private Set UnionInternational Conference on Machine Learning (ICML), 2020 Sivakanth Gopi P. Gulhane Janardhan Kulkarni J. Shen Milad Shokouhi Sergey Yekhanin FedML 154 34 0 22 Feb 2020