Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting

Yeom, Samuel, Giacomelli, Irene, Fredrikson, Matt, Jha, Somesh·2018·2018 IEEE 31st Computer Security Foundations Symposium (CSF)

Cited by (998)

Items 601–700 of 998

  1. Output regeneration defense against membership inference attacks for protecting data privacy
    Yong Ding, Peixiong Huang, Hai Liang, Yuan Fang, Huiyong Wang · 2023 · International Journal of Web Information Systems
  2. PILLAR: How to make semi-private learning more effective
    Francesco Pinto, Yaxi Hu, Fanny Yang, Amartya Sanyal · 2024 · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
  3. Comparison of LSTM and MLP Trained Under Differential Privacy for Intrusion Detection
    Daniel Machooka, Xiaohong Yuan, Kaushik Roy, Guenvere Chen · 2024 · International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD)
  4. Do Backdoors Assist Membership Inference Attacks?
    Yumeki Goto, Nami Ashizawa, Toshiki Shibahara, Naoto Yanai · 2024 · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
  5. Decaf: Data Distribution Decompose Attack Against Federated Learning
    Zhiyang Dai, Yansong Gao, Chunyi Zhou, Anmin Fu, Zhi Zhang, Minhui Xue, Yifeng Zheng, Yuqing Zhang · 2024 · IEEE Transactions on Information Forensics and Security
  6. RMR: A Relative Membership Risk Measure for Machine Learning Models
    Li Bai, Haibo Hu, Qingqing Ye, Jianliang Xu, Jin Li, Chengfang Fang, Jie Shi · 2025 · IEEE Transactions on Dependable and Secure Computing
  7. Investigating privacy leakage in dimensionality reduction methods via reconstruction attack
    Chayadon Lumbut, Donlapark Ponnoprat · 2025 · Journal of Information Security and Applications
  8. Adaptive multi-scale fast and flexible denoising network for SNR enhancement in Φ-OTDR events detection
    Isaack Adidas Kamanga, Zhi Wang, Guo‐Qing Zhu, Fei Liu, Xian Chong Zhou · 2025 · Optics Communications
  9. Trustworthiness of Stochastic Gradient Descent in Distributed Learning
    Hongyang Li, Caesar Wu, Mohammed Chadli, Saïd Mammar, Pascal Bouvry · 2025 · European Control Conference (ECC)
  10. “What did you say?”: Extracting unintentional secrets from predictive text learning systems
    Gwyn Wilkinson, Phil Legg · 2020 · International Conference on Cyber Security and Protection of Digital Services (Cyber Security)
  11. A Study of Differentially Private Machine Learning in Healthcare
    Abdur R. Shahid, Saiedul Talukder · 2021 · Innovations in Intelligent Systems and Applications Conference (ASYU)
  12. LTU Attacker for Membership Inference
    Joseph Pedersen, Rafael Muñoz Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, Isabelle Guyon · 2022 · Algorithms
  13. Privacy-Preserving and Reliable Federated Learning
    Yi Lu, Lei Zhang, Lulu Wang, Yuan-Yuan Gao · 2022 · Lecture notes in computer science
  14. Exploration of Membership Inference Attack on Convolutional Neural Networks and Its Defenses
    Yimian Yao · 2022 · International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)
  15. Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data
    Pratik Karmakar, Debabrota Basu · 2023 · HAL
  16. Ultimate Power of Inference Attacks: Privacy Risks of Learning High-Dimensional Graphical Models
    Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos · 2019 · arXiv (Cornell University)
  17. The Bayes Security Measure
    Konstantinos Chatzikokolakis A, Giovanni Cherubin, Catuscia Palamidessi A, Carmela Troncoso · 2020 · arXiv (Cornell University)
  18. Robustness, Privacy, and Generalization of Adversarial Training
    Fengxiang He, Shaopeng Fu, Wang, Bohan, Dacheng Tao · 2020 · arXiv (Cornell University)
  19. Killing Two Birds with One Stone: Stealing Model and Inferring Attribute from BERT-based APIs.
    Lingjuan Lyu, Xuanli He, Fangzhao Wu, Lichao Sun · 2021 · arXiv (Cornell University)
  20. Anti-Neuron Watermarking: Protecting Personal Data Against Unauthorized Neural Model Training.
    Zihang Zou, Boqing Gong, Liqiang Wang · 2021 · arXiv (Cornell University)
  21. A Survey of Image Gradient Inversion Against Federated Learning
    Zhaohua Li, Le Wang, Guangyao Chen, Muhammad Shafq, Zhaoquan Gu · 2022
  22. Bayes Security: A Not So Average Metric
    Konstantinos Chatzikokolakis A, Giovanni Cherubin, Catuscia Palamidessi A, Carmela Troncoso · 2020 · arXiv (Cornell University)
  23. Not All Tokens Are Equal: Membership Inference Attacks Against Fine-tuned Language Models
    Changtian Song, Dongdong Zhao, Jianwen Xiang · 2024 · Annual Computer Security Applications Conference
  24. Poisoning as a Post-Protection: Mitigating Membership Privacy Leakage From Gradient and Prediction of Federated Models
    Gaoyang Liu, Tianlong Xu, Yang Yang, Ahmed M. Abdelmoniem, Chen Wang, Jiangchuan Liu · 2025 · IEEE Transactions on Dependable and Secure Computing
  25. Intelligent Attacks and Defense Methods in Federated Learning-Enabled Energy-Efficient Wireless Networks
    Han Zhang, Hao Zhou, Medhat Elsayed, Majid Bavand, Raimundas Gaigalas, Yigit Ozcan, Melike Erol‐Kantarci · 2025 · IEEE Transactions on Wireless Communications
  26. CODP: Improving Differentially Private Federated Learning by Cascading and Offsetting Noises Between Iterations
    Runze Wang, Yipeng Zhou, Jiahao Liu, Xuezheng Liu, Miao Hu, Di Wu, Quan Z. Sheng, Song Guo · 2025 · IEEE Transactions on Dependable and Secure Computing
  27. On the Impact of Uncertainty and Calibration on Likelihood-Ratio Membership Inference Attacks
    Meiyi Zhu, Caili Guo, Chunyan Feng, Osvaldo Simeone · 2025 · IEEE Transactions on Information Forensics and Security
  28. Defenses Against Membership Inference Attacks on Unlearned Data
    Josep Domingo‐Ferrer, Najeeb Jebreel, David Sánchez · 2025 · Lecture notes in computer science
  29. Untargeted Poisoning Membership Inference With Sample Selection and Enhancement
    Jian Li, Xiaochun Yang, Wanlun Ma, Bin Wang, Sheng Wen, Yang Xiang · 2025 · IEEE Transactions on Dependable and Secure Computing
  30. Federated Learning With Individualized Privacy Through Client Sampling
    Lucas Lange, Ole Borchardt, Erhard Rahm · 2025 · International Conference on Machine Learning Technologies (ICMLT)
  31. CodeCleaner: Mitigating Data Contamination for LLM Benchmarking
    Cao, Jialun, Chen, Songqiang, Zhang, Wuqi, Lo, Hau Ching, Li, Yeting, Cheung, Shing-Chi · 2025 · Proceedings of the 16th International Conference on Internetware
  32. GraphGRU-Ed: Leveraging Graph-Based Imputation and Deep Learning for MOOC Completion Prediction
    Thu Nguyen, Kha Nguyen, Phuong Thi Bich Nguyen, Khoa Tan Vo, Thu-Thuy Ta, Phuc Nguyen, Tri Nguyen, Tu-Anh Nguyen-Hoang · 2025 · IEEE Access
  33. Iterative Contextual Consent: AI-enabled Data Privacy Contracts
    Daniel D. Slate, Chaoran Chen, Yaxing Yao, Toby Jia-Jun Li · 2025
  34. DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation
    Xinyu Gao, Xiangtao Meng, Yingkai Dong, Zheng Li, Shanqing Guo · 2025 · ACM SIGSAC Conference on Computer and Communications Security (CCS)
  35. GateBleed: Exploiting On-Core Accelerator Power Gating for High Performance and Stealthy Attacks on AI
    Joshua Kalyanapu, Farshad Dizani, Darsh Asher, Azam Ghanbari, Rosario Cammarota, Aydın Aysu, Samira Mirbagher Ajorpaz · 2025 · IEEE/ACM International Symposium on Microarchitecture (MICRO)
  36. Tighter privacy auditing of differentially private stochastic gradient descent in the hidden state threat model
    Apeksha Bhuekar · 2026 · Scientific Reports
  37. Security in AI Systems
    Anurag Reddy Ekkati, Sai Kiran Taduri, Naresh Reddy Nimmala · 2026 · Springer eBooks
  38. Co-Creation by Human–AI Sophimatics Framework and Applications
    Gerardo Iovane, Giovanni Iovane · 2026 · Algorithms
  39. Meeting SLO with Privacy: Partial Homomorphic Encryption Inference and Anomaly Gating for Predictive Autoscaling in Cloud Environments
    Alan Chuang, Melody Moh, Teng-Sheng Moh · 2026 · 2012 International Conference on Computing, Networking and Communications (ICNC)
  40. Data protection in the era of large language models: challenges and opportunities
    Zvinodashe Revesai, Colletor Tendeukai Chipfumbu · 2026 · AI and Ethics
  41. Towards Privacy in Deep Learning
    Florian Kerschbaum · 2021 · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
  42. SPGC: Integration of Secure Multiparty Computation and Differential Privacy for Gradient Computation on Collaborative Learning
    Kazuki Iwahana, Naoto Yanai, Jason Paul Cruz, Toru Fujiwara · 2022 · Journal of Information Processing
  43. Resilient and Verifiable Federated Learning against Byzantine Colluding Attacks
    Georges A. Kamhoua, Eranga Bandara, Peter B. Foytik, Priyanka Aggarwal, Sachin S. Shetty · 2021 · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
  44. Membership Inference Attacks on Aggregated Time Series with Linear Programming
    Antonin Voyez, Tristan Allard, Gildas Avoine, Pierre Cauchois, Élisa Fromont, Matthieu Simonin · 2022 · International Conference on Security and Cryptography
  45. Membership Inference Attack in Face of Data Transformations
    Jiyu Chen, Yiwen Guo, Hao Chen, Neil Zhenqiang Gong · 2022 · IEEE Conference on Communications and Network Security
  46. Inference Attacks and Counterattacks in Federated Learning
    Shui Yu, Lei Cui · 2022 · Digital Privacy and Security
  47. CRJ 700 Longitudinal Aerodynamic Coefficients Identification using Support Vector Machine
    Yvan Tondji, Georges Ghazi, Ruxandra Mihaela Botez · 2023 · AIAA AVIATION Forum
  48. Exploring and Exploiting Data-Free Model Stealing
    Chi Hong, Jiyue Huang, Robert Birke, Lydia Y. Chen · 2023 · Lecture notes in computer science
  49. Computer Security – ESORICS 2023
    Gene Tsudik, Mauro Conti, Kaitai Liang, Georgios Smaragdakis · 2024 · Lecture notes in computer science
  50. GanNoise: Defending against black-box membership inference attacks by countering noise generation
    Jiaming Liang, Teng Huang, Zidan Luo, Dan Li, Yunhao Li, Ziyu Ding · 2023 · International Conference on Data Security and Privacy Protection (DSPP)
  51. Membership Inference Attacks Against the Graph Classification
    Junze Yang, Hongwei Li, Wenshu Fan, Xilin Zhang, Meng Hao · 2023 · Globecom
  52. Nob-MIAs: Non-biased Membership Inference Attacks Assessment on Large Language Models with Ex-Post Dataset Construction
    Cédric Eichler, Nathan Champeil, Nicolas Anciaux, Alexandra Bensamoun, Héber H. Arcolezi, Jose Maria De Fuentes · 2024 · Lecture notes in computer science
  53. SoK: Unintended Interactions among Machine Learning Defenses and Risks
    Vasisht Duddu, Sebastian Szyller, N. Asokan · 2024 · IEEE Symposium on Security and Privacy (S&P)
  54. Label-Only Membership Inference Attack Based on Model Explanation
    Yao Ma, Xurong Zhai, Dan Yu, Yuli Yang, Xingyu Wei, Yongle Chen · 2024 · Neural Processing Letters
  55. Towards a Game-Theoretic Understanding of Explanation-Based Membership Inference Attacks
    Kavita Kumari, Murtuza S. Jadliwala, Sumit Kumar Jha, Anindya Maiti · 2024 · Lecture notes in computer science
  56. Navigating Differential Privacy Constraints in Machine Learning
    Trung Ha, Tran Khanh Dang · 2024 · Communications in computer and information science
  57. Leveraging Multiple Adversarial Perturbation Distances for Enhanced Membership Inference Attack in Federated Learning
    Fan Xia, Yuhao Liu, Bo Jin, Zheng Yu, Xingwei Cai, Hao Li, Zhiyong Zha, Dai Hou, Kai Peng · 2024 · Symmetry
  58. Assessing Membership Inference Attacks under Distribution Shifts
    Shi Yichuan, Olivera Kotevska, Viktor Reshniak, Amir Sadovnik · 2024 · IEEE International Conference on Big Data (BigData)
  59. Universal and Efficient Adversarial Training Framework With Membership Inference Resistance
    Ran Yan, Ruiying Du, Kun He, Jing Chen, Qiao Li, Cong Wu · 2025 · IEEE Internet of Things Journal
  60. On the Account Security Risks Posed by Password Strength Meters
    Ming Xu, Weili Han, Jitao Yu, Jing Liu, Xinyi Zhang, Yun Lin, Jin Song Dong · 2025 · ACM Asia Conference on Computer and Communications Security (ASIA CCS)
  61. Active Attribute Inference Against Well-Generalized Models In Federated Learning
    Catarina Gomes, Ricardo Mendes, João P. Vilela · 2025 · IEEE European Symposium on Security and Privacy
  62. The mosaic memory of large language models
    Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye · 2026 · Nature Communications
  63. A High-Recall Membership Inference Attack Based on Confidence-Thresholding Method with Relaxed Assumption
    Lulu Wang, Xiaoyu Zhang, Yi Xie, Xu Ma, Meixia Miao · 2020 · Lecture notes in computer science
  64. MiDA: Membership inference attacks against domain adaptation
    Yuanjie Zhang, Lingchen Zhao, Qian Wang · 2023 · ISA Transactions
  65. Prediction of anterior cruciate ligament injury from MRI using deep learning
    Nguyen Khanh Hung Truong, P.T.A. Nguyen, Quang Hien Kha, Ngoc Hoang Le, Văn Tuấn Lê, Thi Cao, Ho Thanh Lam Luu, Nguyen Quoc Khanh Le, Jiunn‐Horng Kang · 2021 · International Forum on Medical Imaging in Asia (IFMIA)
  66. How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models
    Matthew Jagielski, Stanley L. Wu, Alina Oprea, Jonathan Ullman, Roxana Geambasu · 2023 · Proceedings on Privacy Enhancing Technologies
  67. Privacy in Practice: Private COVID-19 Detection in X-Ray Images
    Lucas Lange, Maja Schneider, Peter Christen, Erhard Rahm · 2023 · International Conference on Security and Cryptography
  68. ASRA-Q: AI Security Risk Assessment by Selective Questions
    Jun Yajima, Maki Inui, Takanori Oikawa, Fumiyoshi Kasahara, Kentaro Tsuji, Ikuya Morikawa, Nobukazu Yoshioka · 2023 · Journal of Information Processing
  69. Reducing Model Memorization to Mitigate Membership Inference Attacks
    Mehrdad Sheikhjaberi, Dima Alhadidi · 2023 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  70. Program Analysis for Adaptive Data Analysis
    Jiawen Liu, Weihao Qu, Marco Gaboardi, Deepak Garg, Jonathan Ullman · 2024 · Proceedings of the ACM on Programming Languages
  71. Balancing Privacy and Attack Utility: Calibrating Sample Difficulty for Membership Inference Attacks in Transfer Learning
    Shuwen Liu, Yongfeng Qian, Yixue Hao · 2024 · IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S)
  72. PrivGen: Preserving Privacy of Sequences Through Data Generation
    Sigal Shaked, Lior Rokach · 2020 · arXiv (Cornell University)
  73. Robust Membership Encoding: Inference Attacks and Copyright Protection for Deep Learning
    Congzheng Song, Reza Shokri · 2019 · arXiv (Cornell University)
  74. GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning
    Vasisht Duddu, Antoine Boutet, Virat Shejwalkar · 2020 · arXiv (Cornell University)
  75. Unexpected Information Leakage of Differential Privacy Due to Linear Property of Queries
    Wen Cai Huang, Shijie Zhou, Yongjian Liao · 2020 · arXiv (Cornell University)
  76. Federated Learning of Artificial Neural Networks
    Péter T. Kiss · 2022 · Eötvös Loránd Tudományegyetem
  77. Fundamental Limits of Membership Inference Attacks on Machine Learning Models
    Eric Aubinais, Élisabeth Gassiat, Pablo Piantanida · 2023 · arXiv (Cornell University)
  78. On the Importance of Encrypting Deep Features
    Xingyang Ni, Heikki J. Huttunen, Esa Rahtu · 2021 · IEEE International Conference on Computer Vision Workshops
  79. Evaluating the Impact of Adversarial Factors on Membership Inference Attacks
    Ben Niu, Jingwei Sun, Yahong Chen, Likun Zhang, Jin Ping Cao, Kui Geng, Fenghua Li · 2023 · IEEE Smart World Congress (SWC)
  80. Robustness and Privacy for Green Learning under Noisy Labels
    De Li, Tiange Xia, Qiyu Li, Xianxian Li, Jinyan Wang · 2023 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  81. MUSO: achieving exact machine unlearning in over-parameterized regimes
    Ruikai Yang, Mingzhen He, Zhengbao He, Youmei Qiu, Xiaolin Huang · 2025 · Machine Learning
  82. Measuring Local and Shuffled Privacy of Gradient Randomized Response
    Marin Matsumoto, Tsubasa Takahashi, Seng Pei Liew, Masato Oguchi · 2024 · Journal of Information Processing
  83. FLDS: differentially private federated learning with double shufflers
    Qingqiang Qi, Xingye Yang, Chengyu Hu, Peng Tang, Zhiyuan Su, Shanqing Guo · 2024 · The Computer Journal
  84. Preserving Privacy During Reinforcement Learning With AI Feedback
    David Gao, Ian J. Miller, Ali Ataeemh Allami, Dan Lin · 2024 · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)
  85. Reliability, Resiliency, and Responsibility: A Framework for Addressing Security Concerns in Large Language Models
    Linsey Sara Passarella, Edmon Begoli, Colin J. Smith, Amir Sadovnik · 2025 · SN Computer Science
  86. LossControl: Defending Membership Inference Attacks by Controlling the Loss
    Bo Yang, Hongwei Yang, Renhao Lu, Hui Xin He, Weizhe Zhang, Haoyu He, Rahul Yadav · 2025 · IEEE International Conference on Acoustics Speech and Signal Processing
  87. Do Fairness Interventions Come at the Cost of Privacy: Evaluations for Binary Classifiers
    Huan Tian, Guangsheng Zhang, Bo Liu, Tianqing Zhu, Ming Ding, Wanlei Zhou · 2025 · IEEE Transactions on Dependable and Secure Computing
  88. Is Client Unlearning Really Necessary in Federating Learning?
    Alessio Mora, Paolo Bellavista · 2025 · International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
  89. Active Source Inference Attack Based on Label-Flipping in Federated Learning
    Lening Zhang, Hui Xia · 2024 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  90. Membership Inference Attacks Fueled by Few-Shot Learning to Detect Privacy Leakage and Address Data Integrity
    Daniel Jiménez-López, Nuria Rodríguez-Barroso, M. Victoria Luzón, Javier Del Ser, Francisco Herrera · 2025 · Machine Learning and Knowledge Extraction
  91. Auditing Differential Privacy Guarantees Using Density Estimation
    Antti Koskela, Jafar Aco Mohammadi · 2025 · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
  92. On the Reliability of Membership Inference Attacks
    Amrita Roy Chowdhury, Zhifeng Kong, Kamalika Chaudhuri · 2025 · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
  93. Trustworthiness in Vision-Language Models
    Katie Vu, Phung Lai · 2025 · Lecture notes in computer science
  94. Data Chameleon: A Self-adaptive Synthetic Data Management System
    Qianying Liao, Maarten Kesters, Dimitri Van Landuyt, Wouter Joosen · 2025 · Lecture notes in computer science
  95. Enhancing Membership Inference Attacks in Federated Learning Based on Overfitting Property
    Xiaoyan Yin, Yangyang Li, Congrui Bai, Qingjie Han, Yanjiao Chen · 2024 · International Conference on Mobility, Sensing and Networking (MSN)
  96. Variance-Based Membership Inference Attacks Against Large-Scale Image Captioning Models
    Daniel Samira, Edan Habler, Yuval Elovici, Asaf Shabtai · 2025 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  97. Dual-Server Privacy-Preserving Collaborative Deep Learning: A Round-Efficient, Dynamic and Lossless Approach
    Lulu Wang, Lei Zhang, Kim‐Kwang Raymond Choo, Josep Domingo‐Ferrer, Mauro Conti, Yuanyuan Gao · 2025 · IEEE Transactions on Dependable and Secure Computing
  98. Challenges of identification and anonymity in time-continuous data from medical environments
    F. Hammer, Thorsten Strufe · 2025 · Frontiers in Digital Health
  99. A2E: Black-Box Anti-Adversarial Example Based Watermarking to Verify Federated Unlearning
    Xiangshan Gao, Jingyi Wang, Zhikun Zhang, Jialuo Chen, Peng Cheng, Jiming Chen · 2025 · IEEE Transactions on Dependable and Secure Computing
  100. Mitigating Membership Inference Attacks via Generative Denoising Mechanisms
    Zonghuang Yang, Xiaolong Yan, Guoguang Chen, Xiaoli Tian · 2025 · Mathematics