Membership Inference Attacks against Machine Learning Models

18 October 2016

Papers citing "Membership Inference Attacks against Machine Learning Models"

50 / 2,058 papers shown

Title
LTU Attacker for Membership Inference Joseph Pedersen Rafael Munoz-Gómez Jiangnan Huang Haozhe Sun Wei-Wei Tu Isabelle M Guyon 44 1 0 04 Feb 2022
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks Jan Aalmoes Vasisht Duddu A. Boutet 26 10 0 04 Feb 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference Jasper Tan Blake Mason Hamid Javadi Richard G. Baraniuk FedML 45 19 0 02 Feb 2022
Towards Fast and Accurate Federated Learning with non-IID Data for Cloud-Based IoT Applications Tian Liu Jiahao Ding Ting Wang Miao Pan Mingsong Chen 11 7 0 29 Jan 2022
Bounding Training Data Reconstruction in Private (Deep) Learning Chuan Guo Brian Karrer Kamalika Chaudhuri Laurens van der Maaten 115 53 0 28 Jan 2022
Toward Training at ImageNet Scale with Differential Privacy Alexey Kurakin Shuang Song Steve Chien Roxana Geambasu Andreas Terzis Abhradeep Thakurta 46 100 0 28 Jan 2022
Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics T. Ryffel Francis R. Bach D. Pointcheval 29 21 0 28 Jan 2022
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders Tianshuo Cong Xinlei He Yang Zhang 26 53 0 27 Jan 2022
An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications Hitoshi Kiya AprilPyone Maungmaung Yuma Kinoshita Shoko Imaizumi Sayaka Shiota 32 58 0 26 Jan 2022
Variational Model Inversion Attacks Kuan-Chieh Wang Yanzhe Fu Ke Li Ashish Khisti R. Zemel Alireza Makhzani MIACV 30 95 0 26 Jan 2022
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization Ildikó Pilán Pierre Lison Lilja Ovrelid Anthia Papadopoulou David Sánchez Montserrat Batet AILaw 40 80 0 25 Jan 2022
Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models Shagufta Mehnaz S. V. Dibbo Ehsanul Kabir Ninghui Li E. Bertino MIACV 50 60 0 23 Jan 2022
FedComm: Federated Learning as a Medium for Covert Communication Dorjan Hitaj Giulio Pagnotta Briland Hitaj Fernando Perez-Cruz L. Mancini FedML 32 10 0 21 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 37 213 0 20 Jan 2022
Enhancing the Security & Privacy of Wearable Brain-Computer Interfaces Zahra Tarkhani Lorena Qendro Malachy O'Connor Brown Oscar Hill Cecilia Mascolo Anil Madhavapeddy 21 9 0 19 Jan 2022
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders Zeyang Sha Xinlei He Ning Yu Michael Backes Yang Zhang 35 34 0 19 Jan 2022
A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis Qi A. An Ruijiang Li Lin Gu Hao Zhang Qingyu Chen Zhiyong Lu Fei Wang Yingying Zhu OOD 26 4 0 18 Jan 2022
Towards Adversarial Evaluations for Inexact Machine Unlearning Shashwat Goel Ameya Prabhu Amartya Sanyal Ser-Nam Lim Philip Torr Ponnurangam Kumaraguru AAML ELM MU 54 51 0 17 Jan 2022
Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN) Edan Habler Ron Bitton D. Avraham D. Mimran Eitan Klevansky Oleg Brodt Heiko Lehmann Yuval Elovici A. Shabtai AAML 46 12 0 16 Jan 2022
StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning Yupei Liu Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong MIACV 16 24 0 15 Jan 2022
Zero-Shot Machine Unlearning Vikram S Chundawat Ayush K Tarun Murari Mandal Mohan S. Kankanhalli MU 19 120 0 14 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 50 161 0 13 Jan 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 44 22 0 12 Jan 2022
Deletion-Compliance in the Absence of Privacy Jonathan Godin Philippe Lamontagne AILaw 16 3 0 10 Jan 2022
Differentially Private Generative Adversarial Networks with Model Inversion Dongjie Chen S. Cheung Chen-Nee Chuah Sally Ozonoff SyDa 26 13 0 10 Jan 2022
Privacy-aware Early Detection of COVID-19 through Adversarial Training Omid Rohanian Samaneh Kouchaki A. Soltan Jenny Yang Morteza Rohanian Yang Yang David Clifton AAML OOD 38 6 0 09 Jan 2022
Learning to be adversarially robust and differentially private Jamie Hayes Borja Balle M. P. Kumar FedML 15 5 0 06 Jan 2022
DP-FP: Differentially Private Forward Propagation for Large Models Jian Du Haitao Mi 32 5 0 29 Dec 2021
Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Settings Tiantian Feng H. Hashemi Rajat Hebbar M. Annavaram Shrikanth S. Narayanan 28 25 0 26 Dec 2021
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 32 48 0 25 Dec 2021
SoK: A Study of the Security on Voice Processing Systems Robert Chang Logan Kuo Arthur Liu Nader Sehatbakhsh 24 0 0 24 Dec 2021
DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine Learning Ismat Jarin Birhanu Eshete AAML 22 10 0 24 Dec 2021
Counterfactual Memorization in Neural Language Models Chiyuan Zhang Daphne Ippolito Katherine Lee Matthew Jagielski Florian Tramèr Nicholas Carlini 34 129 0 24 Dec 2021
Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applications Jin Li B. Cairns Jingsong Li T. Zhu SyDa 46 70 0 22 Dec 2021
Distributed Machine Learning and the Semblance of Trust Dmitrii Usynin Alexander Ziller Daniel Rueckert Jonathan Passerat-Palmbach Georgios Kaissis 24 1 0 21 Dec 2021
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 36 9 0 19 Dec 2021
Correlation inference attacks against machine learning models Ana-Maria Creţu Florent Guépin Yves-Alexandre de Montjoye MIACV AAML 43 6 0 16 Dec 2021
Model Stealing Attacks Against Inductive Graph Neural Networks Yun Shen Xinlei He Yufei Han Yang Zhang 24 60 0 15 Dec 2021
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing Xiao Han Yuncong Yang Junjie Wu 21 1 0 15 Dec 2021
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis Bingzhe Wu Zhicong Liang Yatao Bian Chaochao Chen Junzhou Huang Yuan Yao 29 1 0 14 Dec 2021
Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors Timothy Stevens Christian Skalka C. Vincent J. Ring Samuel Clark Joseph P. Near FedML 37 71 0 13 Dec 2021
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer Shiye Lei Zhuozhuo Tu Leszek Rutkowski Feng Zhou Li Shen Fengxiang He Dacheng Tao BDL 31 2 0 12 Dec 2021
SoK: Anti-Facial Recognition Technology Emily Wenger Shawn Shan Haitao Zheng Ben Y. Zhao PICV 34 13 0 08 Dec 2021
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Andreas Terzis Florian Tramèr MIACV MIALM 36 646 0 07 Dec 2021
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 40 46 0 07 Dec 2021
Defending against Model Stealing via Verifying Embedded External Features Yiming Li Linghui Zhu Xiaojun Jia Yong Jiang Shutao Xia Xiaochun Cao AAML 43 62 0 07 Dec 2021
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning Vasisht Duddu S. Szyller Nadarajah Asokan 32 12 0 04 Dec 2021
FedRAD: Federated Robust Adaptive Distillation Stefán Páll Sturluson Samuel Trew Luis Muñoz-González Matei Grama Jonathan Passerat-Palmbach Daniel Rueckert A. Alansary FedML 21 17 0 02 Dec 2021
Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu Matthew B. Blaschko 35 5 0 01 Dec 2021
Adversarial Attacks Against Deep Generative Models on Data: A Survey Hui Sun Tianqing Zhu Zhiqiu Zhang Dawei Jin Wanlei Zhou AAML 50 42 0 01 Dec 2021