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

24 February 2017

Papers citing "Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning"

50 / 354 papers shown

Title
Decaf: Data Distribution Decompose Attack against Federated Learning Zhiyang Dai Chunyi Zhou Anmin Fu 39 2 0 24 May 2024
A GAN-Based Data Poisoning Attack Against Federated Learning Systems and Its Countermeasure Wei Sun Bo Gao Ke Xiong Yuwei Wang AAML FedML 48 2 0 19 May 2024
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy Yichuan Shi Olivera Kotevska Viktor Reshniak Abhishek Singh Ramesh Raskar AAML 43 1 0 16 May 2024
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health Systems Amin Aminifar Matin Shokri Amir Aminifar FedML 31 11 0 09 May 2024
MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception Vidit Khazanchi Pavan Kulkarni Yuvaraj Govindarajulu Manojkumar Somabhai Parmar AAML 37 0 0 24 Apr 2024
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning Tanveer Khan Mindaugas Budzys A. Michalas 37 4 0 14 Apr 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks Qiushi Li Yan Zhang Ju Ren Qi Li Yaoxue Zhang AAML PICV 41 23 0 05 Apr 2024
Privacy Re-identification Attacks on Tabular GANs Abdallah Alshantti Adil Rasheed Frank Westad AAML 29 3 0 31 Mar 2024
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning Joshua C. Zhao Ahaan Dabholkar Atul Sharma Saurabh Bagchi FedML 41 2 0 26 Mar 2024
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures S. V. Dibbo Adam Breuer Juston S. Moore Michael Teti AAML 41 4 0 21 Mar 2024
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning Divyansh Jhunjhunwala Shiqiang Wang Gauri Joshi FedML 33 6 0 19 Mar 2024
Efficient and Privacy-Preserving Federated Learning based on Full Homomorphic Encryption Yuqi Guo Lin Li Zhongxiang Zheng Hanrui Yun Ruoyan Zhang Xiaolin Chang Zhixuan Gao FedML 27 1 0 18 Mar 2024
Adaptive Hybrid Masking Strategy for Privacy-Preserving Face Recognition Against Model Inversion Attack Yinggui Wang Yuanqing Huang Jianshu Li Le Yang Kai Song Lei Wang AAML PICV 56 0 0 14 Mar 2024
Developing Federated Time-to-Event Scores Using Heterogeneous Real-World Survival Data Siqi Li Yuqing Shang Ziwen Wang Qiming Wu Chuan Hong Yilin Ning Di Miao M. Ong Bibhas Chakraborty Nan Liu FedML 26 1 0 08 Mar 2024
Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training Tanveer Khan Mindaugas Budzys Khoa Nguyen A. Michalas 48 3 0 06 Mar 2024
Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem Dorjan Hitaj Giulio Pagnotta Fabio De Gaspari Sediola Ruko Briland Hitaj Luigi V. Mancini Fernando Perez-Cruz 42 4 0 06 Mar 2024
Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks Yichang Xu Ming Yin Minghong Fang Neil Zhenqiang Gong OOD FedML 44 6 0 05 Mar 2024
Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks Ehsan Nowroozi Imran Haider R. Taheri Mauro Conti AAML 32 5 0 05 Mar 2024
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks Sayedeh Leila Noorbakhsh Binghui Zhang Yuan Hong Binghui Wang AAML 25 8 0 04 Mar 2024
Enhancing Data Provenance and Model Transparency in Federated Learning Systems -- A Database Approach Michael Gu Ramasoumya Naraparaju Dongfang Zhao FedML 28 0 0 03 Mar 2024
Analysis of Privacy Leakage in Federated Large Language Models Minh Nhat Vu Truc D. T. Nguyen Tre' R. Jeter My T. Thai 45 6 0 02 Mar 2024
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach Qi Tan Qi Li Yi Zhao Zhuotao Liu Xiaobing Guo Ke Xu FedML 42 2 0 02 Mar 2024
PrivatEyes: Appearance-based Gaze Estimation Using Federated Secure Multi-Party Computation Mayar Elfares Pascal Reisert Zhiming Hu Wenwu Tang Ralf Küsters Andreas Bulling FedML 26 4 0 29 Feb 2024
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective Xinjian Luo Yangfan Jiang Fei Wei Yuncheng Wu Xiaokui Xiao Beng Chin Ooi DiffM 46 4 0 28 Feb 2024
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study Natalija Mitic Apostolos Pyrgelis Sinem Sav FedML 58 1 0 25 Feb 2024
CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models Abhishek Singh Gauri Gupta Ritvik Kapila Yichuan Shi Alex Dang Sheshank Shankar Mohammed Ehab Ramesh Raskar FedML 49 0 0 25 Feb 2024
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation Pablo Lemos Sammy N. Sharief Nikolay Malkin Laurence Perreault Levasseur Y. Hezaveh Laurence Perreault-Levasseur Yashar Hezaveh 29 3 0 06 Feb 2024
Privacy and Security Implications of Cloud-Based AI Services : A Survey Alka Luqman Riya Mahesh Anupam Chattopadhyay 30 2 0 31 Jan 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 48 6 0 29 Jan 2024
Decentralized Federated Learning: A Survey on Security and Privacy Ehsan Hallaji R. Razavi-Far M. Saif Boyu Wang Qiang Yang FedML 58 35 0 25 Jan 2024
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them Chao-Jung Liu Boxi Chen Wei Shao Chris Zhang Kelvin Wong Yi Zhang 47 3 0 22 Jan 2024
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning Zhangchen Xu Fengqing Jiang Luyao Niu Jinyuan Jia Radha Poovendran 26 0 0 10 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning Hideaki Takahashi SILM 38 2 0 29 Dec 2023
Federated Continual Learning via Knowledge Fusion: A Survey Xin Yang Hao Yu Xin Gao Hao Wang Junbo Zhang Tianrui Li FedML 38 33 0 27 Dec 2023
Personalized Federated Learning with Attention-based Client Selection Zihan Chen Wenlin Yao Cong Shen FedML 32 8 0 23 Dec 2023
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 50 0 0 17 Dec 2023
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning Yuting Ma Yuanzhi Yao Xiaohua Xu FedML 21 5 0 16 Dec 2023
Topology-Based Reconstruction Prevention for Decentralised Learning Florine W. Dekker Z. Erkin Mauro Conti 35 3 0 08 Dec 2023
AHSecAgg and TSKG: Lightweight Secure Aggregation for Federated Learning Without Compromise Siqing Zhang Yong Liao Pengyuan Zhou FedML 11 2 0 08 Dec 2023
Exploring the Robustness of Decentralized Training for Large Language Models Lin Lu Chenxi Dai Wangcheng Tao Binhang Yuan Yanan Sun Pan Zhou 37 1 0 01 Dec 2023
Survey on AI Ethics: A Socio-technical Perspective Dave Mbiazi Meghana Bhange Maryam Babaei Ivaxi Sheth Patrik Kenfack 23 4 0 28 Nov 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 50 19 0 27 Nov 2023
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning Tre' R. Jeter Truc D. T. Nguyen Raed Alharbi My T. Thai AAML 24 0 0 23 Nov 2023
Decentralized Personalized Online Federated Learning Renzhi Wu Saayan Mitra Xiang Chen Anup Rao FedML 29 2 0 08 Nov 2023
A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning Pengfei Li Zhibo Zhang A. Al‐Sumaiti Naoufel Werghi C. Yeun AAML 26 13 0 21 Oct 2023
Secure Decentralized Learning with Blockchain Xiaoxue Zhang Yifan Hua Chen Qian OOD 40 2 0 10 Oct 2023
Differentially Private Multi-Site Treatment Effect Estimation Tatsuki Koga Kamalika Chaudhuri David Page OOD FedML CML 33 1 0 10 Oct 2023
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning Padmaksha Roy Jaganmohan Chandrasekaran Erin Lanus Laura J. Freeman Jeremy Werner 30 3 0 06 Oct 2023
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models Zhou Yang Zhipeng Zhao Chenyu Wang Jieke Shi Dongsum Kim Donggyun Han David Lo SILM AAML MIACV 45 12 0 02 Oct 2023
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation Xiang Liu Liangxi Liu Feiyang Ye Yunheng Shen Xia Li Linshan Jiang Jialin Li 36 4 0 30 Sep 2023