Exploiting Unintended Feature Leakage in Collaborative Learning

10 May 2018

Luca Melis

Congzheng Song

Emiliano De Cristofaro

Vitaly Shmatikov

FedML

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Papers citing "Exploiting Unintended Feature Leakage in Collaborative Learning"

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ALI-DPFL: Differentially Private Federated Learning with Adaptive Local Iterations Xinpeng Ling Jie Fu Kuncan Wang Haitao Liu Zhili Chen FedML 22 2 0 21 Aug 2023
Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning Yiping Ma Jess Woods Sebastian Angel Antigoni Polychroniadou T. Rabin FedML 11 52 0 19 Aug 2023
Attesting Distributional Properties of Training Data for Machine Learning Vasisht Duddu Anudeep Das Nora Khayata Hossein Yalame T. Schneider Nirmal Asokan 35 5 0 18 Aug 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization Hao Fang Bin Chen Xuan Wang Zhi Wang Shutao Xia 49 32 0 09 Aug 2023
When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection Mohammed Lansari R. Bellafqira K. Kapusta V. Thouvenot Olivier Bettan G. Coatrieux FedML 23 15 0 07 Aug 2023
Private Federated Learning with Dynamic Power Control via Non-Coherent Over-the-Air Computation Anbang Zhang Shuaishuai Guo Shuai Liu 14 2 0 05 Aug 2023
Asynchronous Federated Learning with Bidirectional Quantized Communications and Buffered Aggregation Tomàs Ortega Hamid Jafarkhani FedML 23 6 0 01 Aug 2023
The Applicability of Federated Learning to Official Statistics Joshua Stock Oliver Hauke Julius Weissmann Hannes Federrath FedML 11 1 0 28 Jul 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 30 13 0 27 Jul 2023
Mitigating Cross-client GANs-based Attack in Federated Learning Hong Huang Xinyu Lei Tao Xiang AAML 45 1 0 25 Jul 2023
Security and Privacy Issues of Federated Learning J. Hasan 19 10 0 22 Jul 2023
PATROL: Privacy-Oriented Pruning for Collaborative Inference Against Model Inversion Attacks Shiwei Ding Lan Zhang Miao Pan Xiaoyong Yuan AAML 17 5 0 20 Jul 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 30 22 0 20 Jul 2023
Co(ve)rtex: ML Models as storage channels and their (mis-)applications Md Abdullah Al Mamun Quazi Mishkatul Alam Erfan Shayegani Pedram Zaree Ihsen Alouani Nael B. Abu-Ghazaleh 37 0 0 17 Jul 2023
Information-Theoretically Private Federated Submodel Learning with Storage Constrained Databases Sajani Vithana S. Ulukus FedML 10 0 0 12 Jul 2023
Over-The-Air Federated Learning: Status Quo, Open Challenges, and Future Directions Bingnan Xiao Xichen Yu Wei Ni Xin Wang H. Vincent Poor 25 20 0 03 Jul 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 22 43 0 25 Jun 2023
Locally Differentially Private Distributed Online Learning with Guaranteed Optimality Ziqin Chen Yongqiang Wang 31 3 0 25 Jun 2023
DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum Xiaolan Gu Ming Li Lishuang Xiong FedML 12 4 0 22 Jun 2023
Differentially Private Over-the-Air Federated Learning Over MIMO Fading Channels Hang Liu Jiahe Yan Y. Zhang 16 3 0 19 Jun 2023
Leveraging The Edge-to-Cloud Continuum for Scalable Machine Learning on Decentralized Data A. Abdelmoniem 33 1 0 19 Jun 2023
FedMultimodal: A Benchmark For Multimodal Federated Learning Tiantian Feng Digbalay Bose Tuo Zhang Rajat Hebbar Anil Ramakrishna Rahul Gupta Mi Zhang Salman Avestimehr Shrikanth Narayanan 29 48 0 15 Jun 2023
Privacy Inference-Empowered Stealthy Backdoor Attack on Federated Learning under Non-IID Scenarios Haochen Mei Gaolei Li Jun Wu Longfei Zheng SILM AAML 8 11 0 13 Jun 2023
AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning Ghada Almashaqbeh Zahra Ghodsi FedML 24 1 0 12 Jun 2023
PriSampler: Mitigating Property Inference of Diffusion Models Hailong Hu Jun Pang DiffM 20 3 0 08 Jun 2023
FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs Shanshan Han Baturalp Buyukates Zijian Hu Han Jin Weizhao Jin ... Qifan Zhang Yuhui Zhang Carlee Joe-Wong Salman Avestimehr Chaoyang He SILM 21 12 0 08 Jun 2023
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning Kostadin Garov Dimitar I. Dimitrov Nikola Jovanović Martin Vechev AAML FedML 26 7 0 05 Jun 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 24 46 0 25 May 2023
pFedSim: Similarity-Aware Model Aggregation Towards Personalized Federated Learning Jiahao Tan Yipeng Zhou Gang Liu Jessie Hui Wang Shui Yu FedML 17 13 0 25 May 2023
Privacy Implications of Retrieval-Based Language Models Yangsibo Huang Samyak Gupta Zexuan Zhong K. Li Danqi Chen RALM 25 29 0 24 May 2023
PrivaScissors: Enhance the Privacy of Collaborative Inference through the Lens of Mutual Information Lin Duan Jingwei Sun Yiran Chen M. Gorlatova 24 2 0 17 May 2023
Private Training Set Inspection in MLaaS Mingxue Xu Tongtong Xu Po-Yu Chen 17 0 0 15 May 2023
Securing Distributed SGD against Gradient Leakage Threats Wenqi Wei Ling Liu Jingya Zhou Ka-Ho Chow Yanzhao Wu FedML 16 18 0 10 May 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 22 11 0 10 May 2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information Kiwan Maeng Chuan Guo Sanjay Kariyappa G. E. Suh 11 8 0 06 May 2023
Over-the-Air Federated Averaging with Limited Power and Privacy Budgets Na Yan Kezhi Wang Cunhua Pan K. K. Chai Feng Shu Jiangzhou Wang FedML 25 2 0 05 May 2023
Reconstructing Training Data from Multiclass Neural Networks G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Michal Irani 25 4 0 05 May 2023
MLHOps: Machine Learning for Healthcare Operations Kristoffer Larsen Vallijah Subasri A. Krishnan Cláudio Tinoco Mesquita Diana Paez Laleh Seyyed-Kalantari Amalia Peix LM&MA AI4TS VLM 27 2 0 04 May 2023
Efficient Federated Learning with Enhanced Privacy via Lottery Ticket Pruning in Edge Computing Yi Shi Kang Wei Li Shen Jun Li Xueqian Wang Bo Yuan Song Guo 33 5 0 02 May 2023
Exactly Optimal and Communication-Efficient Private Estimation via Block Designs Hyun-Young Park Seungsoo Nam Si-Hyeon Lee 21 3 0 02 May 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy Yi Shi Kang Wei Li Shen Yingqi Liu Xueqian Wang Bo Yuan Dacheng Tao FedML 28 2 0 01 May 2023
Private Information Retrieval and Its Applications: An Introduction, Open Problems, Future Directions Sajani Vithana Zhusheng Wang S. Ulukus 25 5 0 27 Apr 2023
Blockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things Aditya Pribadi Kalapaaking Ibrahim Khalil Mohammad Saidur Rahman Mohammed Atiquzzaman X. Yi Mahathir Almashor FedML 13 65 0 25 Apr 2023
Secure Split Learning against Property Inference, Data Reconstruction, and Feature Space Hijacking Attacks Yunlong Mao Zexi Xin Zhenyu Li Jue Hong Qingyou Yang Sheng Zhong MIACV AAML 18 10 0 19 Apr 2023
Permutation Equivariance of Transformers and Its Applications Hengyuan Xu Liyao Xiang Hang Ye Dixi Yao Pengzhi Chu Baochun Li 17 13 0 16 Apr 2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense Yue-li Cui Syed Imran Ali Meerza Zhuohang Li Luyang Liu Jiaxin Zhang Jian-Dong Liu AAML FedML 21 4 0 11 Apr 2023
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding Yuke Hu Wei Liang Ruofan Wu Kai Y. Xiao Weiqiang Wang Xiaochen Li Jinfei Liu Zhan Qin 20 8 0 06 Apr 2023
FACE-AUDITOR: Data Auditing in Facial Recognition Systems Min Chen Zhikun Zhang Tianhao Wang Michael Backes Yang Zhang CVBM 25 14 0 05 Apr 2023
Scalable and Privacy-Preserving Federated Principal Component Analysis D. Froelicher Hyunghoon Cho Manaswitha Edupalli João Sá Sousa Jean-Philippe Bossuat Apostolos Pyrgelis J. Troncoso-Pastoriza Bonnie Berger Jean-Pierre Hubaux FedML 13 15 0 31 Mar 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 11 6 0 28 Mar 2023