Papers citing 'Exploiting Unintended Feature Leakage in Collaborative Learning'

Title
On the Security & Privacy in Federated Learning Gorka Abad S. Picek Víctor Julio Ramírez-Durán A. Urbieta 289 12 0 10 Dec 2021
Membership Inference Attacks From First Principles Nicholas Carlini Steve Chien Milad Nasr Shuang Song Seth Neel Florian Tramèr MIACV MIALM 640 894 0 07 Dec 2021
Location Leakage in Federated Signal MapsIEEE Transactions on Mobile Computing (IEEE TMC), 2021 Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 194 6 0 07 Dec 2021
When the Curious Abandon Honesty: Federated Learning Is Not PrivateEuropean Symposium on Security and Privacy (EuroS&P), 2021 Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 244 220 0 06 Dec 2021
The Impact of Data Distribution on Fairness and Robustness in Federated Learning Mustafa Safa Ozdayi Murat Kantarcioglu FedML OOD 107 5 0 29 Nov 2021
Contextual Combinatorial Multi-output GP Bandits with Group Constraints Sepehr Elahi Baran Atalar Sevda Öğüt Cem Tekin 168 3 0 29 Nov 2021
Decentralized Federated Learning through Proxy Model SharingNature Communications (Nat Commun), 2021 Shivam Kalra Junfeng Wen Jesse C. Cresswell Anthony L. Caterini Hamid R. Tizhoosh FedML 263 144 0 22 Nov 2021
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Chaoyang He Alay Dilipbhai Shah Zhenheng Tang Adarshan Naiynar Sivashunmugam Keerti Bhogaraju Mita Shimpi Li Shen Xiaowen Chu Mahdi Soltanolkotabi Salman Avestimehr VLM FedML 198 79 0 22 Nov 2021
Enhanced Membership Inference Attacks against Machine Learning Models Jiayuan Ye Aadyaa Maddi S. K. Murakonda Vincent Bindschaedler Reza Shokri MIALM MIACV 533 324 0 18 Nov 2021
Property Inference Attacks Against GANsNetwork and Distributed System Security Symposium (NDSS), 2021 Junhao Zhou Yufei Chen Chao Shen Yang Zhang AAML MIACV 240 66 0 15 Nov 2021
Eluding Secure Aggregation in Federated Learning via Model InconsistencyConference on Computer and Communications Security (CCS), 2021 Dario Pasquini Danilo Francati G. Ateniese FedML 544 131 0 14 Nov 2021
Flatee: Federated Learning Across Trusted Execution Environments A. Mondal Yash More Ruthu Hulikal Rooparaghunath Debayan Gupta FedML 89 20 0 12 Nov 2021
Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System Timon Rückel Johannes Sedlmeir Peter Hofmann FedML 189 66 0 11 Nov 2021
Membership Inference Attacks Against Self-supervised Speech ModelsInterspeech (Interspeech), 2021 Wei-Cheng Tseng Wei-Tsung Kao Hung-yi Lee 327 18 0 09 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 176 50 0 08 Nov 2021
FedLess: Secure and Scalable Federated Learning Using Serverless Computing Andreas Grafberger Mohak Chadha Anshul Jindal Jianfeng Gu Michael Gerndt 177 59 0 05 Nov 2021
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation SetupsItalian National Conference on Sensors (INS), 2021 A. Wainakh Ephraim Zimmer Sandeep Subedi Jens Keim Tim Grube Shankar Karuppayah Alejandro Sánchez Guinea Max Mühlhäuser 165 15 0 05 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security PerspectiveIEEE Access (IEEE Access), 2021 Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 227 11 0 05 Nov 2021
Practical and Light-weight Secure Aggregation for Federated Submodel Learning Jamie Cui Cen Chen Tiandi Ye Li Wang FedML 125 2 0 02 Nov 2021
Resource-Efficient Federated LearningEuropean Conference on Computer Systems (EuroSys), 2021 A. Abdelmoniem Atal Narayan Sahu Marco Canini Suhaib A. Fahmy FedML 229 68 0 01 Nov 2021
Revealing and Protecting Labels in Distributed TrainingNeural Information Processing Systems (NeurIPS), 2021 Trung D. Q. Dang Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Peter Chin Franccoise Beaufays 102 29 0 31 Oct 2021
Efficient passive membership inference attack in federated learning Oualid Zari Chuan Xu Giovanni Neglia FedML 224 38 0 31 Oct 2021
10 Security and Privacy Problems in Large Foundation Models Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong 261 11 0 28 Oct 2021
Gradient Inversion with Generative Image PriorNeural Information Processing Systems (NeurIPS), 2021 Jinwoo Jeon Jaechang Kim Kangwook Lee Sewoong Oh Jungseul Ok 167 183 0 28 Oct 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection Chunjong Park Anas Awadalla Tadayoshi Kohno Shwetak N. Patel OOD 167 39 0 26 Oct 2021
DPCOVID: Privacy-Preserving Federated Covid-19 Detection Trang-Thi Ho Yennun Huang OOD FedML 116 4 0 26 Oct 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 333 169 0 25 Oct 2021
DistFL: Distribution-aware Federated Learning for Mobile ScenariosProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (IMWUT), 2021 Bingyan Liu Y. Cai Ziqi Zhang Yan Liang Leye Wang Ding Li Yao Guo Xiangqun Chen OOD FedML 94 10 0 22 Oct 2021
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy Xiaolan Gu Ming Li Lishuang Xiong FedML 137 15 0 22 Oct 2021
Towards General Deep Leakage in Federated Learning Fauzan Farooqui Yongli Mou Feifei Li Qing Li Oya Beyan Stefan Decker Chunming Rong FedML 158 62 0 18 Oct 2021
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture Xinyu Tang Saeed Mahloujifar Liwei Song Virat Shejwalkar Milad Nasr Amir Houmansadr Prateek Mittal 153 102 0 15 Oct 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models Divyat Mahajan Shruti Tople Amit Sharma OOD 207 7 0 07 Oct 2021
Inference Attacks Against Graph Neural Networks Zhikun Zhang Min Chen Michael Backes Yun Shen Yang Zhang MIACV AAML GNN 164 50 0 06 Oct 2021
Securing Federated Learning: A Covert Communication-based Approach Yuan-ai Xie Jiawen Kang Dusit Niyato Nguyen Thi Thanh Van Nguyen Cong Luong Zhixin Liu Han Yu FedML 130 36 0 05 Oct 2021
MixNN: Protection of Federated Learning Against Inference Attacks by Mixing Neural Network LayersInternational Middleware Conference (Middleware), 2021 A. Boutet Thomas LeBrun Jan Aalmoes Adrien Baud FedML 252 18 0 26 Sep 2021
FedProc: Prototypical Contrastive Federated Learning on Non-IID dataFuture generations computer systems (FGCS), 2021 Xutong Mu Yulong Shen Ke Cheng Xueli Geng Jiaxuan Fu Tao Zhang Ruoyu Zhou FedML 190 233 0 25 Sep 2021
InvBERT: Reconstructing Text from Contextualized Word Embeddings by inverting the BERT pipeline Emily M. Bender Timnit Gebru Eric Wallace 156 13 0 21 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 239 20 0 20 Sep 2021
Decentralized Wireless Federated Learning with Differential Privacy Shuzhen Chen Dongxiao Yu Yifei Zou Jiguo Yu Xiuzhen Cheng 205 64 0 19 Sep 2021
Membership Inference Attacks Against Recommender Systems Minxing Zhang Zhaochun Ren Zihan Wang Sudipta Singha Roy Zhumin Chen Pengfei Hu Yang Zhang MIACV AAML 150 114 0 16 Sep 2021
Source Inference Attacks in Federated Learning Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Xuyun Zhang 150 97 0 13 Sep 2021
Critical Learning Periods in Federated Learning Gang Yan Hao Wang Jian Li FedML 183 11 0 12 Sep 2021
Asynchronous Federated Learning on Heterogeneous Devices: A Survey Chenhao Xu Youyang Qu Yong Xiang Longxiang Gao FedML 322 322 0 09 Sep 2021
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning Zhifeng Jiang Wen Wang Yang Liu FedML 163 64 0 02 Sep 2021
Personalised Federated Learning: A Combinational Approach Sone Kyaw Pye Han Yu FedML 137 6 0 22 Aug 2021
A Novel Attribute Reconstruction Attack in Federated Learning Lingjuan Lyu Chong Chen AAML 128 46 0 16 Aug 2021
SAFE: Secure Aggregation with Failover and EncryptionACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 2021 Thomas Sandholm S. Mukherjee Bernardo A. Huberman FedML 202 9 0 12 Aug 2021
Sensing and Mapping for Better Roads: Initial Plan for Using Federated Learning and Implementing a Digital Twin to Identify the Road Conditions in a Developing Country -- Sri Lanka Thilanka Munasinghe H. Pasindu 67 3 0 30 Jul 2021
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and TrustworthinessIEEE Transactions on Artificial Intelligence (IEEE TAI), 2021 Yuwei Sun H. Ochiai Hiroshi Esaki FedML 440 49 0 30 Jul 2021
Precision-Weighted Federated Learning Jonatan Reyes Di-Jorio Lisa Cécile Low-Kam Marta Kersten-Oertel FedML 147 49 0 20 Jul 2021