PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments

29 April 2021

Hamed Haddadi

Papers citing "PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments"

33 / 33 papers shown

Title
Federated Learning for Cyber Physical Systems: A Comprehensive Survey Minh K. Quan P. Pathirana M. Wijayasundara S. Setunge Dinh C. Nguyen Christopher G. Brinton David J. Love H. Vincent Poor AI4CE 49 0 0 08 May 2025
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 48 0 0 13 Mar 2025
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Zhihui Zhao Xiaorong Dong Yimo Ren Jianhua Wang Dan Yu Hongsong Zhu Yongle Chen 77 0 0 24 Feb 2025
Poisoning Prevention in Federated Learning and Differential Privacy via Stateful Proofs of Execution Norrathep Rattanavipanon Ivan de Oliviera Nunes 78 0 0 28 Jan 2025
A performance analysis of VM-based Trusted Execution Environments for Confidential Federated Learning Bruno Casella FedML 32 0 0 20 Jan 2025
Laminator: Verifiable ML Property Cards using Hardware-assisted Attestations Vasisht Duddu Oskari Jarvinen Lachlan J. Gunn Nirmal Asokan 67 1 0 25 Jun 2024
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices Han Zhang Zifan Wang Mihir Dhamankar Matt Fredrikson Yuvraj Agarwal 41 2 0 02 Jun 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 36 23 0 05 Apr 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 23 16 0 02 Feb 2024
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 37 0 0 17 Dec 2023
Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges Vishnu Pandi Chellapandi Liangqi Yuan Christopher G. Brinton Stanislaw H. .Zak Ziran Wang FedML 31 75 0 21 Aug 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 33 244 0 20 Jul 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 16 4 0 06 Jun 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
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups Ioannis Arapakis P. Papadopoulos Kleomenis Katevas Diego Perino 19 7 0 26 Feb 2023
FLINT: A Platform for Federated Learning Integration Ewen N. Wang Ajaykumar Kannan Yuefeng Liang Boyi Chen Mosharaf Chowdhury 33 24 0 24 Feb 2023
Federated Gradient Matching Pursuit Halyun Jeong Deanna Needell Jing Qin FedML 35 1 0 20 Feb 2023
Does Federated Learning Really Need Backpropagation? H. Feng Tianyu Pang Chao Du Wei-Neng Chen Shuicheng Yan Min-Bin Lin FedML 26 10 0 28 Jan 2023
Personalised Federated Learning On Heterogeneous Feature Spaces A. Rakotomamonjy Maxime Vono H. M. Ruiz L. Ralaivola FedML 18 8 0 26 Jan 2023
Enhancing Efficiency in Multidevice Federated Learning through Data Selection Fan Mo Mohammad Malekzadeh S. Chatterjee F. Kawsar Akhil Mathur FedML 30 2 0 08 Nov 2022
A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications Maryna Kapitonova P. Kellmeyer S. Vogt T. Ball 16 8 0 19 Sep 2022
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning Hua Ma Qun Li Yifeng Zheng Zhi Zhang Xiaoning Liu Yan Gao S. Al-Sarawi Derek Abbott FedML 21 3 0 19 Jul 2022
DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware H. Hashemi Yongqin Wang M. Annavaram FedML 18 58 0 30 Jun 2022
Edge Security: Challenges and Issues Xin Jin Charalampos Katsis Fan Sang Jiahao Sun A. Kundu Ramana Rao Kompella 39 8 0 14 Jun 2022
Private delegated computations using strong isolation Mathias Brossard Guilhem Bryant Basma El Gaabouri Xinxin Fan Alexandre Ferreira ... Dominic P. Mulligan Nick Spinale Eric van Hensbergen Hugo J. M. Vincent Shale Xiong 26 4 0 06 May 2022
Towards Battery-Free Machine Learning and Inference in Underwater Environments Yuchen Zhao Sayed Saad Afzal Waleed Akbar Osvy Rodriguez Fan Mo David E. Boyle Fadel M. Adib Hamed Haddadi 3DV 25 19 0 16 Feb 2022
FedComm: Federated Learning as a Medium for Covert Communication Dorjan Hitaj Giulio Pagnotta B. Hitaj F. Pérez-Cruz L. Mancini FedML 25 10 0 21 Jan 2022
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 56 9 0 05 Nov 2021
Minimum Viable Device Drivers for ARM TrustZone Liwei Guo F. Lin 24 18 0 15 Oct 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 24 100 0 10 Aug 2021
Federated Learning with Buffered Asynchronous Aggregation John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 13 288 0 11 Jun 2021
L $^2$ -GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks Yuning You Tianlong Chen Zhangyang Wang Yang Shen GNN 98 82 0 30 Mar 2020
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018