Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection

29 October 2019

Chao Shen

Papers citing "Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection"

20 / 20 papers shown

Title
Decentralized and Robust Privacy-Preserving Model Using Blockchain-Enabled Federated Deep Learning in Intelligent Enterprises Reza Fotohi Fereidoon Shams Aliee Bahar Farahani FedML 82 8 0 18 Feb 2025
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning Ning Wang Shanghao Shi Yang Xiao Yimin Chen Y. T. Hou W. Lou FedML AAML 48 1 0 12 Jul 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 36 16 0 02 Feb 2024
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks Jorge Castillo Phillip Rieger Hossein Fereidooni Qian Chen Ahmad Sadeghi FedML AAML 43 8 0 03 Oct 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 27 4 0 06 Jun 2023
New data poison attacks on machine learning classifiers for mobile exfiltration M. A. Ramírez Sangyoung Yoon Ernesto Damiani H. A. Hamadi C. Ardagna Nicola Bena Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 35 4 0 20 Oct 2022
CrowdGuard: Federated Backdoor Detection in Federated Learning Phillip Rieger T. Krauß Markus Miettinen Alexandra Dmitrienko Ahmad-Reza Sadeghi Technical University Darmstadt AAML FedML 32 22 0 14 Oct 2022
Combined Federated and Split Learning in Edge Computing for Ubiquitous Intelligence in Internet of Things: State of the Art and Future Directions Qiang Duan Shijing Hu Ruijun Deng Zhihui Lu FedML 39 61 0 20 Jul 2022
Performance Weighting for Robust Federated Learning Against Corrupted Sources Dimitris Stripelis M. Abram J. Ambite FedML 28 7 0 02 May 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 25 37 0 21 Feb 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments Joost Verbraeken M. Vos J. Pouwelse 31 4 0 21 Oct 2021
Evaluation of Federated Learning in Phishing Email Detection Chandra Thapa Jun Tang A. Abuadbba Yansong Gao S. Çamtepe Surya Nepal Mahathir Almashor Yifeng Zheng FedML 25 16 0 27 Jul 2020
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach Yi Liu S. Garg Jiangtian Nie Yan Zhang Zehui Xiong Jiawen Kang M. S. Hossain FedML 39 378 0 19 Jul 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 31 640 0 16 Jul 2020
Local Differential Privacy based Federated Learning for Internet of Things Yang Zhao Jun Zhao Mengmeng Yang Teng Wang Ning Wang Lingjuan Lyu Dusit Niyato Kwok-Yan Lam 27 292 0 19 Apr 2020
VeriML: Enabling Integrity Assurances and Fair Payments for Machine Learning as a Service Lingchen Zhao Qian Wang Cong Wang Qi Li Chao Shen Xiaodong Lin Bo Feng Minxin Du VLM 13 86 0 16 Sep 2019
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 136 186 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,034 0 29 Nov 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 359 5,849 0 08 Jul 2016