XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning

28 December 2022

Papers citing "XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning"

42 / 42 papers shown

Title
Data Poisoning Attacks and Defenses to Crowdsourcing Systems Minghong Fang Minghao Sun Qi Li Neil Zhenqiang Gong Jinhua Tian Jia-Wei Liu 77 36 0 18 Feb 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 136 626 0 27 Dec 2020
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation Han Qiu Yi Zeng Shangwei Guo Tianwei Zhang Meikang Qiu B. Thuraisingham AAML 47 191 0 13 Dec 2020
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks Mojan Javaheripi Mohammad Samragh Gregory Fields T. Javidi F. Koushanfar AAML FedML 14 42 0 04 Sep 2020
One-pixel Signature: Characterizing CNN Models for Backdoor Detection Shanjiaoyang Huang Weiqi Peng Zhiwei Jia Zhuowen Tu 8 63 0 18 Aug 2020
Backdoor Learning: A Survey Yiming Li Yong Jiang Zhifeng Li Shutao Xia AAML 73 595 0 17 Jul 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Hongyi Wang Kartik K. Sreenivasan Shashank Rajput Harit Vishwakarma Saurabh Agarwal Jy-yong Sohn Kangwook Lee Dimitris Papailiopoulos FedML 47 595 0 09 Jul 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 231 1,746 0 18 Mar 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 66 644 0 31 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 98 6,177 0 10 Dec 2019
Deep Probabilistic Models to Detect Data Poisoning Attacks Mahesh Subedar Nilesh A. Ahuja R. Krishnan I. Ndiour Omesh Tickoo AAML TDI 17 23 0 03 Dec 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 92 1,093 0 26 Nov 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 56 565 0 18 Nov 2019
NeuronInspect: Detecting Backdoors in Neural Networks via Output Explanations Xijie Huang M. Alzantot Mani B. Srivastava AAML 32 105 0 18 Nov 2019
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy Min Du R. Jia D. Song AAML 41 175 0 16 Nov 2019
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Yue Liu 52 322 0 08 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification T. Hsu Qi Matthew Brown FedML 106 1,128 0 13 Sep 2019
Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems Bao Gia Doan Ehsan Abbasnejad Damith C. Ranasinghe AAML 34 66 0 09 Aug 2019
Model Agnostic Defence against Backdoor Attacks in Machine Learning Sakshi Udeshi Shanshan Peng Gerald Woo Lionell Loh Louth Rawshan Sudipta Chattopadhyay AAML 29 104 0 06 Aug 2019
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Soheil Kolouri Aniruddha Saha Hamed Pirsiavash Heiko Hoffmann AAML 50 232 0 26 Jun 2019
Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation Cong Xie Oluwasanmi Koyejo Indranil Gupta FedML AAML 19 253 0 10 Mar 2019
Attacking Graph-based Classification via Manipulating the Graph Structure Binghui Wang Neil Zhenqiang Gong AAML 58 155 0 01 Mar 2019
STRIP: A Defence Against Trojan Attacks on Deep Neural Networks Yansong Gao Chang Xu Derui Wang Shiping Chen Damith C. Ranasinghe Surya Nepal AAML 51 801 0 18 Feb 2019
A Little Is Enough: Circumventing Defenses For Distributed Learning Moran Baruch Gilad Baruch Yoav Goldberg FedML 26 496 0 16 Feb 2019
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations Jacob Dumford Walter J. Scheirer AAML 39 117 0 07 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 244 1,044 0 29 Nov 2018
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets Liping Li Canran Xu Xiangnan He Yixin Cao Tat-Seng Chua FedML 90 591 0 09 Nov 2018
Poisoning Attacks to Graph-Based Recommender Systems Minghong Fang Guolei Yang Neil Zhenqiang Gong Jia-Wei Liu AAML 49 204 0 11 Sep 2018
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation C. Liao Haoti Zhong Anna Squicciarini Sencun Zhu David J. Miller SILM 67 312 0 30 Aug 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 67 1,892 0 02 Jul 2018
Is feature selection secure against training data poisoning? Huang Xiao Battista Biggio Gavin Brown Giorgio Fumera Claudia Eckert Fabio Roli AAML SILM 36 423 0 21 Apr 2018
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks Ali Shafahi Wenjie Huang Mahyar Najibi Octavian Suciu Christoph Studer Tudor Dumitras Tom Goldstein AAML 73 1,080 0 03 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 57 757 0 01 Apr 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 67 287 0 19 Mar 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 78 1,822 0 15 Dec 2017
Neural Trojans Yuntao Liu Yang Xie Ankur Srivastava AAML 39 351 0 03 Oct 2017
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization Luis Muñoz-González Battista Biggio Ambra Demontis Andrea Paudice Vasin Wongrassamee Emil C. Lupu Fabio Roli AAML 85 628 0 29 Aug 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 72 1,754 0 22 Aug 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 267 4,620 0 18 Oct 2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering Bo Li Yining Wang Aarti Singh Yevgeniy Vorobeychik AAML 53 341 0 29 Aug 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 226 17,235 0 17 Feb 2016
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 77 1,580 0 27 Jun 2012