Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks

19 March 2018

Papers citing "Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks"

50 / 132 papers shown

Title
A Survey on Poisoning Attacks Against Supervised Machine Learning Wenjun Qiu AAML 22 9 0 05 Feb 2022
How to Backdoor HyperNetwork in Personalized Federated Learning? Phung Lai Nhathai Phan Issa M. Khalil Abdallah Khreishah Xintao Wu AAML FedML 23 0 0 18 Jan 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 29 21 0 12 Jan 2022
LoMar: A Local Defense Against Poisoning Attack on Federated Learning Xingyu Li Zhe Qu Shangqing Zhao Bo Tang Zhuo Lu Yao-Hong Liu AAML 33 92 0 08 Jan 2022
SoK: A Study of the Security on Voice Processing Systems Robert Chang Logan Kuo Arthur Liu Nader Sehatbakhsh 14 0 0 24 Dec 2021
Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors Ruoxi Sun Minhui Xue Gareth Tyson Tian Dong Shaofeng Li Shuo Wang Haojin Zhu S. Çamtepe Surya Nepal AAML 41 14 0 19 Nov 2021
An Overview of Backdoor Attacks Against Deep Neural Networks and Possible Defences Wei Guo B. Tondi Mauro Barni AAML 19 65 0 16 Nov 2021
Get a Model! Model Hijacking Attack Against Machine Learning Models A. Salem Michael Backes Yang Zhang AAML 15 28 0 08 Nov 2021
10 Security and Privacy Problems in Large Foundation Models Jinyuan Jia Hongbin Liu Neil Zhenqiang Gong 11 7 0 28 Oct 2021
Towards Robust Reasoning over Knowledge Graphs Zhaohan Xi Ren Pang Changjiang Li S. Ji Xiapu Luo Xusheng Xiao Ting Wang 15 0 0 27 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data Shuang Luo Didi Zhu Zexi Li Chao-Xiang Wu FedML 22 7 0 26 Oct 2021
Demystifying the Transferability of Adversarial Attacks in Computer Networks Ehsan Nowroozi Yassine Mekdad Mohammad Hajian Berenjestanaki Mauro Conti Abdeslam El Fergougui AAML 31 32 0 09 Oct 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap Luke E. Richards A. Nguyen Ryan Capps Steven D. Forsythe Cynthia Matuszek Edward Raff AAML 33 7 0 23 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 30 16 0 20 Sep 2021
Avengers Ensemble! Improving Transferability of Authorship Obfuscation Muhammad Haroon Muhammad Fareed Zaffar P. Srinivasan Zubair Shafiq AAML 14 8 0 15 Sep 2021
Accumulative Poisoning Attacks on Real-time Data Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu 24 20 0 18 Jun 2021
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization Lixu Wang Shichao Xu Ruiqi Xu Xiao Wang Qi Zhu AAML 11 45 0 13 Jun 2021
Topological Detection of Trojaned Neural Networks Songzhu Zheng Yikai Zhang H. Wagner Mayank Goswami Chao Chen AAML 24 40 0 11 Jun 2021
Gradient-based Data Subversion Attack Against Binary Classifiers Rosni Vasu Sanjay Seetharaman Shubham Malaviya Manish Shukla S. Lodha AAML 11 0 0 31 May 2021
Broadly Applicable Targeted Data Sample Omission Attacks Guy Barash E. Farchi Sarit Kraus Onn Shehory AAML 8 0 0 04 May 2021
Turning Federated Learning Systems Into Covert Channels Gabriele Costa Fabio Pinelli S. Soderi Gabriele Tolomei FedML 37 10 0 21 Apr 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry Yingqi Liu Guangyu Shen Guanhong Tao Zhenting Wang Shiqing Ma X. Zhang AAML 22 8 0 16 Mar 2021
Robust learning under clean-label attack Avrim Blum Steve Hanneke Jian Qian Han Shao OOD 14 8 0 01 Mar 2021
Oriole: Thwarting Privacy against Trustworthy Deep Learning Models Liuqiao Chen Hu Wang Benjamin Zi Hao Zhao Minhui Xue Hai-feng Qian PICV 11 4 0 23 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges Ayodeji Oseni Nour Moustafa Helge Janicke Peng Liu Z. Tari A. Vasilakos AAML 34 48 0 09 Feb 2021
A Real-time Defense against Website Fingerprinting Attacks Shawn Shan A. Bhagoji Haitao Zheng Ben Y. Zhao AAML 14 19 0 08 Feb 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 108 611 0 27 Dec 2020
Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems Moshe Kravchik Battista Biggio A. Shabtai AAML 11 28 0 23 Dec 2020
The Translucent Patch: A Physical and Universal Attack on Object Detectors Alon Zolfi Moshe Kravchik Yuval Elovici A. Shabtai AAML 18 88 0 23 Dec 2020
TrojanZoo: Towards Unified, Holistic, and Practical Evaluation of Neural Backdoors Ren Pang Zheng-Wei Zhang Xiangshan Gao Zhaohan Xi S. Ji Peng Cheng Xiapu Luo Ting Wang AAML 27 31 0 16 Dec 2020
Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks Jinyuan Jia Yupei Liu Xiaoyu Cao Neil Zhenqiang Gong AAML 21 72 0 07 Dec 2020
BaFFLe: Backdoor detection via Feedback-based Federated Learning Sébastien Andreina G. Marson Helen Möllering Ghassan O. Karame FedML 29 137 0 04 Nov 2020
Blockchain based Attack Detection on Machine Learning Algorithms for IoT based E-Health Applications Thippa Reddy Gadekallu Manoj M K Sivarama Krishnan S Neeraj Kumar S. Hakak S. Bhattacharya OOD 22 54 0 03 Nov 2020
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers T. Shapira David Berend Ishai Rosenberg Yang Liu A. Shabtai Yuval Elovici AAML 13 4 0 30 Oct 2020
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 24 5 0 26 Oct 2020
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models A. Salem Yannick Sautter Michael Backes Mathias Humbert Yang Zhang AAML SILM AI4CE 17 38 0 06 Oct 2020
Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud Zhuo Ma Jianfeng Ma Yinbin Miao Ximeng Liu K. Choo R. Deng FedML 12 32 0 23 Sep 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl W. R. Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 19 215 0 04 Sep 2020
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection Luca Demetrio Scott E. Coull Battista Biggio Giovanni Lagorio A. Armando Fabio Roli AAML 17 59 0 17 Aug 2020
Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks Jinyuan Jia Xiaoyu Cao Neil Zhenqiang Gong SILM 8 128 0 11 Aug 2020
Trojaning Language Models for Fun and Profit Xinyang Zhang Zheng-Wei Zhang Shouling Ji Ting Wang SILM AAML 9 131 0 01 Aug 2020
The Price of Tailoring the Index to Your Data: Poisoning Attacks on Learned Index Structures Evgenios M. Kornaropoulos Silei Ren R. Tamassia AAML 11 17 0 01 Aug 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 23 637 0 16 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain Ishai Rosenberg A. Shabtai Yuval Elovici L. Rokach AAML 26 12 0 05 Jul 2020
Subpopulation Data Poisoning Attacks Matthew Jagielski Giorgio Severi Niklas Pousette Harger Alina Oprea AAML SILM 16 112 0 24 Jun 2020
Graph Backdoor Zhaohan Xi Ren Pang S. Ji Ting Wang AI4CE AAML 12 163 0 21 Jun 2020
On Adversarial Bias and the Robustness of Fair Machine Learning Hong Chang Ta Duy Nguyen S. K. Murakonda Ehsan Kazemi Reza Shokri FaML OOD FedML 6 50 0 15 Jun 2020
Arms Race in Adversarial Malware Detection: A Survey Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 8 52 0 24 May 2020
VerifyTL: Secure and Verifiable Collaborative Transfer Learning Zhuo Ma Jianfeng Ma Yinbin Miao Ximeng Liu Wei Zheng K. Choo R. Deng AAML 11 3 0 18 May 2020
Bullseye Polytope: A Scalable Clean-Label Poisoning Attack with Improved Transferability H. Aghakhani Dongyu Meng Yu-Xiang Wang Christopher Kruegel Giovanni Vigna AAML 15 105 0 01 May 2020