Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

15 December 2017

Papers citing "Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning"

37 / 387 papers shown

Title
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems Yue Wang Esha Sarkar Wenqing Li Michail Maniatakos Saif Eddin Jabari AAML 23 60 0 17 Mar 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 13 71 0 09 Mar 2020
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers Giorgio Severi J. Meyer Scott E. Coull Alina Oprea AAML SILM 29 18 0 02 Mar 2020
NNoculation: Catching BadNets in the Wild A. Veldanda Kang Liu Benjamin Tan Prashanth Krishnamurthy Farshad Khorrami Ramesh Karri Brendan Dolan-Gavitt S. Garg AAML OnRL 11 20 0 19 Feb 2020
Radioactive data: tracing through training Alexandre Sablayrolles Matthijs Douze Cordelia Schmid Hervé Jégou 38 74 0 03 Feb 2020
Label-Consistent Backdoor Attacks Alexander Turner Dimitris Tsipras A. Madry AAML 11 383 0 05 Dec 2019
Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic Zhen Xiang David J. Miller Hang Wang G. Kesidis AAML 34 9 0 18 Nov 2019
REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Data Xinyun Chen Wenxiao Wang Chris Bender Yiming Ding R. Jia Bo-wen Li D. Song AAML 27 107 0 17 Nov 2019
RIGA: Covert and Robust White-Box Watermarking of Deep Neural Networks Tianhao Wang Florian Kerschbaum AAML 19 36 0 31 Oct 2019
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning Xuanqing Liu Si Si Xiaojin Zhu Yang Li Cho-Jui Hsieh AAML 35 78 0 30 Oct 2019
Defending Neural Backdoors via Generative Distribution Modeling Ximing Qiao Yukun Yang H. Li AAML 21 183 0 10 Oct 2019
Detecting AI Trojans Using Meta Neural Analysis Xiaojun Xu Qi Wang Huichen Li Nikita Borisov Carl A. Gunter Bo-wen Li 28 321 0 08 Oct 2019
Detection of Backdoors in Trained Classifiers Without Access to the Training Set Zhen Xiang David J. Miller G. Kesidis AAML 24 23 0 27 Aug 2019
Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems Bao Gia Doan Ehsan Abbasnejad Damith C. Ranasinghe AAML 27 66 0 09 Aug 2019
Helen: Maliciously Secure Coopetitive Learning for Linear Models Wenting Zheng Raluca A. Popa Joseph E. Gonzalez Ion Stoica FedML 27 144 0 16 Jul 2019
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking Ziqi Yang Hung Dang E. Chang AAML 27 34 0 14 Jun 2019
Bypassing Backdoor Detection Algorithms in Deep Learning T. Tan Reza Shokri FedML AAML 39 149 0 31 May 2019
A backdoor attack against LSTM-based text classification systems Jiazhu Dai Chuanshuai Chen SILM 8 320 0 29 May 2019
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder Ji Feng Qi-Zhi Cai Zhi-Hua Zhou AAML 19 104 0 22 May 2019
Assuring the Machine Learning Lifecycle: Desiderata, Methods, and Challenges Rob Ashmore R. Calinescu Colin Paterson AI4TS 27 116 0 10 May 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks David J. Miller Zhen Xiang G. Kesidis AAML 19 35 0 12 Apr 2019
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning Shahbaz Rezaei Xin Liu SILM AAML 33 46 0 08 Apr 2019
Design of intentional backdoors in sequential models Zhaoyuan Yang N. Iyer Johan Reimann Nurali Virani SILM AAML 17 38 0 26 Feb 2019
A new Backdoor Attack in CNNs by training set corruption without label poisoning Mauro Barni Kassem Kallas B. Tondi AAML 29 348 0 12 Feb 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 19 74 0 08 Jan 2019
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations Jacob Dumford Walter J. Scheirer AAML 22 116 0 07 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,033 0 29 Nov 2018
AdVersarial: Perceptual Ad Blocking meets Adversarial Machine Learning K. Makarychev Pascal Dupré Yury Makarychev Giancarlo Pellegrino Dan Boneh AAML 29 64 0 08 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 19 11 0 08 Sep 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 15 497 0 14 Aug 2018
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks Kang Liu Brendan Dolan-Gavitt S. Garg AAML 24 1,021 0 30 May 2018
Hu-Fu: Hardware and Software Collaborative Attack Framework against Neural Networks Wenshuo Li Jincheng Yu Xuefei Ning Pengjun Wang Qi Wei Yu Wang Huazhong Yang AAML 39 61 0 14 May 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 31 286 0 19 Mar 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 40 1,390 0 08 Dec 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 308 5,847 0 08 Jul 2016
Learning Deep Face Representation Haoqiang Fan Zhimin Cao Yuning Jiang Qi Yin Chinchilla Doudou SSL CVBM 52 110 0 12 Mar 2014