Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization

29 August 2017

Luis Muñoz-González

Battista Biggio

Ambra Demontis

Fabio Roli

Papers citing "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"

20 / 119 papers shown

Title
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Soheil Kolouri Aniruddha Saha Hamed Pirsiavash Heiko Hoffmann AAML 25 231 0 26 Jun 2019
Poisoning Attacks with Generative Adversarial Nets Luis Muñoz-González Bjarne Pfitzner Matteo Russo Javier Carnerero-Cano Emil C. Lupu AAML 19 63 0 18 Jun 2019
Mixed Strategy Game Model Against Data Poisoning Attacks Yi-Tsen Ou Reza Samavi AAML 19 4 0 07 Jun 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
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
Data Poisoning against Differentially-Private Learners: Attacks and Defenses Yuzhe Ma Xiaojin Zhu Justin Hsu SILM 19 157 0 23 Mar 2019
Adversarial Attacks on Graph Neural Networks via Meta Learning Daniel Zügner Stephan Günnemann OOD AAML GNN 28 568 0 22 Feb 2019
A new Backdoor Attack in CNNs by training set corruption without label poisoning Mauro Barni Kassem Kallas B. Tondi AAML 24 348 0 12 Feb 2019
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 22 169 0 03 Dec 2018
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 134 186 0 02 Dec 2018
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering Bryant Chen Wilka Carvalho Wenjie Li Heiko Ludwig Benjamin Edwards Chengyao Chen Ziqiang Cao Biplav Srivastava AAML 12 781 0 09 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks Kenneth T. Co Luis Muñoz-González Sixte de Maupeou Emil C. Lupu AAML 22 67 0 30 Sep 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
Are You Tampering With My Data? Michele Alberti Vinaychandran Pondenkandath Marcel Würsch Manuel Bouillon Mathias Seuret Rolf Ingold Marcus Liwicki AAML 37 19 0 21 Aug 2018
Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks Kang Liu Brendan Dolan-Gavitt S. Garg AAML 24 1,018 0 30 May 2018
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 69 1,410 0 24 Mar 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 31 283 0 19 Mar 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Bo-wen Li Kimberly Lu D. Song AAML SILM 41 1,805 0 15 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 40 1,388 0 08 Dec 2017