Manipulating Machine Learning: Poisoning Attacks and Countermeasures for
Regression Learning

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Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

1 April 2018

Matthew Jagielski

Battista Biggio

Cristina Nita-Rotaru

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Papers citing "Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning"

18 / 318 papers shown

Title
Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning Muhammad Shayan Clement Fung Chris J. M. Yoon Ivan Beschastnikh FedML 102 82 0 24 Nov 2018
Oversight of Unsafe Systems via Dynamic Safety Envelopes David Manheim 18 1 0 22 Nov 2018
An Optimal Control View of Adversarial Machine Learning Xiaojin Zhu AAML 55 25 0 11 Nov 2018
FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Junaid Qadir Mohamed Bennai AAML 85 34 0 04 Nov 2018
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks Faiq Khalid Muhammad Abdullah Hanif Semeen Rehman Rehan Ahmed Mohamed Bennai AAML 88 21 0 02 Nov 2018
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks Davide Maiorca Battista Biggio Giorgio Giacinto AAML 80 47 0 02 Nov 2018
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 126 244 0 02 Nov 2018
Law and Adversarial Machine Learning Ramnath Kumar David R. O'Brien Kendra Albert Salome Vilojen AILaw AAML 49 12 0 25 Oct 2018
Security Matters: A Survey on Adversarial Machine Learning Guofu Li Pengjia Zhu Jin Li Zhemin Yang Ning Cao Zhiyi Chen AAML 90 25 0 16 Oct 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 86 11 0 08 Sep 2018
Data Poisoning Attacks in Contextual Bandits Yuzhe Ma Kwang-Sung Jun Lihong Li Xiaojin Zhu AAML 85 68 0 17 Aug 2018
Mitigation of Adversarial Attacks through Embedded Feature Selection Ziyi Bao Luis Muñoz-González Emil C. Lupu AAML 44 1 0 16 Aug 2018
Security and Privacy Issues in Deep Learning Ho Bae Jaehee Jang Dahuin Jung Hyemi Jang Heonseok Ha Hyungyu Lee Sungroh Yoon SILM MIACV 158 79 0 31 Jul 2018
On the adversarial robustness of robust estimators Lifeng Lai Erhan Bayraktar 71 10 0 11 Jun 2018
PAC-learning in the presence of evasion adversaries Daniel Cullina A. Bhagoji Prateek Mittal AAML 104 55 0 05 Jun 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models A. Salem Yang Zhang Mathias Humbert Pascal Berrang Mario Fritz Michael Backes MIACV MIALM 186 957 0 04 Jun 2018
Label Sanitization against Label Flipping Poisoning Attacks Andrea Paudice Luis Muñoz-González Emil C. Lupu AAML 69 164 0 02 Mar 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 183 1,412 0 08 Dec 2017