Explaining Vulnerabilities of Deep Learning to Adversarial Malware
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Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries

11 January 2019

Christian Scano

Battista Biggio

Giovanni Lagorio

Fabio Roli

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Papers citing "Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries"

17 / 17 papers shown

Title
Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples M. Kozák Christian Scano Dmitrijs Trizna Fabio Roli AAML 111 0 0 04 May 2024
EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models Hyrum S. Anderson P. Roth 56 479 0 12 Apr 2018
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables Bojan Kolosnjaji Ambra Demontis Battista Biggio Davide Maiorca Giorgio Giacinto Claudia Eckert Fabio Roli AAML 70 318 0 12 Mar 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 135 1,409 0 08 Dec 2017
DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification Omid David N. Netanyahu 42 206 0 21 Nov 2017
Malware Detection by Eating a Whole EXE Edward Raff Jon Barker Jared Sylvester Robert Brandon Bryan Catanzaro Charles K. Nicholas 84 546 0 25 Oct 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 163 2,160 0 21 Aug 2017
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection Ambra Demontis Marco Melis Battista Biggio Davide Maiorca Dan Arp Konrad Rieck Igino Corona Giorgio Giacinto Fabio Roli AAML 66 284 0 28 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 227 2,910 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 211 6,027 0 04 Mar 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,587 0 16 Aug 2016
Adversarial Perturbations Against Deep Neural Networks for Malware Classification Kathrin Grosse Nicolas Papernot Praveen Manoharan Michael Backes Patrick McDaniel AAML 90 418 0 14 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 120 3,968 0 24 Nov 2015
Deep Neural Network Based Malware Detection Using Two Dimensional Binary Program Features Joshua Saxe Konstantin Berlin 66 623 0 13 Aug 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,145 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 293 14,978 1 21 Dec 2013

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