Malware Evasion Attack and Defense

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Malware Evasion Attack and Defense

7 April 2019

Celeste Fralick

G. Infante-Lopez

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Papers citing "Malware Evasion Attack and Defense"

19 / 19 papers shown

Title
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries Christian Scano Battista Biggio Giovanni Lagorio Fabio Roli A. Armando AAML 59 131 0 11 Jan 2019
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
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples Felix Kreuk A. Barak Shir Aviv-Reuven Moran Baruch Benny Pinkas Joseph Keshet AAML 59 118 0 13 Feb 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 135 1,409 0 08 Dec 2017
Malware Detection by Eating a Whole EXE Edward Raff Jon Barker Jared Sylvester Robert Brandon Bryan Catanzaro Charles K. Nicholas 81 546 0 25 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 319 12,138 0 19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 131 1,867 0 20 May 2017
The Space of Transferable Adversarial Examples Florian Tramèr Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML SILM 102 558 0 11 Apr 2017
Enhancing Robustness of Machine Learning Systems via Data Transformations A. Bhagoji Daniel Cullina Chawin Sitawarin Prateek Mittal AAML 74 231 0 09 Apr 2017
Delving into Transferable Adversarial Examples and Black-box Attacks Yanpei Liu Xinyun Chen Chang-rui Liu Basel Alomair AAML 143 1,741 0 08 Nov 2016
Technical Report on the CleverHans v2.1.0 Adversarial Examples Library Nicolas Papernot Fartash Faghri Nicholas Carlini Ian Goodfellow Reuben Feinman ... David Berthelot P. Hendricks Jonas Rauber Rujun Long Patrick McDaniel AAML 86 514 0 03 Oct 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,587 0 16 Aug 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 76 3,685 0 08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 117 3,968 0 24 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 118 3,077 0 14 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 19,129 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013