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Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

19 July 2017

Papers citing "Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers"

23 / 23 papers shown

Title
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 105 73 0 07 Aug 2020
DeepAPT: Nation-State APT Attribution Using End-to-End Deep Neural Networks Ishai Rosenberg Guillaume Sicard E. David 53 43 0 27 Nov 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
Black-Box Attacks against RNN based Malware Detection Algorithms Weiwei Hu Ying Tan 51 151 0 23 May 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 105 894 0 01 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 86 714 0 21 Feb 2017
On Detecting Adversarial Perturbations J. H. Metzen Tim Genewein Volker Fischer Bastian Bischoff AAML 73 950 0 14 Feb 2017
Towards Principled Methods for Training Generative Adversarial Networks Martín Arjovsky M. Nault GAN 83 2,112 0 17 Jan 2017
Towards the Science of Security and Privacy in Machine Learning Nicolas Papernot Patrick McDaniel Arunesh Sinha Michael P. Wellman AAML 96 474 0 11 Nov 2016
SoK: Applying Machine Learning in Security - A Survey Heju Jiang J. Nagra P. Ahammad 36 30 0 10 Nov 2016
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
A multi-task learning model for malware classification with useful file access pattern from API call sequence Xin Eric Wang Siu-Ming Yiu 111 30 0 19 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 109 1,811 0 09 Sep 2016
Adversarial Perturbations Against Deep Neural Networks for Malware Classification Kathrin Grosse Nicolas Papernot Praveen Manoharan Michael Backes Patrick McDaniel AAML 79 418 0 14 Jun 2016
Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples Nicolas Papernot Patrick McDaniel Ian Goodfellow SILM AAML 116 1,742 0 24 May 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks Nicolas Papernot Patrick McDaniel A. Swami Richard E. Harang AAML GAN SILM 61 456 0 28 Apr 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
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 607 12,745 0 11 Dec 2014
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches Kyunghyun Cho B. V. Merrienboer Dzmitry Bahdanau Yoshua Bengio AI4CE AIMat 259 6,791 0 03 Sep 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