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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"

20 / 20 papers shown

Title
Interactive Machine Learning: A State of the Art Review Natnael A. Wondimu Cédric Buche U. Visser VLM HAI 99 10 0 13 Jul 2022
Universal Adversarial Examples and Perturbations for Quantum Classifiers Weiyuan Gong D. Deng AAML 83 25 0 15 Feb 2021
Information Laundering for Model Privacy Xinran Wang Yu Xiang Jun Gao Jie Ding 34 24 0 13 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 113 73 0 07 Aug 2020
A Framework for Enhancing Deep Neural Networks Against Adversarial Malware Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 65 13 0 15 Apr 2020
Effectiveness of Adversarial Examples and Defenses for Malware Classification Robert Podschwadt Hassan Takabi AAML 46 11 0 10 Sep 2019
FortuneTeller: Predicting Microarchitectural Attacks via Unsupervised Deep Learning Berk Gülmezoglu A. Moghimi T. Eisenbarth B. Sunar AAML 66 38 0 08 Jul 2019
Adversarial Attacks on Deep Learning Models in Natural Language Processing: A Survey W. Zhang Quan Z. Sheng A. Alhazmi Chenliang Li AAML 114 57 0 21 Jan 2019
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 54 15 0 19 Dec 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Adversarial Attacks and Defences: A Survey Anirban Chakraborty Manaar Alam Vishal Dey Anupam Chattopadhyay Debdeep Mukhopadhyay AAML OOD 102 683 0 28 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 63 21 0 18 Sep 2018
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks Siwakorn Srisakaokul Yuhao Zhang Zexuan Zhong Wei Yang Tao Xie Bo Li AAML 75 19 0 31 Aug 2018
Android HIV: A Study of Repackaging Malware for Evading Machine-Learning Detection Xiao Chen Chaoran Li Derui Wang S. Wen Jun Zhang Surya Nepal Yang Xiang K. Ren AAML 80 246 0 10 Aug 2018
BEBP: An Poisoning Method Against Machine Learning Based IDSs Pan Li Qiang Liu Wentao Zhao Dongxu Wang Siqi Wang AAML 46 6 0 11 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 75 118 0 13 Feb 2018
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning Hyrum S. Anderson Anant Kharkar Bobby Filar David Evans P. Roth AAML 90 210 0 26 Jan 2018
Adversarial Deep Learning for Robust Detection of Binary Encoded Malware Abdullah Al-Dujaili Alex Huang Erik Hemberg Una-May O’Reilly AAML 107 188 0 09 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 142 1,872 0 02 Jan 2018
Early Stage Malware Prediction Using Recurrent Neural Networks Matilda Rhode Pete Burnap K. Jones AAML 72 255 0 11 Aug 2017