Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus

12 June 2018

Papers citing "Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus"

9 / 9 papers shown

Title
High-resolution Image-based Malware Classification using Multiple Instance Learning Tim Peters H. Farhat 42 0 0 21 Nov 2023
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive Conditions M. Rigaki Sebastian Garcia AAML 74 11 0 13 Apr 2022
The Cross-evaluation of Machine Learning-based Network Intrusion Detection Systems Giovanni Apruzzese Luca Pajola Mauro Conti 81 56 0 09 Mar 2022
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art Xiang Ling Lingfei Wu Jiangyu Zhang Zhenqing Qu Wei Deng ... Chunming Wu S. Ji Tianyue Luo Jingzheng Wu Yanjun Wu AAML 145 83 0 23 Dec 2021
A Comparison of State-of-the-Art Techniques for Generating Adversarial Malware Binaries P. Dasgupta Zachary Osman AAML 64 2 0 22 Nov 2021
A Survey on Adversarial Attacks for Malware Analysis Kshitiz Aryal Maanak Gupta Mahmoud Abdelsalam AAML 106 53 0 16 Nov 2021
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection Edward Raff William Fleshman Richard Zak Hyrum S. Anderson Bobby Filar Mark McLean AAML 59 58 0 17 Dec 2020
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification Edward Raff Charles K. Nicholas AAML 72 57 0 15 Jun 2020
MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers Wei Song Xuezixiang Li Sadia Afroz D. Garg Dmitry Kuznetsov Heng Yin AAML 117 27 0 06 Mar 2020