MalProtect: Stateful Defense Against Adversarial Query Attacks in ML-Based Malware Detection
Author:
Affiliation:
1. Department of Informatics, King’s College London, Strand Campus, London, U.K
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Networks and Communications,Safety, Risk, Reliability and Quality
Link
http://xplorestaging.ieee.org/ielx7/10206/9970396/10177782.pdf?arnumber=10177782
Reference90 articles.
1. Intriguing Properties of Adversarial ML Attacks in the Problem Space
2. A Comprehensive Review on Malware Detection Approaches
3. Black-box adversarial attacks with limited queries and information;ilyas;Proc Int Conf Mach Learn,2018
4. Dos and don’ts of machine learning in computer security;arp;Proc Usenix Secur Symp,2022
5. The malicious use of artificial intelligence: Forecasting, prevention, and mitigation;brundage;arXiv 1802 07228,2018
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1. Improving the transferability of adversarial attacks via self-ensemble;Applied Intelligence;2024-08-22
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