An Overview of Artificial Intelligence Used in Malware

Abstract Artificial intelligence (AI) and machine learning (ML) methods are increasingly adopted in cyberattacks. AI supports the establishment of covert channels, as well obfuscation malware. Additionally, results new forms phishing attacks enables hard-to-detect cyber-physical sabotage. Malware creators deploy ML to improve their attack’s capabilities. Defenders must therefore expect unconventional malware with new, sophisticated changing features functions. AI’s potential for automation complex tasks serves a challenge face defensive deployment anti-malware techniques. This article summarizes state art AI-enhanced evasion attack techniques it uses against AI-supported systems. Our findings include articles describing targeted detection functions, advanced payload techniques, networked communication methods, unsupervised-learning-based sabotage, decentralized botnet control using swarm concealment payloads within neural networks that fulfill other purposes.