"Using AI-enhanced malware, researchers disrupt algorithms used in antimalware"

As many organizations and government foundations are being encouraged to embrace the future of artificial intelligence (AI) in the implementation and processes of cybersecurity, concerns of emerging machine learning-based malware arises. Researchers at Peking University’s School of Electronics Engineering and Computer Science have published a research paper, “Generating Adversarial Malware Examples for Black Box Attacks Based on GAN”, which discusses the components of “MalGAN”, an algorithm used to produce adversarial malware examples and evade black-box machine learning-based detection models. This article discusses some points outlined in the research paper as well as how cybersecurity experts expect AI to benefit cybercriminals. 

TechRepublic reports "Using AI-enhanced malware, researchers disrupt algorithms used in antimalware"