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With the wide range of adversarial learning applications in the cybersecurity domain, from malware detection to speaker recognition to cyber-physical systems to many others such as deep fakes, ...
Congressional hearings on artificial intelligence and machine learning in cyberspace quietly took place in the U.S. Senate Armed Forces Committee’s Subcommittee on Cyber in early May 2022.
The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems.
Let's explore the potential adversarial attacks on AI systems, the security challenges they pose and solutions on how to navigate this landscape and keep models secure.
M.A. Thomas, Machine Learning Applications for Cybersecurity, The Cyber Defense Review, Vol. 8, No. 1 (SPRING 2023), pp. 87-102 ...