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With the turmoil in cybersecurity and the mind-blowing advances in AI, it isonly natural that cybersecurity practitioners consider further employinglearning techniques to help secure their organizations and improve theefficiency of their security operation centers. But with great fears come greatopportunities for both the good and the evil, and a myriad of bad deals. Thispaper discusses ten issues in cybersecurity that hopefully will make it easierfor practitioners to ask detailed questions about what they want from an AIsystem in their cybersecurity operations. We draw on the state of the art toprovide factual arguments for a discussion on well-established AI incybersecurity issues, including the current scope of AI and its application tocybersecurity, the impact of privacy concerns on the cybersecurity data thatcan be collected and shared externally to the organization, how an AI decisioncan be explained to the person running the operations center, and theimplications of the adversarial nature of cybersecurity in the learningtechniques. We then discuss the use of AI by attackers on a level playing fieldincluding several issues in an AI battlefield, and an AI perspective on the oldcat-and-mouse game including how the adversary may assess your AI power.

Ten AI Stepping Stones for Cybersecurity