  With the turmoil in cybersecurity and the mind-blowing advances in AI, it is
only natural that cybersecurity practitioners consider further employing
learning techniques to help secure their organizations and improve the
efficiency of their security operation centers. But with great fears come great
opportunities for both the good and the evil, and a myriad of bad deals. This
paper discusses ten issues in cybersecurity that hopefully will make it easier
for practitioners to ask detailed questions about what they want from an AI
system in their cybersecurity operations. We draw on the state of the art to
provide factual arguments for a discussion on well-established AI in
cybersecurity issues, including the current scope of AI and its application to
cybersecurity, the impact of privacy concerns on the cybersecurity data that
can be collected and shared externally to the organization, how an AI decision
can be explained to the person running the operations center, and the
implications of the adversarial nature of cybersecurity in the learning
techniques. We then discuss the use of AI by attackers on a level playing field
including several issues in an AI battlefield, and an AI perspective on the old
cat-and-mouse game including how the adversary may assess your AI power.
