Trailblazing the Artificial Intelligence for Cybersecurity Discipline: A Multi-Disciplinary Research Roadmap

Trailblazing the Artificial Intelligence for Cybersecurity Discipline: A Multi-Disciplinary Research Roadmap

연구 분야: Safety

학회: ACM Transactions on Management Information Systems (TMIS), Volume 11, Issue 4

Cybersecurity has rapidly emerged as a grand societal challenge of the 21st century. Innovative solutions to proactively tackle emerging cybersecurity challenges are essential to ensuring a safe and secure society. Artificial Intelligence (AI) has rapidly emerged as a viable approach for sifting through terabytes of heterogeneous cybersecurity data to execute fundamental cybersecurity tasks, such as asset prioritization, control allocation, vulnerability management, and threat detection, with unprecedented efficiency and effectiveness. Despite its initial promise, AI and cybersecurity have been traditionally siloed disciplines that relied on disparate knowledge and methodologies. Consequently, the AI for Cybersecurity discipline is in its nascency. In this article, we aim to provide an important step to progress the AI for Cybersecurity discipline. We first provide an overview of prevailing cybersecurity data, summarize extant AI for Cybersecurity application areas, and identify key limitations in the prevailing landscape. Based on these key issues, we offer a multi-disciplinary AI for Cybersecurity roadmap that centers on major themes such as cybersecurity applications and data, advanced AI methodologies for cybersecurity, and AI-enabled decision making. To help scholars and practitioners make significant headway in tackling these grand AI for Cybersecurity issues, we summarize promising funding mechanisms from the National Science Foundation (NSF) that can support long-term, systematic research programs. We conclude this article with an introduction of the articles included in this special issue.