TY - JOUR
AU - Sagar Samtani
AU - Murat Kantarcioglu
AU - Hsinchun Chen
AB -  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.
BT - Association for Computing Machinery (ACM)
DA - 2020-12-02
DO - 10.1145/3430360
N1 - Preventing cyber-attacks has become a grand societal challenge. Despite significant investments in various cybersecurity programs, breaches remain on an upward trend. AI-based techniques hold significant promise in sifting through large quantities of heterogeneous cybersecurity data to efficiently and effectively support critical cybersecurity tasks such as asset prioritization, controls allocation, threat detection, and vulnerability management. Despite these potential benefits, the AI for Cybersecurity discipline is still in its nascency. Numerous opportunities exist for scholars to make significant progress and practical impacts in turning the tide against cyber-attacks.
N2 -  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.
PY - 2020
T2 - Association for Computing Machinery (ACM)
TI - Trailblazing the Artificial Intelligence for Cybersecurity Discipline: A Multi-Disciplinary Research Roadmap
UR - https://dl.acm.org/doi/abs/10.1145/3430360
SN - 2158-656X
ER -