TIM-8315: v1

Samtani, S., Kantarcioglu, M., & Chen, H. (2020). Trailblazing the artificial intelligence for cybersecurity discipline : A multi-disciplinary research roadmap. ACM Transactions on Management Information Systems (TMIS) - Special Issue on Analytics for Cybersecurity and Privacy, Part 1, 11(4), 1–19.
This article provides an overview of prevailing cybersecurity data, highlights the use of artificial intelligence for cybersecurity applications, and describes the limitations present in the current cybersecurity landscape. Four main themes are focal points: cyber threat intelligence (CTI), security operations centers (SOCs), disinformation and computational propaganda, and adversarial machine learning (ML).

Bowman, B., & Huang, H. H. (2021). Towards next-generation cybersecurity with graph AI. ACM SIGOPS Operating Systems Review - SIGOPS, 55(1), 61–67.
This journal article discusses the implications of massive amounts of data on cybersecurity threat intelligence gathering and management. Graph-based machine learning (Graph AI) and its potential to make a significant impact in the next generation of cybersecurity systems are discussed.

González-Granadillo, G., González-Zarzosa, S., & Diaz, R. (2021). Security information and event management (SIEM): Analysis, trends, and usage in critical infrastructures. Sensors (Basel, Switzerland), 21(14).
This journal article discusses the deployment of SIEM systems as a means of preventing, detecting, and reacting against cyberattacks. The evolution of SIEM solutions is discussed and the next generation of SIEMs and analysis of benefits and usage in critical infrastructures are explored.

Johansen, G.(2020). Digital forensics and incident response. Packt Publishing.
Optional Resource: This book is a comprehensive guide for incident response, digital forensics, and threat hunting in the organization.