Abstract: 

Cybersecurity has undoubtedly become one of the grand societal challenges in the 21st century. Today, many organizations are struggling to sift 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. I will aim provide an important step to progress the AI for Cybersecurity discipline in this talk by summarizing the state of the field and promising future directions. To set the foundation for this talk, I will first review the principles of cybersecurity, and the need for AI-enabled analytics. Then, I will include a detailed overview of prevailing cybersecurity data sources that many modern organizations often have at their disposal to execute their cybersecurity tasks. Based on this review of the data, I will 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. I will introduce a new open source tool, the AI4Cyber virtual machine (VM), that seeks to integrate traditionally disparate cybersecurity tools and packages for AI-enabled analytics under one hood to facilitate AI-enabled cybersecurity analytics. I will also provide examples of recent research at the intersection of AI and cybersecurity, particularly around detecting vulnerable code on GitHub repositories and detecting emerging threats from the Dark Web for proactive cyber threat intelligence (CTI) capabilities.

Bio: 

Dr. Sagar Samtani is an Assistant Professor and Grant Thornton Scholar in the Department of Operations and Decision Technologies at Indiana University. Dr. Samtani graduated with his Ph.D. from the AI Lab from University of Arizona. Dr. Samtani’s research interests are in AI for Cybersecurity, developing deep learning approaches for cyber threat intelligence, vulnerability assessment, open-source software, AI risk management, and Dark Web analytics. He has received funding from NSF’s SaTC, CICI, and SFS programs and has published over 40 peer-reviewed articles in leading information systems, machine learning, and cybersecurity venues. He is deeply involved with industry, serving on the Board of Directors for the DEFCON AI Village and Executive Advisory Council for the CompTIA ISAO.