Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022

TL;DR

This workshop highlights the application of AI in cybersecurity, emphasizing challenges like data volume, adversarial attacks, and the need for trustworthy, practical AI solutions in real-world cyber defense.

Contribution

It identifies key gaps and challenges in adopting AI for cybersecurity, calling for research on certification, practical constraints, vulnerabilities, explanations, and trust.

Findings

AI methods are not widely adopted in cybersecurity.

Major challenges include vulnerabilities and lack of trust.

Research gaps exist in practical AI deployment for security.

Abstract

The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. Additionally, adversaries continue to develop new attacks. Hence, AI methods are required to understand and protect the cyber domain. These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. In general, AI techniques are still not widely adopted in the real world. Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. There is a need for the research community to develop novel solutions for these practical issues.