Artificial intelligence presents new challenges in cybersecurity
Misty K. Blowers, Jonathan Williams · 2020
Artificial Intelligence and Machine Learning (AI/ML) based solutions contain inherent vulnerabilities that are of growing concern as investment is made into applying these technologies to gain a strategic advantage in speed of response, analysis, and maneuver for both private industry and government applications. Current cybersecurity practices and tools must evolve to handle new vulnerabilities inherent to AI/ML enabled systems across all domains. This paper will explore how the tools and techniques to defend against attacks and exploits, both on AI/ML, and with AI/ML, fall short from the tools typically used by today’s cybersecurity professional. It will explore both the intrinsic vulnerabilities due to model failure points and data poisoning strategies as well as address concerns that arise when our adversaries use AI/ML tools to their advantage. Some of these challenges present themselves as very advanced strategies brought on by nation state actors who have both time and resources. Other threats to our AI/ML systems are much less sophisticated but still seem to slip through the cracks because AI/ML is only beginning to gain significant momentum in real world applications.