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12 June 2023 Securing the attack surface of AI-enabled systems (Conference Presentation)
Joshua D. Harguess, Chris M. Ward
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Proceedings Volume 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V; 1253805 (2023) https://doi.org/10.1117/12.2672808
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States
Abstract
With the acceleration of Artificial Intelligence (AI) innovation in recent years, organizations across the public sector have been racing to adopt AI into their products and processes. With respect to National Security, AI adoption offers the potential to automate the operation of valuable assets and provide critical warfighter support across the observe–orient–decide–act (OODA) cycle. As we progress towards integration of AI-enabled mission critical systems, the robustness of these systems must be verified, especially against adversarial exploitation. We present a process for red-teaming AI systems used in real-world decision-making. We consider attacks on target AI systems in the context of the larger concept of operations (CONOPS) and use threat modeling to narrow down likely attack vectors.
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Joshua D. Harguess and Chris M. Ward "Securing the attack surface of AI-enabled systems (Conference Presentation)", Proc. SPIE 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, 1253805 (12 June 2023); https://doi.org/10.1117/12.2672808
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KEYWORDS
Artificial intelligence
Machine learning
Decision making
Modeling
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