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Title: Cybersecurity, Artificial Intelligence, and Risk Management: Understanding Their Implementation in Military Systems Acquisitions
Authors: Johnathan Mun, Thomas Housel
Keywords: Software Acquisition
Portfolio Management
Machine Learning
Issue Date: 18-Jan-2022
Publisher: Acquisition Research Program
Citation: Published--Unlimited Distribution
Series/Report no.: Acquisition Management;NPS-AM-22-014
Abstract: The exponential growth in data management has led to explosive growth in data analytics, big data, machine learning (ML), and AI. Despite the positive effects these emerging solutions have on productivity, there is a desperate need for information on extreme risk factors (e.g., climate change, pandemic risks, data loss, failure of IT systems) impacting on cybersecurity. We propose a systematic review on how AI, especially ML, is being considered in military acquisitions, including discussions around risk management and extreme events in order to identify how the DoD could use these findings to increase awareness of the hidden aspects of ML and AI, especially in the face of extreme events.
Description: Acquisition Management / Faculty Report
Appears in Collections:Sponsored Acquisition Research & Technical Reports

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