Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/4528
Title: | Cybersecurity, Artificial Intelligence, and Risk Management: Understanding Their Implementation in Military Systems Acquisitions |
Authors: | Johnathan Mun, Thomas Housel |
Keywords: | Software Acquisition Modeling Decision-making 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 |
URI: | https://dair.nps.edu/handle/123456789/4528 |
Appears in Collections: | Sponsored Acquisition Research & Technical Reports |
Files in This Item:
File | Description | Size | Format | |
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NPS-AM-22-014.pdf | Technical Report | 2.79 MB | Adobe PDF | View/Open |
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