Adversarial Cognitive Engineering (ACE) and Defensive Cybersecurity: Leveraging Attacker Decision-Making Heuristics in a Cybersecurity Task

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dc.contributor.author Johnson, Chelsea
dc.contributor.author Van Tassel, Richard W.
dc.contributor.author Shade, Temmie
dc.contributor.author Rogers, Andrew
dc.contributor.author Ferguson-Walter, Kimberly
dc.date.accessioned 2023-12-26T18:36:36Z
dc.date.available 2023-12-26T18:36:36Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other e62b59f1-acc9-4bc6-bc28-d650c8fc0a65
dc.identifier.uri https://hdl.handle.net/10125/106495
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Cyber Deception and Cyberpsychology for Defense
dc.subject cognitive engineering
dc.subject cybersecurity
dc.subject decision-making heuristics
dc.subject sunk cost fallacy
dc.title Adversarial Cognitive Engineering (ACE) and Defensive Cybersecurity: Leveraging Attacker Decision-Making Heuristics in a Cybersecurity Task
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract The role of cyberspace continues to expand, touching nearly every aspect in our lives. Critical information, when stolen, can be devastating to a nation’s people, economy, and security. To defend against this threat, it is essential to understand the human behind the attack. A first step in developing new defenses where human attackers are involved is obtaining valid and reliable human performance and decision-making data. These data can be procured through rigorous human science research that experimentally evaluates foundational theory and measures human performance. Taking the key concepts from behavioral economics, the game-based testbed, CYPHER, was specifically designed to test the occurrence of the Sunk Cost Fallacy across multiple decisions in an abstract cyber environment. Evaluating decisions made over a series of actions to catch a fictitious cyber thief, we analyze the effects of two antecedents (uncertainty and project completion) and resource expenditure. Our results show that irrespective of condition, significantly more participants unnecessarily wasted resources, demonstrating behavior consistent with the Sunk Cost Fallacy. These data provide a baseline upon which to build artificial intelligence algorithms for automated cyber defense.
dcterms.extent 10 pages
prism.startingpage 974
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