TY - GEN
T1 - Decision-Making Biases and Cyber Attackers
AU - Johnson, Chelsea K.
AU - Gutzwiller, Robert S.
AU - Gervais, Joseph
AU - Ferguson-Walter, Kimberly J.
N1 - Funding Information:
*This work was funded by the Laboratory of Advanced Cybersecurity Research.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Cyber security is reliant on the actions of both machine and human and remains a domain of importance and continual evolution. While the study of human behavior has grown, less attention has been paid to the adversarial operator. Cyber environments consist of complex and dynamic situations where decisions are made with incomplete information. In such scenarios people form strategies based on simplified models of the world and are often efficient and effective, yet may result in judgement or decision-making bias. In this paper, we examine an initial list of biases affecting adversarial cyber actors. We use subject matter experts to derive examples and demonstrate these biases likely exist, and play a role in how attackers operate.
AB - Cyber security is reliant on the actions of both machine and human and remains a domain of importance and continual evolution. While the study of human behavior has grown, less attention has been paid to the adversarial operator. Cyber environments consist of complex and dynamic situations where decisions are made with incomplete information. In such scenarios people form strategies based on simplified models of the world and are often efficient and effective, yet may result in judgement or decision-making bias. In this paper, we examine an initial list of biases affecting adversarial cyber actors. We use subject matter experts to derive examples and demonstrate these biases likely exist, and play a role in how attackers operate.
KW - Peltzman effect
KW - aversion to ambiguity
KW - default effect
KW - functional fixedness
KW - loss aversion
KW - sunk cost
UR - http://www.scopus.com/inward/record.url?scp=85125636261&partnerID=8YFLogxK
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U2 - 10.1109/ASEW52652.2021.00038
DO - 10.1109/ASEW52652.2021.00038
M3 - Conference contribution
AN - SCOPUS:85125636261
T3 - Proceedings - 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2021
SP - 140
EP - 144
BT - Proceedings - 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASEW 2021
Y2 - 15 November 2021 through 19 November 2021
ER -