| Title | Decision-Making Biases and Cyber Attackers |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Johnson, Chelsea K., Gutzwiller, Robert S., Gervais, Joseph, Ferguson-Walter, Kimberly J. |
| Conference Name | 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW) |
| Date Published | nov |
| Keywords | aversion to ambiguity, Computer crime, Conferences, Costs, cyber warfare, cybersecurity, decision making, default effect, delays, functional fixedness, Human Behavior, loss aversion, Peltzman effect, pubcrawl, Software measurement, sunk cost |
| Abstract | 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. |
| DOI | 10.1109/ASEW52652.2021.00038 |
| Citation Key | johnson_decision-making_2021 |
Decision-Making Biases and Cyber Attackers