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2021-05-13
Peck, Sarah Marie, Khan, Mohammad Maifi Hasan, Fahim, Md Abdullah Al, Coman, Emil N, Jensen, Theodore, Albayram, Yusuf.  2020.  Who Would Bob Blame? Factors in Blame Attribution in Cyberattacks Among the Non-Adopting Population in the Context of 2FA 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). :778–789.
This study focuses on identifying the factors contributing to a sense of personal responsibility that could improve understanding of insecure cybersecurity behavior and guide research toward more effective messaging targeting non-adopting populations. Towards that, we ran a 2(account type) x2(usage scenario) x2(message type) between-group study with 237 United States adult participants on Amazon MTurk, and investigated how the non-adopting population allocates blame, and under what circumstances they blame the end user among the parties who hold responsibility: the software companies holding data, the attackers exposing data, and others. We find users primarily hold service providers accountable for breaches but they feel the same companies should not enforce stronger security policies on users. Results indicate that people do hold end users accountable for their behavior in the event of a breach, especially when the users' behavior affects others. Implications of our findings in risk communication is discussed in the paper.
2016-05-04
Proctor, Robert W., Chen, Jing.  2015.  The Role of Human Factors/Ergonomics in the Science of Security: Decision Making and Action Selection in Cyberspace. Human Factors: The Journal of the Human Factors and Ergonomics Society.

Objective: The overarching goal is to convey the concept of science of security and the contributions that a scientifically based, human factors approach can make to this interdisciplinary field.Background: Rather than a piecemeal approach to solving cybersecurity problems as they arise, the U.S. government is mounting a systematic effort to develop an approach grounded in science. Because humans play a central role in security measures, research on security-related decisions and actions grounded in principles of human information-processing and decision-making is crucial to this interdisciplinary effort.Method: We describe the science of security and the role that human factors can play in it, and use two examples of research in cybersecurity—detection of phishing attacks and selection of mobile applications—to illustrate the contribution of a scientific, human factors approach.Results: In these research areas, we show that systematic information-processing analyses of the decisions that users make and the actions they take provide a basis for integrating the human component of security science.Conclusion: Human factors specialists should utilize their foundation in the science of applied information processing and decision making to contribute to the science of cybersecurity.

2015-06-30
J. Chen, C. S. Gates, Z. Jorgensen, W. Yang.  2015.  Effective risk communication for end users: A multi-granularity approach. Women in CyberSecurity (WiCyS) Conference.

We proposed a multi-granularity approach to present risk information of mobile apps to the end users. Within this approach the highest level is a summary risk index, which allows quick and easy comparison among multiple apps that provide similar functionality. We have developed several types of risk index, such as text saying “High Risk” or number of filled circles (Gates, Chen, Li, & Proctor, 2014). Through both online and in-lab studies, we found that when presented the interface with the summary risk index, participants made more secure app-selection decisions. Subsequent research showed that framing of the summary risk information affects users’ app-selection decisions, and positive framing in terms of safety has an advantage over negative framing in terms of risk (Chen, Gates, Li, & Proctor, 2014).

In addition to the summary risk index, some users may also want more detailed risk information for the apps. We have been developing an intermediate-level risk display that presents only the major risk categories. As a first step, we conducted user studies to have expert users’ identify the major risk categories (personal privacy, monetary loss, and device stability) and validate the categories on typical users (Jorgensen, Chen, Gates, Li, Proctor, & Yu, 2015). In a subsequent study, we are developing a graphical display to incorporate these risk categories into the current app interface and test its effectiveness.

This multi-granularity approach can be applied to risk communication in other contexts. For example, in the context of communicating the potential risk associated with phishing attacks, an effective warning should be designed to include both higher-level and lower-level risk information: A higher-level index information about how likely an email message or website is a phishing one should be presented to users and inform them about the potential risk in an easy-to-comprehend manner; a more detailed explanation should also be available for users who want to know more about the warning and the index. We have completed a pilot study in this area and are initiating a full study to investigate the effectiveness of such an interface in preventing users from being phished successfully.