Biblio

Effective reasoning about the impact of security policy decisions requires understanding how human users actually behave, rather than assuming desirable but incorrect behavior. Simulation could help with this reasoning, but it requires building computational models of the relevant human behavior and validating that these models match what humans actually do. In this paper we describe our progress on building agent-based models of human behavior with passwords, and we demonstrate how these models reproduce phenomena
shown in the empirical literature.
 

In this paper we explore the differential perceptions of cybersecurity professionals and general users regarding access rules and passwords. We conducted a preliminary survey involving 28 participants: 15 cybersecurity professionals and 13 general users. We present our preliminary findings and explain how such survey data might be used to improve security in
practice. We focus on user fatigue with access rules and passwords.
 

In this paper we explore the differential perceptions of cybersecurity professionals and general users regarding access rules and passwords. We conducted a preliminary survey involving 28 participants: 15 cybersecurity professionasl and 13 general users. We present our preliminary findings and explain how such survey data might be used to improve security in practice. We focus on user fatigue with access rules and passwords.

Healthcare technology—sometimes called “healthtech” or “healthsec”—is enmeshed with security and privacy via usability, performance, and cost-effectiveness issues. It is multidisciplinary, distributed, and complex—and it also involves many competing stakeholders and interests. To address the problems that arise in such a multifaceted field—comprised of physicians, IT professionals, management information specialists, computer scientists, edical informaticists, and epidemiologists, to name a few—the Healthtech Declaration was initiated at the most recent USENIX Summit on Information Technologies for Health (Healthtech 2015) held in Washington, DC. This Healthtech Declaration includes an easy-touse—and easy-to-cite—checklist of key issues that anyone proposing a solution must consider (see “The Healthtech Declaration Checklist” sidebar). In this article, we provide the context and motivation for the declaration.

Agent-based modeling can serve as a valuable asset to security personnel who wish to better understand the security landscape within their organization, especially as it relates to user behavior and circumvention. In this paper, we ar- gue in favor of cognitive behavioral agent-based modeling for usable security, report on our work on developing an agent- based model for a password management scenario, perform a sensitivity analysis, which provides us with valuable insights into improving security (e.g., an organization that wishes to suppress one form of circumvention may want to endorse another), and provide directions for future work.

In real world domains, from healthcare to power to finance, we deploy computer systems intended to streamline and im- prove the activities of human agents in the corresponding non-cyber worlds. However, talking to actual users (instead of just computer security experts) reveals endemic circum- vention of the computer-embedded rules. Good-intentioned users, trying to get their jobs done, systematically work around security and other controls embedded in their IT systems.

This poster reports on our work compiling a large corpus of such incidents and developing a model based on semi- otic triads to examine security circumvention. This model suggests that mismorphisms—mappings that fail to preserve structure—lie at the heart of circumvention scenarios; dif- ferential perceptions and needs explain users’ actions. We support this claim with empirical data from the corpus.

In real world domains, from healthcare to power to finance, we deploy computer systems intended to streamline and improve the activities of human agents in the corresponding non-cyber worlds. However, talking to actual users (instead of just computer security experts) reveals endemic circumvention of the computer-embedded rules. Good-intentioned users, trying to get their jobs done, systematically work around security and other controls embedded in their IT systems.

This paper reports on our work compiling a large corpus of such incidents and developing a model based on semiotic triads to examine security circumvention. This model suggests that mismorphisms— mappings that fail to preserve structure—lie at the heart of circumvention scenarios; differential percep- tions and needs explain users’ actions. We support this claim with empirical data from the corpus.

Workarounds to computer access in healthcare are sufficiently common that they often go unnoticed. Clinicians focus on patient care, not cybersecurity. We argue and demonstrate that understanding workarounds to healthcare workers’ computer access requires not only analyses of computer rules, but also interviews and observations with clinicians. In addition, we illustrate the value of shadowing clinicians and conducing focus groups to understand their motivations and tradeoffs for circumvention. Ethnographic investigation of the medical workplace emerges as a critical method of research because in the inevitable conflict between even well-intended people versus the machines, it’s the people who are the more creative, flexible, and motivated. We conducted interviews and observations with hundreds of medical workers and with 19 cybersecurity experts, CIOs, CMIOs, CTO, and IT workers to obtain their perceptions of computer security. We also shadowed clinicians as they worked. We present dozens of ways workers ingeniously circumvent security rules. The clinicians we studied were not “black hat” hackers, but just professionals seeking to accomplish their work despite the security technologies and regulations.
 

Workarounds to computer access in healthcare are sufficiently common that they often go unnoticed. Clinicians focus on patient care, not cybersecurity. We argue and demonstrate that understanding workarounds to healthcare workers’ computer access requires not only analyses of computer rules, but also interviews and observations with clinicians. In addition, we illustrate the value of shadowing clinicians and conducing focus groups to understand their motivations and tradeoffs for circumvention. Ethnographic investigation of the medical workplace emerges as a critical method of research because in the inevitable conflict between even well-intended people versus the machines, it’s the people who are the more creative, flexible, and motivated. We conducted interviews and observations with hundreds of medical workers and with 19 cybersecurity experts, CIOs, CMIOs, CTO, and IT workers to obtain their perceptions of computer security. We also shadowed clinicians as they worked. We present dozens of ways workers ingeniously circumvent security rules. The clinicians we studied were not “black hat” hackers, but just professionals seeking to accomplish their work despite the security technologies and regulations.