Accounting for User Behavior in Predictive Cyber Security Models
Title | Accounting for User Behavior in Predictive Cyber Security Models |
Publication Type | Presentation |
Year of Publication | 2015 |
Authors | Mohammad Noureddine, University of Illinois at Urbana-Champaign, Masooda Bashir, University of Illinois at Urbana-Champaign, Ken Keefe, University of Illinois at Urbana-Champaign, Andrew Marturano, University of Illinois at Urbana-Champaign, William H. Sanders, University of Illinois at Urbana-Champaign |
Keywords | Data-Driven Model-Based Decision-Making, Human and Societal Aspects of Security and Privacy, NSA SoS Lablets Materials, quantitative metrics, science of security, UIUC, usuable security |
Abstract | The human factor is often regarded as the weakest link in cybersecurity systems. The investigation of several security breaches reveals an important impact of human errors in exhibiting security vulnerabilities. Although security researchers have long observed the impact of human behavior, few improvements have been made in designing secure systems that are resilient to the uncertainties of the human element. In this talk, we discuss several psychological theories that attempt to understand and influence the human behavior in the cyber world. Our goal is to use such theories in order to build predictive cyber security models that include the behavior of typical users, as well as system administrators. We then illustrate the importance of our approach by presenting a case study that incorporates models of human users. We analyze our preliminary results and discuss their challenges and our approaches to address them in the future. |
Notes | Presented at the ITI Joint Trust and Security/Science of Security Seminar, October 20, 2016. |
URL | https://recordings.engineering.illinois.edu:8443/ess/echo/presentation/fb4f2d83-7238-4e28-b538-ddff0... |
Citation Key | node-29809 |
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