10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

Role-Playing Game for Studying User Behaviors in Security: A Case Study on Email Secrecy

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2014.257242,
        author={Kui Xu and Danfeng Yao and Manuel A. Perez-Quinones and Casey Link and E. Scott Geller},
        title={Role-Playing Game for Studying User Behaviors in Security: A Case Study on Email Secrecy},
        proceedings={10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2014},
        month={11},
        keywords={adversary's knowledge privacy social interaction cyber game},
        doi={10.4108/icst.collaboratecom.2014.257242}
    }
    
  • Kui Xu
    Danfeng Yao
    Manuel A. Perez-Quinones
    Casey Link
    E. Scott Geller
    Year: 2014
    Role-Playing Game for Studying User Behaviors in Security: A Case Study on Email Secrecy
    COLLABORATECOM
    IEEE
    DOI: 10.4108/icst.collaboratecom.2014.257242
Kui Xu1, Danfeng Yao1,*, Manuel A. Perez-Quinones1, Casey Link1, E. Scott Geller1
  • 1: Virginia Tech
*Contact email: danfeng@cs.vt.edu

Abstract

Understanding the capabilities of adversaries (e.g., how much the adversary knows about a target) is important for building strong security defenses. Computing an adversary's knowledge about a target requires new modeling techniques and experimental methods. Our work describes a quantitative analysis technique for modeling an adversary's knowledge about private information at workplace. Our technical enabler is a new emulation environment for conducting user experiments on attack behaviors. We develop a role-playing cyber game for our evaluation, where the participants take on the adversary role to launch ID theft attacks by answering challenge questions about a target. We measure an adversary's knowledge based on how well he or she answers the authentication questions about a target. We present our empirical modeling results based on the data collected from a total of 36 users.