NSF-Funded Research

A User-Centric Approach to the Design of Intelligent Fake Website Detection Systems

Under award number CNS-1049497

Goal

Fake websites have emerged as a major source of online fraud, accounting for billions of dollars in fraudulent revenue at the expense of unsuspecting Internet users. Existing tools for combating fake websites are not very accurate, are limited in terms of the categories and genres of fake websites they detect, and lack adequate usability often causing users to disregard their recommendations. Hence, there remains a need for intelligent detection systems capable of accurately detecting various types and genres of fake websites and displaying recommendations in a manner that is conducive to system use. In filling this gap, this research takes a novel user-centric approach that involves an assessment of user perceptions regarding detection-system design alternatives. The research method includes an extensive theory-based controlled lab experiment, which assesses the impacts of various design alternatives (such as website categories, genres, and accuracy/time tradeoffs) on users’ perceptions, behaviors, and skills (including security threat awareness, security threat appraisal, coping assessment, security behaviors, internet trust, and ability to identify fake websites). The research also develops a novel fake website detection system comprised of an intelligent hierarchical classification algorithm capable of promoting users’ trust in the Internet. It utilizes a test bed of two thousand fake websites that include more than two million web pages. This work uncovers new knowledge about factors influencing individuals’ online security behaviors and skills, promotes Internet trust by developing enhanced systems for identifying fake websites, and develops advanced data and web mining techniques suitable for incorporating into information systems curricula.

Research Team

Fatemeh “Mariam” Zahedi (Project PI), University of Wisconsin-Milwaukee

Ahmed Abbasi (Project Co-PI), University of Virginia

Yan Chen, Auburn University Montgomery

Publications

Refereed Journal Publications

  • Chen, Y. and Zahedi, F. M. 2016. “Individuals’ Internet Security Perceptions and Behaviors: Polycontextual Contrasts between The United States and China, research note, MIS Quarterly (MISQ), (MIS Flagship Journal), Vol. 40, No. 1, pp. 205-222.
  • Zahedi, F. M., Abbasi, A., and Chen, Y. 2015. “Fake-Website Detection Tools: Identifying Design Elements that Promote Trust and Use,” Journal of Association for Information Systems (JAIS), Vol. 16, No. 6, pp. 448-484.
  • Abbasi, A., Zahedi, F. M., Zeng, D., and Chen, Y., Chen, H., and Nunamaker, J. F. 2015. “Exploiting Genre and Structure Information for Enhanced Detection of Phishing Websites,”Journal of Management Information Systems (JMIS), Vol. 31, No. 4, pp. 109-157.
  • Abbasi, A. , Zahedi, F. M., Kaza, S. 2012 “Detecting Fake Medical Websites using Recursive Trust Labeling,” ACM Transactions on Information Systems, Vol. 49, No. 4.
  • Abbasi, A., Zahedi, F. M., Vance, T. and Chen, Y. “The Phishing Funnel: Understanding and Predicting User Susceptibility to Phishing Website Attacks,” under revision for MIS Quarterly.
  • Zahedi, F. M., Abbasi, A., and Chen, Y. “Trust Calibration of Security IT Artifacts: The Case of Fake Website Detection Tools,” under revision forJournal of Management Information Systems.
  • Zahedi, F. M., Abbasi, A., Chen, Y., and Zhao, H. “The Moderating Role of Intelligent Interface Personalization in Users’ Security Behaviors and Self-Protection Performance,” under revision.

Presentations and Refereed Conference Proceedings

  • Abbasi, A., Zahedi, F. M., and Chen, Y. 2012.  “The Phishing Funnel: Assessing the Impact of Anti-phishing Tool Performance on Attack Success Rates,”INFORMS, October, Phoenix, AZ.
  • Abbasi, A., Zahedi, F. M., and Chen, Y. 2012. “Impact of Anti-Phishing Tool Performance on Attack Success Rates,” Proceedings of 2012 IEEE International Conference on Intelligence and Security Informatics, June, Washington DC
  • Zahedi, F. M., Abbasi, A. and Chen, Y. 2011. “Trust Calibration of Security IT Artifacts: The Case of Fake Website Detection Tools,” Proceedings of the 6th AIS SIG-SEC Workshop in Security and Privacy (WISP), December, Shanghai, China.
  • Zahedi, F. M., Abbasi, A. and Chen, Y.2011. “Design Elements that Promote the Use of Fake Website-Detection Tools,” Proceedings of the 10th AIS SIG-HCI Workshop on Human Computer Interactions, December, Shanghai, China.
  • Chen, Y, Zahedi, M, and Abbasi, A. 2011.”Interface Design Elements for Anti-phishing Systems,” In Service-Oriented Perspectives in Design Science Research.  Proceedings of the 6th International Conference on Design Science Research in Information Systems and Technology, Lecture Notes in Computer Science, H. Jain, A. P. Sinha and P. Vitharana (Eds.), Springer-Verlag Berlin Heidelberg, Vol. 6629, pp. 253-265, Nominated for the Best Student Paper Award.