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SPIES Lab, Computer Science and Engineering

Texas A&M University College of Engineering

fNIRS

Study of Website Legitimacy and Familiarity

In this paper, we study the neural underpinnings relevant to user-centered web security through the lens of functional near-infrared spectroscopy (fNIRS). Specifically, we design and conduct a fNIRS study to pursue a thorough investigation of users’ processing of legitimate vs. illegitimate and familiar vs. unfamiliar websites. We pinpoint the neural activity in these tasks as well as the brain areas that control such activity. We show that, at the neurological level, users process the legitimate websites differently from the illegitimate websites when subject to phishing attacks. Similarly, we show that users exhibit marked differences in the way their brains process the previously familiar websites from unfamiliar websites. These findings have several defensive and offensive implications. In particular, we discuss how these differences may be used by the system designers in the future to differentiate between legitimate and illegitimate websites automatically based on neural signals. Similarly, we discuss the potential for future malicious attackers, with access to neural signals, in compromising the privacy of users by detecting whether a website is previously familiar or un-familiar to the user.
Compared to prior research, our novelty lies in several aspects. First, we employ a neuroimaging methodology (fNIRS) not tapped into by prior security research for the problem domain we are studying. Second, we provide a focused study design and comprehensive investigation of the neural processing underlying the specific tasks of legitimate vs. illegitimate and familiar vs. unfamiliar websites. Third, we use an experimental set-up much more amenable to real-world settings, compared to previous fMRI studies. Beyond these scientific innovations, our work also serves to corroborate and extend several of the findings of the prior literature with independent methodologies, tools and settings.

Experimental Setting

Experimental Setting

People

Faculty

  • Nitesh Saxena

Student

  • Ajaya Neupane (@UAB; PhD 2017)

External Collaborators:

  • Leanne Hirshfield (Syracuse University)

Publication

  • Neural Underpinnings of Website Legitimacy and Familiarity Detection: An fNIRS Study.
    Ajaya Neupane, Nitesh Saxena and Leanne Hirshfield.
    In Security and Privacy Track, the World-Wide Web Conference (WWW), 2017.
    [pdf]

Recent News

  • Paper accepted to CCS 2023 September 2, 2023
  • Paper accepted to PETS 2024 August 31, 2023
  • Paper accepted to CNS 2023 August 13, 2023
  • Paper accepted to MobiCom 2023 August 6, 2023
  • Presenting SPIES’ 13th PhD Graduate — Shalini Saini June 20, 2023
  • Dr. Saxena appointed as Associate Director of Cybersecurity Institute June 7, 2023
  • Saxena and team awarded $6M DOD grant on cognitive security May 3, 2023
  • Dr. Saxena appointed as the Vice Chair of EFAC May 3, 2023
  • Paper accepted to MobiSys 2023 May 2, 2023
  • Paper accepted to ICDCS 2023 April 11, 2023
  • Journal paper accepted to ACM Computing Surveys April 2, 2023
  • 3 full papers accepted to WiSec 2023 March 28, 2023
  • Paper accepted to Oakland 2023 March 14, 2023
  • Paper accepted to USENIX Security 2023 February 21, 2023
  • Cybersecurity Program Led By Dr. Saxena Ranks Best! January 26, 2023
  • EarSpy in Media January 26, 2023
  • Dr. Saxena is a Co-PI on Thematic AI Lab November 28, 2022
  • Paper accepted to PMC 2022 November 28, 2022
  • Paper accepted to ICISC 2022 November 28, 2022
  • A New Grant from NSA October 17, 2022

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