Multi-modal decision fusion for continuous authentication

Lex Fridman, Ariel Stolerman, Sayandeep Acharya, Patrick Brennan, Patrick Juola, Rachel Greenstadt, Moshe Kam, Felix Gomez

    Research output: Contribution to journalArticle

    Abstract

    Active authentication is the process of continuously verifying a user based on their ongoing interaction with a computer. In this study, we consider a representative collection of behavioral biometrics: two low-level modalities of keystroke dynamics and mouse movement, and a high-level modality of stylometry. We develop a sensor for each modality and organize the sensors as a parallel binary decision fusion architecture. We consider several applications for this authentication system, with a particular focus on secure distributed communication. We test our approach on a dataset collected from 67 users, each working individually in an office environment for a period of approximately one week. We are able to characterize the performance of the system with respect to intruder detection time and robustness to adversarial attacks, and to quantify the contribution of each modality to the overall performance.

    Original languageEnglish (US)
    Pages (from-to)142-156
    Number of pages15
    JournalComputers and Electrical Engineering
    Volume41
    Issue numberC
    DOIs
    StatePublished - 2015

    Keywords

    • Active authentication
    • Behavioral biometrics
    • Decision fusion
    • Distributed communication
    • Multimodal biometric systems
    • Security and privacy

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Computer Science(all)
    • Electrical and Electronic Engineering

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  • Cite this

    Fridman, L., Stolerman, A., Acharya, S., Brennan, P., Juola, P., Greenstadt, R., Kam, M., & Gomez, F. (2015). Multi-modal decision fusion for continuous authentication. Computers and Electrical Engineering, 41(C), 142-156. https://doi.org/10.1016/j.compeleceng.2014.10.018