Learning adversary's actions for secret communication

Mehrdad Tahmasbi, Matthieu R. Bloch, Aylin Yener

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Scopus citations


    We analyze the problem of secure communication over a wiretap channel with an active adversary, in which the legitimate transmitter has the opportunity to sense and learn the adversary's actions. Specifically, the adversary has the ability to switch between two channels and to observe the corresponding output at every channel use; the encoder, however, has causal access to observations impacted by adversary's actions. We develop a joint learning/transmission scheme in which the legitimate users learn and adapt to the adversary's actions. For some channel models, we show that the achievable rates, which we define precisely, are arbitrarily close to those obtained with hindsight, had the transmitter known the actions ahead of time. This suggests that there is much to exploit and gain in physical-layer security by monitoring the environment.

    Original languageEnglish (US)
    Title of host publication2017 IEEE International Symposium on Information Theory, ISIT 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages5
    ISBN (Electronic)9781509040964
    StatePublished - Aug 9 2017
    Event2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany
    Duration: Jun 25 2017Jun 30 2017

    Publication series

    NameIEEE International Symposium on Information Theory - Proceedings
    ISSN (Print)2157-8095


    Other2017 IEEE International Symposium on Information Theory, ISIT 2017

    All Science Journal Classification (ASJC) codes

    • Theoretical Computer Science
    • Information Systems
    • Modeling and Simulation
    • Applied Mathematics


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