BLEDiff: Scalable and Property-Agnostic Noncompliance Checking for BLE Implementations

Imtiaz Karim, Abdullah Al Ishtiaq, Syed Rafiul Hussain, Elisa Bertino

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

    1 Scopus citations


    In this work, we develop an automated, scalable, property-agnostic, and black-box protocol noncompliance checking framework called BLEDiff that can analyze and uncover noncompliant behavior in the Bluetooth Low Energy (BLE) protocol implementations. To overcome the enormous manual effort of extracting BLE protocol reference behavioral abstraction and security properties from a large and complex BLE specification, BLEDiff takes advantage of having access to multiple BLE devices and leverages the concept of differential testing to automatically identify deviant noncompliant behavior. In this regard, BLEDiff first automatically extracts the protocol FSM of a BLE implementation using the active automata learning approach. To improve the scalability of active automata learning for the large and complex BLE protocol, BLEDiff explores the idea of using a divide and conquer approach. BLEDiff essentially divides the BLE protocol into multiple sub-protocols, identifies their dependencies and extracts the FSM of each sub-protocol separately, and finally composes them to create the large protocol FSM. These FSMs are then pair-wise tested to automatically identify diverse deviations. We evaluate BLEDiff with 25 different commercial devices and demonstrate it can uncover 13 different deviant behaviors with 10 exploitable attacks.

    Original languageEnglish (US)
    Title of host publicationProceedings - 44th IEEE Symposium on Security and Privacy, SP 2023
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages19
    ISBN (Electronic)9781665493369
    StatePublished - 2023
    Event44th IEEE Symposium on Security and Privacy, SP 2023 - Hybrid, San Francisco, United States
    Duration: May 22 2023May 25 2023

    Publication series

    NameProceedings - IEEE Symposium on Security and Privacy
    ISSN (Print)1081-6011


    Conference44th IEEE Symposium on Security and Privacy, SP 2023
    Country/TerritoryUnited States
    CityHybrid, San Francisco

    All Science Journal Classification (ASJC) codes

    • Safety, Risk, Reliability and Quality
    • Software
    • Computer Networks and Communications

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