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    A method for detecting abnormal program behavior on embedded devices

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    Authors
    Zhai, Xiaojun cc
    Ehsan, Shoaib
    Howells, Gareth
    Dongbing, Gu
    McDonald-Maier, Klaus
    Appiah, Kofi cc
    Hu, Huosheng cc
    Affiliation
    University of Leicester
    University of Essex
    University of Kent
    University of Derby
    Issue Date
    2015-04-13
    
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    Abstract
    A potential threat to embedded systems is the execution of unknown or malicious software capable of triggering harmful system behavior, aimed at theft of sensitive data or causing damage to the system. Commercial off-the-shelf embedded devices, such as embedded medical equipment, are more vulnerable as these type of products cannot be amended conventionally or have limited resources to implement protection mechanisms. In this paper, we present a self-organizing map (SOM)-based approach to enhance embedded system security by detecting abnormal program behavior. The proposed method extracts features derived from processor's program counter and cycles per instruction, and then utilises the features to identify abnormal behavior using the SOM. Results achieved in our experiment show that the proposed method can identify unknown program behaviors not included in the training set with over 98.4% accuracy.
    Citation
    Zhai, X, Appiah, K, Ehsan, S, Howells, G, Hu, H, Gu, D, & McDonald-Maier, K (2015), 'A Method for Detecting Abnormal Program Behavior on Embedded Devices', IEEE Transactions On Information Forensics And Security, 10, 8, pp. 1692-1704
    Publisher
    IEEE
    Journal
    IEEE Transactions on Information Forensics and Security
    URI
    http://hdl.handle.net/10545/583863
    DOI
    10.1109/TIFS.2015.2422674
    Additional Links
    http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7084637
    Type
    Article
    Language
    en
    Series/Report no.
    INSPEC Accession Number: 15232972
    Vol. 10
    Issue 8
    ISSN
    1556-6013
    EISSN
    1556-6021
    ae974a485f413a2113503eed53cd6c53
    10.1109/TIFS.2015.2422674
    Scopus Count
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    Department of Mechanical Engineering & the Built Environment

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