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Ad Hoc Networks. 12th EAI International Conference, ADHOCNETS 2020, Paris, France, November 17, 2020, Proceedings

Research Article

Analysis and Performance of Topology Inference in Mobile Ad Hoc Networks

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  • @INPROCEEDINGS{10.1007/978-3-030-67369-7_6,
        author={J. David Brown and Mazda Salmanian and Tricia J. Willink},
        title={Analysis and Performance of Topology Inference in Mobile Ad Hoc Networks},
        proceedings={Ad Hoc Networks. 12th EAI International Conference, ADHOCNETS 2020, Paris, France, November 17, 2020, Proceedings},
        proceedings_a={ADHOCNETS},
        year={2021},
        month={1},
        keywords={Network topology inference Mobile ad hoc networks (MANET) Traffic analysis Cyber analytics},
        doi={10.1007/978-3-030-67369-7_6}
    }
    
  • J. David Brown
    Mazda Salmanian
    Tricia J. Willink
    Year: 2021
    Analysis and Performance of Topology Inference in Mobile Ad Hoc Networks
    ADHOCNETS
    Springer
    DOI: 10.1007/978-3-030-67369-7_6
J. David Brown,*, Mazda Salmanian, Tricia J. Willink
    *Contact email: david.brown@drdc-rddc.gc.ca

    Abstract

    This paper examines the performance of a strategy for mapping the topology of a mobile ad hoc network (MANET), providing insight for network defenders to understand how much information an adversary could discern about a target network. Using this topology inference strategy, a network eavesdropper collects frame emission start- and end-times and uses these to detect the presence of link layer acknowledgements between devices and ultimately constructs a network topology. We show how the performance of this simple strategy varies as a function of the amount of data collected by the eavesdropper over time, the size of the target network, the speed of the nodes, and the nodes’ data generation rate. We derive analytical results that allow for the rapid computation of expected true positive rate and false positive rate for topology inference in a MANET; these are compared against simulation results. The analytical results are used to derive a sensible window of observation over which to perform inference, with guidance on when to discard stale data. The results are also used to recommend strategies for network defenders to frustrate the performance of an adversary’s network inference.

    Keywords
    Network topology inference Mobile ad hoc networks (MANET) Traffic analysis Cyber analytics
    Published
    2021-01-31
    Appears in
    SpringerLink
    http://dx.doi.org/10.1007/978-3-030-67369-7_6
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