IoT Traffic Flow Identification using Locality Sensitive Hashes

Batyr Charyyev, Mehmet Hadi Gunes

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    38 Scopus citations

    Abstract

    Systems get smarter with computing capabilities, especially in the form of Internet of Things (IoT) devices. IoT devices are often resource-limited as they are optimized for a certain task. Hence, they are prone to be compromised and have become a target of malicious activities. Since IoT devices lack computing power for security software, network administrators need to isolate such devices and limit traffic to the device based on their communication needs. To this end, network administrators need to identify IoT devices when they join a network and detect anomalous traffic when they are compromised. In this paper, we introduce a novel approach to identify the IoT device based on the Nilsimsa hash of its traffic flow. Different from previous studies, the proposed approach does not require feature extraction from the data. In our evaluations, our approach has an average precision and recall of 93% and 90%, respectively.

    Original languageEnglish
    Title of host publication2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
    ISBN (Electronic)9781728150895
    DOIs
    StatePublished - Jun 2020
    Event2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland
    Duration: 7 Jun 202011 Jun 2020

    Publication series

    NameIEEE International Conference on Communications
    Volume2020-June
    ISSN (Print)1550-3607

    Conference

    Conference2020 IEEE International Conference on Communications, ICC 2020
    Country/TerritoryIreland
    CityDublin
    Period7/06/2011/06/20

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