A statistical-based anomaly detection method for connected cars in internet of things environment

Mee Lan Han, Sangjin Lee, Ah Reum Kang, Sungwook Kang, Jung Kyu Park, Huy Kang Kim

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

    21 Citations (Scopus)

    Abstract

    A connected car is the most successful thing in the era of Internet of Things (IoT). The connections between vehicles and networks grow and provide more convenience to users. However, vehicles become exposed to malicious attacks from outside. Therefore, a connected car now needs strong safeguard to protect malicious attacks that can cause security and safety problems at the same time. In this paper, we proposed a method to detect the anomalous status of vehicles. We extracted the invehicle traffic data from the well-known commercial car and performed the one-way ANOVA test. As a result, our statistical-based detection method can distinguish the abnormal status of the connected cars in IoT environment.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    PublisherSpringer Verlag
    Pages89-97
    Number of pages9
    Volume9502
    ISBN (Print)9783319272924
    DOIs
    Publication statusPublished - 2015
    Event2nd International Conference on Internet of Vehicles – Safe and Intelligent Mobility, IOV 2015 - Chengdu, China
    Duration: 2015 Dec 192015 Dec 21

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9502
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other2nd International Conference on Internet of Vehicles – Safe and Intelligent Mobility, IOV 2015
    Country/TerritoryChina
    CityChengdu
    Period15/12/1915/12/21

    Keywords

    • Anomaly detection
    • ANOVA
    • Connected car
    • Internet of Things

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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