Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015, Revised Selected Papers, Part II

Research Article

A Study on the Detection of Abnormal Behavior and Vulnerability Analysis in BYOD

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  • @INPROCEEDINGS{10.1007/978-3-319-47075-7_20,
        author={Taeeun Kim},
        title={A Study on the Detection of Abnormal Behavior and Vulnerability Analysis in BYOD},
        proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015, Revised Selected Papers, Part II},
        proceedings_a={IOT360},
        year={2017},
        month={6},
        keywords={Mobile BYOD Security Context information Behavior pattern analysis},
        doi={10.1007/978-3-319-47075-7_20}
    }
    
  • Taeeun Kim
    Year: 2017
    A Study on the Detection of Abnormal Behavior and Vulnerability Analysis in BYOD
    IOT360
    Springer
    DOI: 10.1007/978-3-319-47075-7_20
Taeeun Kim1,*
  • 1: Korea Internet & Security Agency
*Contact email: tekim31@kisa.or.kr

Abstract

When many companies recently introduced BYOD (Bring Your Own Device), i.e. allowing employees to use personal mobile devices at work, they also adopted the NAC and MDM system for prevention of confidential information leakage, access control and efficient user management. As the access control policy of the NAC and MDM system is uniformly applied to users, however, they cannot be aggressive in implementing BYOD since there are security threats due to the frequent loss and theft of devices and low security. Accordingly, it is necessary to be able to flexibly set up policies and detect and control abnormal users by collecting personalized context information. This paper proposes a behavior-based abnormality detection method that detects abnormal behavior by classifying vulnerabilities occurring in the BYOD environment and patterning various users’ information use contexts.