• DocumentCode
    3779420
  • Title

    Anomaly Behavior Analysis System for ZigBee in smart buildings

  • Author

    Bilal Al Baalbaki;Jesus Pacheco;Cihan Tunc;Salim Hariri;Youssif Al-Nashif

  • Author_Institution
    Electrical and Computer Engineering Department, The University of Arizona line, Tucson, USA
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Smart Building (SB) exploits advances in information and communication technologies in order to provide the next generation of information and automation services that will significantly reduce operational costs and improve performance and efficiency. SB elements are typically interconnected using short range wireless communication technologies such as ZigBee, which is the most used wireless communication protocol for SBs. However, ZigBee protocol has multiple vulnerabilities that can be exploited by cyberattacks. In this paper, we present an Anomaly Behavior Analysis System (ABAS) for ZigBee protocol to be used in SBs. Our ABAS can detect both known and unknown ZigBee attacks with a high detection rate and low false alarms. Additionally, after detection, our system classifies the attack based on the impact, origin, and destination. We evaluate our approach by launching many attack scenarios such as DoS, Flooding, and Pulse DoS attacks, and then we compare our results with other intrusion detection systems such as secure HAN, signature IDS, and specification IDS.
  • Keywords
    "Jamming","Classification algorithms","Algorithm design and analysis","Artificial neural networks","Correlation","Delays","Floods"
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2015 IEEE/ACS 12th International Conference of
  • Electronic_ISBN
    2161-5330
  • Type

    conf

  • DOI
    10.1109/AICCSA.2015.7507187
  • Filename
    7507187