• DocumentCode
    3217627
  • Title

    RSSI vector attack detection method for wireless sensor networks

  • Author

    Guoqiang, Yan ; Weijun, Duan ; Chao, Ma ; Liang, Huang

  • Author_Institution
    Sch. of Electron., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    27-29 May 2011
  • Firstpage
    229
  • Lastpage
    232
  • Abstract
    In contrast to traditional networks, Wireless Sensor networks (WSN) are more vulnerable to attacks such as DOS, eavesdropping, tampering, node compromise, wormhole and Sibyl. To give security protection for WSN, many attack prevention and detection methods were proposed. As the second line of defence, Intrusion Detection can resist attacks under cryptography technologies are unavailable, and provide strategies for network recovery. This paper proposed a novel attack detection based on RSSI technology. It collects multi-observed RSSI values to form vectors, and uses mean vector confidential interval examination of multivariate normal population to detect malicious packets. Real experiments showed that vector-based detection approach have a better detection sensitivity and fault tolerance than single value detection approach.
  • Keywords
    cryptography; fault tolerance; signal detection; wireless sensor networks; RSSI vector attack detection method; Sibyl; attack prevention; cryptography technology; denial of service; detection sensitivity; fault tolerance; intrusion detection; mean vector confidential interval examination; network recovery; node compromise; received signal strength indicator; security protection; vector-based detection; wireless sensor networks; wormhole; Communication system security; Routing; Security; Sensitivity; Vectors; Wireless communication; Wireless sensor networks; Attack Detection; RSSI Vector; Security; WSN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-61284-485-5
  • Type

    conf

  • DOI
    10.1109/ICCSN.2011.6013581
  • Filename
    6013581