• DocumentCode
    1949779
  • Title

    SAD-SJ: A self-adaptive decentralized solution against Selective Jamming attack in Wireless Sensor Networks

  • Author

    Tiloca, Marco ; De Guglielmo, Domenico ; Dini, G. ; Anastasi, Giuseppe

  • Author_Institution
    Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy
  • fYear
    2013
  • fDate
    10-13 Sept. 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Wireless Sensor Networks (WSNs) are currently used in many application scenarios, including industrial applications and factory automation. In such scenarios, Time Division Multiple Access (TDMA) is typically used for data communication among sensor nodes. However, TDMA-based WSNs are particularly prone to Selective Jamming attack, a specific form of Denial of Service attack aimed at severely thwarting network reliability. In this paper, we present SAD-SJ, a self-adaptive and decentralized MAC-layer solution against selective jamming in TDMA-based WSNs. SAD-SJ does not need a central entity, requires sensor nodes to rely only on local information, and allows them to join and leave the network without hindering other nodes activity. We show that SAD-SJ introduces a limited overhead, in terms of computation, communication and energy consumption.
  • Keywords
    access protocols; telecommunication network reliability; telecommunication security; time division multiple access; wireless sensor networks; MAC layer; SAD-SJ; TDMA; WSN; data communication; denial of service attack; factory automation; industrial applications; network reliability; self-adaptive decentralized solution against selective jamming attack; time division multiple access; wireless sensor networks; Energy consumption; Jamming; Resource management; Robot sensing systems; Time division multiple access; Vectors; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies & Factory Automation (ETFA), 2013 IEEE 18th Conference on
  • Conference_Location
    Cagliari
  • ISSN
    1946-0740
  • Print_ISBN
    978-1-4799-0862-2
  • Type

    conf

  • DOI
    10.1109/ETFA.2013.6648037
  • Filename
    6648037