Security and Privacy in Communication Networks. 9th International ICST Conference, SecureComm 2013, Sydney, NSW, Australia, September 25-28, 2013, Revised Selected Papers

Research Article

Anomaly Detection in Beacon-Enabled IEEE 802.15.4 Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-319-04283-1_1,
        author={Eirini Karapistoli and Anastasios Economides},
        title={Anomaly Detection in Beacon-Enabled IEEE 802.15.4 Wireless Sensor Networks},
        proceedings={Security and Privacy in Communication Networks. 9th International ICST Conference, SecureComm 2013, Sydney, NSW, Australia, September 25-28, 2013, Revised Selected Papers},
        proceedings_a={SECURECOMM},
        year={2014},
        month={6},
        keywords={Wireless Sensor Networks Beacon-enabled IEEE 802.15.4 MAC Rule-based Anomaly Detection},
        doi={10.1007/978-3-319-04283-1_1}
    }
    
  • Eirini Karapistoli
    Anastasios Economides
    Year: 2014
    Anomaly Detection in Beacon-Enabled IEEE 802.15.4 Wireless Sensor Networks
    SECURECOMM
    Springer
    DOI: 10.1007/978-3-319-04283-1_1
Eirini Karapistoli1,*, Anastasios Economides1,*
  • 1: University of Macedonia
*Contact email: ikarapis@uom.gr, economid@uom.gr

Abstract

During the past decade, wireless sensor networks (WSNs) have evolved as an important wireless networking technology attracting the attention of the scientific community. With WSNs being envisioned to support applications requiring little to no human attendance, however, these networks also lured the attention of various sophisticated attackers. Today, the number of attacks to which WSNs are susceptible is constantly increasing. Although many anomaly detection algorithms have been developed since then to defend against them, not all of them are tailored to the IEEE 802.15.4 standard, a dominant communication standard for low power and low data rate WSNs. This paper proposes a novel anomaly detection algorithm aimed at securing the beacon-enabled mode of the IEEE 802.15.4 MAC protocol. The performance of the proposed algorithm in identifying intrusions using a rule-based detection technique is studied via simulations.