Distributed position localization and tracking (DPLT) of malicious nodes in cluster based mobile ad hoc networks (MANET)

  • Authors:
  • Shakhakarmi Niraj;Dhadesugoor R. Vaman

  • Affiliations:
  • Department of Electrical and Computer Engineering, Prairie View A & M University, Prairie View, Texas and ARO Center for Battlefield Communications;Department of Electrical and Computer Engineering, Prairie View A & M University, Prairie View, Texas and ARO Center for Battlefield Communications

  • Venue:
  • WSEAS TRANSACTIONS on COMMUNICATIONS
  • Year:
  • 2010

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Abstract

In this paper, a robust distributed malicious node detection and precise localization and tracking method is proposed for Cluster based Mobile Ad hoc Network (MANET). Certificate Authority (CA) node is selected as the most stable node among trusted nodes, surrounded by Registration Authority nodes (RAs) in each cluster to generate the Dynamic Demilitarized Zone (DDMZ) to defend CA from probable attackers and mitigate the authentication overhead. The RAs also co-operate with member nodes to detect a target node and determine whether it is malicious or not, by providing the public key certificate and trust value. In addition, Internet Protocol (IP) based Triangulation and multi-lateration method are deployed based on using the average time difference of Time of Arrival (ToA) and Time of Departure (ToD) of the management packets. Triangulation uses three reference nodes which are elected within each cluster based on Best Criterion Function (BCF) to localize each member node inside the cluster in 2D. Multi-lateration is employed to localize the malicious target node in 2D using four neighbor nodes. After localization of two consecutive positions, the target node is continuously localized and tracked by a particular node using the modified real time Position Localization and Tracking (PL&T) algorithm by adaptive beam forming and mapping the energy contours of tracking zone into coverage radii distance. The performance of the proposed scheme demonstrates the significant accuracy in the detection of malicious nodes within each cluster.