A lightweight Sybil attack detection framework for Wireless Sensor Networks

Abstract

In the field of Wireless Sensor Networks (WSNs), the problem of Sybil attacks has been widely considered by researchers. However, among the existing solutions, lightweight models are very limited. To accomplish this, the authors suggest a lightweight Sybil attack detection framework (LSDF) in this paper. This framework has two components: first, evidence collection; second, evidence validation. Every node in the network collects the evidences by observing the activities of neighboring nodes. These evidences are validated by running sequential hypothesis test to decide whether neighboring node is a benign node or Sybil node. With extensive simulations, it was revealed that the LSDF can detect Sybil activity accurately with few evidences.