An Efficient ID-Based Scheme For Filtering Gang Injected False Data In Wireless Sensor Networks

Abstract: Wireless sensor networks are usually deployed at aggressive environments which are more vulnerable to various security attacks such as selective forwarding, wormholes and sybil attacks. In such network user authentication is essential in any service- oriented communication network in order to identify and reject any access request of an unauthorized user. This project of wireless sensor networks focus on injecting false data attack and their mitigation techniques. For an injecting false data attack, an attacker node first compromises the sensor nodes and then accesses all keying materials stored in the compromised nodes and then controls these compromised nodes to inject bogus information and send the false data to the sink to cause upper-level error decision as well as energy depletion in en-route nodes. Therefore filtering false data should also be executed as early as possible to mitigate the energy consumption. To tackle this challenging issue false data filtering mechanisms known as novel bandwidth-efficient cooperative authentication (BECAN) scheme is developed for filtering injected false data in wireless sensor networks. Although it identifies false data attack it cannot prevent gang injecting false data attack from mobile compromised sensor nodes. To enhance the efficiency of verification, a new ID-based signature scheme is proposed that allows batch verification of multiple signatures to mitigate gang injection of false attack threat. It allows any pair of users to communicate securely and to verify each other's signatures without exchanging public key certificates.

Keywords: Filtering false data, En-route Filtering, BECAN,ID-Based Scheme, DSS Signature, compromised nodes, Gang injection .