Merkle-Hellman knapsack-side channel monitoring based secure scheme for detecting provenance forgery and selfish nodes in wireless sensor networks

Provenance counterfeit and packet loss assaults are measured as threats in the large scale wireless sensor networks which are engaged for diverse application domains. The assortments of information source generate necessitate promising the reliability of information such as only truthful information is measured in the decision procedure. Details about the sensor nodes play an major role in finding trust value of sensor nodes. In this paper, a novel lightweight secure provenance method is initiated for improving the security of provenance data transmission. The anticipated system comprises provenance authentication and renovation at the base station by means of Merkle-Hellman knapsack algorithm based protected provenance encoding in the Bloom filter framework. Side Channel Monitoring (SCM) is exploited for noticing the presence of selfish nodes and packet drop behaviors. This lightweight secure provenance method decreases the energy and bandwidth utilization with well-organized storage and secure data transmission. The investigational outcomes establishes the efficacy and competence of the secure provenance secure system by professionally noticing provenance counterfeit and packet drop assaults which can be seen from the assessment in terms of provenance confirmation failure rate, collection error, packet drop rate, space complexity, energy consumption, true positive rate, false positive rate and packet drop attack detection.