A Key Level Selection Within Hash Chains for the Efficient Energy Consumption in WSNS

Abstract

A wireless sensor network is comprised of a base station (BS) and numerous sensor nodes. The sensor nodes lack security because they function in an open environment, such as the military. In particular, a false statement injection attack seizures and compromises sensor nodes. The attack then causes the compromised nodes to create forward false reports. Due to the false report injection attack, not only does the sensor network have a false alarm, but its limited energy is also emptied. In order to preserve the false report injection attack, over the past few years, several studies have been made looking for a resolution to the attack. Ye et al. studied statistical en-route filtering (SEF). SEF is a method of randomly verifying event reports in the en-route filtering phase. SEF can filter many false reports early using proof of intermediate nodes. However, because the number of keys in a sensor node is fixed by the system, the sensor network cannot control the event report proof probability depending on the conditions of the network. Therefore, it is tough to proficiently consume energy of the sensor network. In order to resolve the problem, we suggest a technique which controls the event report verification probability by using a key sequence level of an event report. In the suggested method, when an intermediate node obtains an event report, the node authenticates the event report by relating a key sequence level of the report and its key sequence level. Elements defining the key sequence level comprise the concentration of neighbor nodes in the sensing range of a center of stimulus (CoS), the number of stages from the CoS to the BS, and the average of the key sequence level of intermediate nodes in each track. We imitated the projected technique and the SEF technique to assess the performance in terms of energy efficiency and security. In the recreation results, the projected technique disbursed an average of 7.9% less energy of the sensor nodes compared to SEF method. The number of untrue reports inward at the BS of the proposed technique was also fewer, by an average of 6.4, compared to the SEF technique. Concluded the results, we can understand that when the number of false report is huge in the sensor network, the proposed technique is more energy-efficient and protected than the SEF technique.

Keywords: Wireless Sensor Network, False Report Injection Attack, Statistical En-Route Filtering, Energy Efficiency, Security