Abstract
Wireless sensor network consists of a large number of resource constrained sensor nodes. These sensor nodes communicate over wireless medium to perform a variety of information processing functionality. Due to broadcast nature of wireless medium, security is one of the major concerns and overlapping sensing range of sensor nodes results in redundancy in sensing data. Moreover, a large amount of energy is consumed by the base station to process these redundant data. To conserve energy and enhance the lifetime of sensor nodes, redundancy is eliminated at intermediate nodes by performing data aggregation. Wireless sensor networks are generally deployed in untrusted and hostile environments which results in compromised nodes. Thus, security and reliability of the transmitted data get reduced. Compromised nodes can inject false data, drop all the data, selectively forward data to an attacker, copy legal nodes to join routing paths, and disrupt data transmission during the data aggregation operation. In this paper, a novel scheme for data aggregation based on trust and reputation model is presented to ensure security and reliability of aggregated data. It will help to select secure paths from sensor nodes to the base station; thereby the accuracy of aggregated data will be increased significantly. Simulations show that the proposed protocol LDAT has less energy consumption and more accuracy as compared to some existing protocols which are based on functional reputation.
Highlights
Data Aggregation is one of the methods to reduce the communication burden in which a sensor node naming data aggregator processes and aggregates incoming data before passing it to its neighbour node
The objective of this paper is to provide the comparison of various trust mechanism with short summarization of trust methodologies in Wireless Sensor Networks (WSN) which can provide a high level of security taking into account accuracy, average path length leading to trustworthy sensors and energy conservation
The evaluation of action of sensor nodes by data aggregators based on the respective functional reputation of nodes increases the reliability and accuracy of trust system
Summary
Data Aggregation is one of the methods to reduce the communication burden in which a sensor node naming data aggregator processes and aggregates incoming data before passing it to its neighbour node. Trust and Reputation System helps to maintain a minimum security level between the entities of distributed systems for interactions or transactions These entities in a WSN are data aggregator node, normal node and base station. Ganeriwal and Srivastava [15] proposed reputation based framework in which nodes maintain the record of reputation of other nodes and use this information to evaluate their trustworthiness This provides a generalized approach for detecting the malicious or faulty nodes in the network. In the technique [16], authors proposed a trust based framework in which KullbackLeibler (KL) is used to evaluate the trustworthiness of sensor nodes in which compromised nodes are detected with the help of unsupervised learning. The evaluation of action of sensor nodes by data aggregators based on the respective functional reputation of nodes increases the reliability and accuracy of trust system. Steps for mLFTM which in turn based on BTRM-WSN
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