Research Article Rank-Based Report Filtering Scheme (RRFS) for Verifying Phoney Reports in Wireless Sensor Networks Gayathri Santhosh and Yogesh Palanichamy Department of Information Science and Technology, College of Engineering, Anna University, Guindy, Chennai 600025, India Correspondence should be addressed to Gayathri Santhosh; m.gayath@yahoo.com Received 11 February 2020; Revised 17 August 2020; Accepted 20 August 2020; Published 15 September 2020 Academic Editor: Pierre-Martin Tardif Copyright © 2020 Gayathri Santhosh and Yogesh Palanichamy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Wireless sensor networks (WSNs) are open to false data injection attack when they are deployed in hostile scenarios. Attackers can easily deceive the sink by compromising sensing nodes or by injecting phoney data into the network. Such attacks can deplete the energy resources of the network by providing wrong information which in turn can affect the proper network functioning or sometimes can shut the network from further functioning. The existing schemes that deal with this problem focus on only a few aspects of the false data injection attack. To resolve this problem, we propose a Rank-based Report Filtering Scheme (RRFS), a holistic and group verification scheme for the identification of compromised nodes and the filtering of false data injected into the network. The proposed scheme verifies report among clusters, en-routers, and sink. Hence, the RRFS, a holistic scheme that is composed of three-tier verifications, successfully rejects the false data before the attackers falsify the whole environment, and this makes the system unique. Reliability Index (RI) is calculated by the nodes for fellow cluster members, and the cluster head (CH) provides the score for a node based on its RI. This, in turn, strengthens the scheme by assisting the en-routers to detect the compromised nodes. The RRFS scheme has been verified and validated by extensive simulation and meticulous performance evaluation of filtering efficiency and energy consumption against various schemes. The scheme gives high filtering efficiency against the multiple compromised nodes and also improves the network’s lifespan. The sustainability of RRFS against numerous attacks that are launched in the sensor environment is thoroughly investigated. 1. Introduction Wireless sensor network is a collection of sensor nodes that works together to sense various physical parameters by monitoring the given domain [1]. Each node has various sen- sors, actuators, a wireless transceiver, a microcontroller, and power sources. Recent developments that have taken place in the areas of wireless communication and microelectrome- chanical system (MEMS) have led to the deployment of distributed wireless sensing systems. WSNs are widely used in unfavourable terrains like forests, deserts, and battlefields [2]. In recent times, they gain importance in urban areas. As of now, the applications of WSNs include healthcare, military, environmental, smart cities [3], and other regions. WSNs are inherently vulnerable since they are wireless and deployed in remote locations where physical monitoring is difficult. The major attacks launched against WSNs are Sybil attack [4], wormhole attack [5], DoS attack [6], black hole attack [7], eavesdropping [8], jamming [9] etc. Out of all the possible attacks, false data injection attack is the most critical attack. Adversary compromises the sensor node [10] and pushes false or malicious data into the network in such a way that the operators of the network would not be able to realise that the false/malicious data have been injected inside the network. Event-based report generation is com- promised with the false data injection, which misleads the sink to initiate a wrong activity. It also depletes the energy of the nodes by making them forward unnecessary reports to the sink. Several verification schemes have been proposed for filtering the injected false data in the network [11–18]. We have observed that many of these schemes are prone to node compromise attack [19] and selective forwarding attack [20]. Hindawi Wireless Communications and Mobile Computing Volume 2020, Article ID 2785960, 22 pages https://doi.org/10.1155/2020/2785960