The province of wireless sensor networks (WSNs) is continuously increasing due to widespread applications, like, military, monitoring environmental conditions, and several other domains. However, trust management in the WSN is a major challenge as trust is used when cooperation between nodes becomes critical to attaining reliable communication. Therefore, a new trust-based routing algorithm is proposed for initiating secured routing. Additionally, the paper proposes Chicken-Dragonfly (CHicDra) optimization algorithm for assisting secure communication by finding the optimal cluster heads (CHs) in the network. Once the CHs are selected with Multi-Objective Taylor Crow Optimization, the trusted nodes are optimally finalized using the Joint Trust that depends on the trust parameters, like integrity factor, consistency factors, forwarding rate factor, and availability factors. The proposed CHicDra is the modification of the chicken swam optimization with dragonfly algorithm. Finally, the optimally chosen path is employed for further communications in the network, which is secure and trustworthy. The proposed CHicDra computes maximal packet delivery ratio (PDR) of 44%, throughput of 52.8%, and minimal delay of 0.344, respectively.

Joint trust: an approach for trust-aware routing in WSN

In Wireless Sensor Network (WSN), securable data transmission is one of the most challenges. During the transmission between the source and a destination node, routing information of the particular path may be misbehaved by the particular nodes which are known as wormhole nodes/attackers. The paths which include the wormhole nodes are known as wormhole attacked paths. For improving security in WSN, these wormhole attacked paths should be identified. To achieve this, wormhole attack detection method and optimal or secure path selection are presented in this paper. Initially, ‘K’ paths or multiple paths are generated between source and destination using Ad-hoc On demand Multipath Distance Vector (AOMDV) routing protocol. Then, the source node identifies the wormhole attacked path by verifying the Detection Packet (DP) and Feedback Packet (FP) from the destination. After detecting the wormhole attacked paths, the source node selects the optimal path among the attacker free paths using Particle Swarm Optimization (PSO) algorithm. Simulation results show that the performance of the proposed approach improves energy efficiency and network lifetime of the network.

Detection of Wormhole Attack and Secure Path Selection in Wireless Sensor Network

Selective forwarding attacks in WSN can damage many mission-critical applications, like military surveillance and forest fire censoring. In such attacks, malicious nodes most of the time functions like regular nodes, but sometimes drop sensitive packets selectively, like a packet recording the dissimilar power' activity, making it more difficult to identify their malicious intent. The current selective forwarding attack detection schemes, randomly select checkpoint nodes, available in-between nodes within a forwarding route, which are responsible for producing acknowledgments for each received packet. In this paper, the complete sets of nodes are differentiated into three different types based on their functionality as Inspector Node (IN), Cluster Head (CH), and Member Nodes (MN). The newly considered node as IN is considered to overhear all of the activities of the Cluster head, as CH is the most compromising node in the complete cluster, and in the case, if the CH is attacked then the complete cluster stops working in the network. The IN is trained based on certain rules and predefined parameters which analyses if the CH or MN is malicious or not and considers the required action. NS2 is considered for the simulation of the proposed methodology and also for the validation of the proposed work. In the proposed methodology, two different stages are considered as detection and correction, which works to tackle the attacks and also considering the system efficiency almost. As in the proposed methodology, the effect of the attack is minimized which increases the QOS and also better data transmission.

Learning-Based Security Technique for Selective Forwarding Attack in Clustered WSN

Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs. Firstly, a fuzzy trust evaluation method is presented to transform the transmission evidences into trust values while effectively alleviating the trust uncertainty. And then, a K-Means based outlier detection scheme is proposed to further analyze plenty of trust values obtained via fuzzy trust evaluation or trust recommendation. It can discover the commonalities and differences among sensor nodes while improving the accuracy of outlier detection. Finally, we present an evolutionary game based secure clustering protocol to achieve a trade-off between security assurance and energy saving for sensor nodes when electing for the cluster heads. A sensor node which failed to be the cluster head can securely choose its own head by isolating the suspicious nodes. Simulation results verify that our secure clustering protocol can effectively defend the network against the attacks from internal selfish or compromised nodes. Correspondingly, the timely data transfer rate can be improved significantly.

An Evolutionary Game-Based Secure Clustering Protocol With Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks

An availability predictive trust factor‐based semi‐Markov mechanism for effective cluster head selection in wireless sensor networks

A wireless sensor networks encompasses battery powered sensor nodes with extremely limited processing capabilities. One of the major challenges in WSN is to overcome the attacks like Sinkhole, Wormhole and Sybil, Dos attacks, Selective forwarding etc. which reduces the performance of the network, since the Cryptographic techniques are not much effective in solving this problem. So in order to protect wireless sensor networks from attacks and to perform improvement in some of the aspects we have implemented a low overhead trust aware routing with energy efficient network protocol. This protocol is designed by incorporating the trust aware routing frame work with adaptive periodic threshold sensitive energy efficient network protocol. By minimizing the attacks, the network provides a better QOS with trustworthy and energy efficient route which leads to increase the network life time.

Design of TAREEN (trust aware routing with energy efficient network) and enactment of TARF: a trust-aware routing framework for wireless sensor networks

M. Udhayavani

Papers

Design of TAREEN (trust aware routing with energy efficient network) and enactment of TARF: a trust-aware routing framework for wireless sensor networks