Comprehensive Trust based Routing Protocol to Mitigate Black-hole attack in Wireless Sensor Networks

Wireless Sensor Network (WSN) is a collection of sensor nodes, that sense environmental data and send it to the administrator for further processing. Sensor nodes are wireless devices with limited battery and are vulnerable to security attacks such as black hole attack, gray hole attack, sink hole attack etc. Researchers have proposed many security mechanisms to mitigate security attacks. Trust based approaches have gained tremendous interest among researchers to embed security in WSNs. A Trust Based Secure Routing Protocol to mitigate black hole attack is presented in this paper. The protocol computes comprehensive trust value for each node and routes the packets only through the nodes with trust value > 0.5. The results of the proposed protocol are compared with TBSEER [10] protocol. The results show an improvement in Packet Delivery Ratio (PDR), throughput, End to End (EED), routing overhead and energy consumption

Trust Score based Optimized Cluster Routing (TSOCR) approach for Enhancing the Lifetime of Wireless Sensor Networks

Energy efficiency is the most significant obstacle that Wireless Sensor Networks (WSN) must overcome, and the desire for solutions that maximize energy efficiency will never go away. There are a variety of methods that can be utilized to improve energy efficiency, with data transmission as the primary driver of maximum energy consumption. The transmission of data from the source to destination nodes uses more energy. When the transmission of data is handled better, the energy efficiency is improved and the lifetime of the network is increased. The purpose of this research is to propose an Trust Score based Optimized Cluster Routing (TSOCR)  scheme for WSNs, which is based on Whale Optimization Algorithm (WOA). A total trust score is derived by combining the results of computing three distinct trust scores, such as the direct, indirect, and the most recent trust score. The path that has the highest trust score is chosen as the route and employed for data transmission. The effectiveness of the work is evaluated by looking at factors such as the rate of packet delivery, the latency, the amount of energy consumed and the lifetime of the network

SAFE ROUTING MODEL AND BALANCED LOAD MODEL FOR WIRELESS SENSOR NETWORK

Wireless Sensor Networks (WSNs) play a very important role in providing realtime data access for Big Data and Internet. However, the open deployment, energy constraint, and lack of centralized administration make WSNs very vulnerable to various kinds of malicious attacks. In WSNs identifying malicious sensor devices and eliminating their sensed information plays a very important role for mission critical applications. Standard cryptography and authentication schemes cannot be directly used in WSNs because of the resource constraint nature of sensor devices. Thus, energy efficient and low latency methodology is required for minimizing the impact of malicious sensor devices. This paper presents a Secure and Load Balanced Routing (SLBR) scheme for heterogeneous clustered based WSNs. SLBR presents a better trust-based security metric that overcomes the problem when sensors keep oscillating from good to bad state and vice versa, and also SLBR balances load among CH. Thus, aids in achieving better security, packet transmission, and energy efficiency performance. Experiments are conducted to evaluate the performance of proposed SLBR model over existing trust-based routing model namely Exponential Cat Swarm Optimization (ECSO). The result attained shows SLBR model attains better performance than ECSO in terms of energy efficiency (i.e., network lifetime considering first sensor device death and total sensor device death), communication overhead, throughput, packet processing latency, malicious sensor device misclassification rate and identification

Fuzzy TOPSIS-based Secure Neighbor Discovery Mechanism for Improving Reliable Data Dissemination in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) being an indispensable entity of the Internet of Things (IoT) are found to be more and more widely utilized for the rapid advent of IoT environment. The reliability of data dissemination in the IoT environment completely depends on the secure neighbor discovery mechanism that are utilized for effective and efficient communication among the sensor nodes. Secure neighbor discovery mechanisms that significantly determine trustworthy sensor nodes are essential for maintaining potential connectivity and sustaining reliable data delivery in the energy-constrained self organizing WSN. In this paper, Fuzzy Technique of Order Preference Similarity to the Ideal Solution (TOPSIS)-based Secure Neighbor Discovery Mechanism (FTOPSIS-SNDM) is proposed for estimating the trust of each sensor node in the established routing path for the objective of enhancing reliable data delivery in WSNs. This proposed FTOPSIS-SNDM is proposed as an attempt to integrate the merits of Fuzzy Set Theory (FST) and TOPSIS-based Multi-criteria Decision Making (MCDM) approach, since the discovery of secure neighbors involves the exchange of imprecise data and uncertain behavior of sensor nodes. This secure neighbor is also influenced by the factors of packet forwarding potential, delay, distance from the Base Station (BS) and residual energy, which in turn depends on multiple constraints that could be possibly included into the process of secure neighbor discovery. The simulation investigations of the proposed FTOPSIS-SNDM confirmed its predominance over the benchmarked approaches in terms of throughput, energy consumption, network latency, communication overhead for varying number of genuine and malicious neighboring sensor nodes in network