Information-Aware Secure Routing in Wireless Sensor Networks

Shi, Qi; Q, Li; Ding, Yinghua; Xie, Boli; Zheng, Jie; Song, Lipeng

doi:10.3390/s20010165

Cited by 30 publications

(32 citation statements)

References 45 publications

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“…Shi et al, 19 suggested a secure routing protocol by considering the trust value and the status of the nodes in the suggested protocol. The attack probability of node was well defined as the trust value and the hybrid metric (Residual energy & Dist.…”

Section: Literature Surveymentioning

confidence: 99%

A trusted distributed routing scheme for wireless sensor networks using blockchain and meta‐heuristics‐based deep learning technique

Revanesh

Sridhar²

2021

Trans Emerging Tel Tech

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The wireless sensor network (WSN) with fluctuating environs might be susceptible to diverse types of malicious cyber‐attacks, and they are mostly dependent on the authentication and encryption algorithm to astound this challenge. Most predominant routing schemes in literature are fall backs in characterizing the malicious nodes on networks due to the real time variation of routing information. Therefore, a reliable and trustworthy inter‐correlated routing scheme based on Block chain, Meta‐heuristic, and Deep Learning Algorithms are presented in this paper. The disseminated routing info in the WSN is handled by Block chain strategy, in which the optimal routing is accomplished with the help of Salp Swarm Optimization algorithm. The routing info variations between the nodes are envisaged and the optimal routing decisions are done by using the Deep Convolutional Neural network algorithm. The proposed routing scheme is implemented in NS2 and its performance is evaluated based on latency, energy consumption, and throughput metrics are analyzed. The efficiency of the method is improved as 97% and the evaluation is done for the malicious attacks, latency, and the delay. The comparison is made for the existing methods as particle swarm optimization, Markov decision process, security disjoint routing‐based verified message, trusted‐cluster–based routing, and reinforcement learning‐based neural network (RLNN) with the proposed method for the delay ratio.

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Section: Literature Surveymentioning

confidence: 99%

A trusted distributed routing scheme for wireless sensor networks using blockchain and meta‐heuristics‐based deep learning technique

Revanesh

Sridhar²

2021

Trans Emerging Tel Tech

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“…Shi [18] developed a Reputation-Based Mechanism to Stimulate Cooperation (RBMSC) mode. The route for data transmission was obtained by the developed protocol.…”

Section: Literature Reviewmentioning

confidence: 99%

Security and Energy Aware Adaptive Routing using Cost Centric Cuckoo Search Algorithm

2021

IJIES

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“…Q Shi et al [27] proposed a new secure routing protocol for WSNs in the presence of malicious nodes. For each relay node in the route, associated information, such as its trust value and status, areconsidered in the protocol.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The review papers [16][17][18][19][20][21][22][23][24][25][26][27][28][29] are not up to the mark. The proposed method in this paper addresses more about the security issues and solved energy consumption, latency and packet delivery ratio problems.…”

Section: Literature Reviewmentioning

confidence: 99%

Grid-Based Routing Model for Energy Efficient and Secure Data Transmission in WSN for Smart Building Applications

et al. 2021

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Presently, due to the establishment of a sensor network, residual buildings in urban areas are being converted into smart buildings. Many sensors are deployed in various buildings to perform different functions, such as water quality monitoring and temperature monitoring. However, the major concern faced in smart building Wireless Sensor Networks (WSNs) is energy depletion and security threats. Many researchers have attempted to solve these issues by various authors in different applications of WSNs. However, limited research has been conducted on smart buildings. Thus, the present research is focused on designing an energy-efficient and secure routing protocol for smart building WSNs. The process in the proposed framework is carried out in two stages. The first stage is the design of the optimal routing protocol based on the grid-clustering approach. In the grid-based model, a grid organizer was selected based on the sailfish optimization algorithm. Subsequently, a fuzzy expert system is used to select the relay node to reach the shortest path for data transmission. The second stage involves designing a trust model for secure data transmission using the two-fish algorithm. A simulation study of the proposed framework was conducted to evaluate its performance. Some metrics, such as the packet delivery ratio, end-end delay, and average residual energy, were calculated for the proposed model. The average residual energy for the proposed framework was 96%, which demonstrates the effectiveness of the proposed routing design.

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Information-Aware Secure Routing in Wireless Sensor Networks

Cited by 30 publications

References 45 publications

A trusted distributed routing scheme for wireless sensor networks using blockchain and meta‐heuristics‐based deep learning technique

A trusted distributed routing scheme for wireless sensor networks using blockchain and meta‐heuristics‐based deep learning technique

Security and Energy Aware Adaptive Routing using Cost Centric Cuckoo Search Algorithm

Grid-Based Routing Model for Energy Efficient and Secure Data Transmission in WSN for Smart Building Applications

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