Trust Based Secure and Energy Efficient Routing Protocol for Wireless Sensor Networks

Hu, Huangshui; Han, Youjia; Yao, Meiqin; Song, Xue

doi:10.1109/access.2021.3075959

Cited by 50 publications

(24 citation statements)

References 38 publications

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“…Therefore, it is important to consider the energy consumption while enhancing the security of the network to avoid rapid energy depletion of the nodes. In this paper, we use a similar energy model as used in [30], [34]. The energy consumed by node i to send s-bits of data to node j at a distance d is as follows:…”

Section: Energy Modelmentioning

confidence: 99%

Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm

Han

Guo

2022

IEEE Access

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Due to their working environments, limited resources and communication characteristics, wireless sensor networks face some challenges including energy optimization and security enhancement to extend the network lifetime and guarantee the network security. Therefore, an energy-aware and trust-based routing protocol for wireless sensor networks using adaptive genetic algorithm called TAGA is proposed to not only resist common routing attacks and special trust attacks, but also minimize the energy consumption caused by data transmission. To this end, TAGA constructs the nodes' comprehensive trust values based on their direct trust values considering the volatilization and adaptive penalty factors, and indirect trust values with the filtering mechanisms. In addition, a novel threshold function is presented to select the optimal cluster heads, which considers the dynamic changes of the nodes' comprehensive trust values and residual energy. Finally, a genetic algorithm with adaptive crossover probability and mutation probability is applied to find the optimal secure routing for the cluster heads. The simulation results show that TAGA can reduce the number of packets discarded by malicious nodes when facing common attacks and special trust attacks, and effectively improve the energy efficiency compared to the relative secure routing protocols EOSR and IASR.INDEX TERMS Wireless sensor networks, secure routing, comprehensive trust, direct trust.

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Section: Energy Modelmentioning

confidence: 99%

Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm

Han

Guo

2022

IEEE Access

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“…Wang et al [ 16 ] proposed a trust evaluation scheme based on mobile edge nodes for IoT. In [ 17 ], the authors propose a routing protocol called trust-based secure and energy (TBSEER) routing protocol to resolve the congestion and serious energy dissipation problems. In this proposal, the nodes calculate the adaptive direct trust value, and the sink nodes take care of indirect trust computation.…”

Section: Related Workmentioning

confidence: 99%

“…In this section, the performance of the proposed TARM is verified in the MATLAB software (8 GB RAM, i7 core CPU Windows 10 system) and is validated with other similar latest trust-based models that employ edge nodes such as ITCM [ 18 ], TBSEER [ 17 ], VFDC [ 10 ], TEC-SFS [ 33 ], and TEM-MEN [ 16 ]. Deployment of the sensor nodes in the network is considered according to Sah et al [ 34 ].…”

Section: Performance Evaluationmentioning

confidence: 99%

Trust-Aware Routing Mechanism through an Edge Node for IoT-Enabled Sensor Networks

Saleh¹,

Joshi²,

Rathore

et al. 2022

Sensors

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Although IoT technology is advanced, wireless systems are prone to faults and attacks. The replaying information about routing in the case of multi-hop routing has led to the problem of identity deception among nodes. The devastating attacks against the routing protocols as well as harsh network conditions make the situation even worse. Although most of the research in the literature aim at making the IoT system more trustworthy and ensuring faultlessness, it is still a challenging task. Motivated by this, the present proposal introduces a trust-aware routing mechanism (TARM), which uses an edge node with mobility feature that can collect data from faultless nodes. The edge node works based on a trust evaluation method, which segregates the faulty and anomalous nodes from normal nodes. In TARM, a modified gray wolf optimization (GWO) is used for forming the clusters out of the deployed sensor nodes. Once the clusters are formed, each cluster’s trust values are calculated, and the edge node starts collecting data only from trustworthy nodes via the respective cluster heads. The artificial bee colony optimization algorithm executes the optimal routing path from the trustworthy nodes to the mobile edge node. The simulations show that the proposed method exhibits around a 58% hike in trustworthiness, ensuring the high security offered by the proposed trust evaluation scheme when validated with other similar approaches. It also shows a detection rate of 96.7% in detecting untrustworthy nodes. Additionally, the accuracy of the proposed method reaches 91.96%, which is recorded to be the highest among the similar latest schemes. The performance of the proposed approach has proved that it has overcome many weaknesses of previous similar techniques with low cost and mitigated complexity.

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“…It is very difficult to provide the trust [47] all over the network in harsh environment. Also, there exist a chance for the attackers to compromise both the network owner [57] and network user which causes conflict of interest during data dissemination.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Trust Aware Secured Lightweight Authentication Protocol for Efficient Reprogramming in Internet of Things

Shanmugapriya

Kumar

2023

Preprint

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Internet of Things (IoT) is the collection of physical things that consist of integrated technologies to interact, sense and collaborate in the deployed environment. Data dissemination is a network management service that is provided to nodes of IoT, where the base station monitors and manages the device related configuration parameter queries and commands in the network. It is very much essential to identify the legitimate nodes which are required for reprogramming and reconfiguring for device configuration during data transmission in order to ensure the security and reliability of the network. Since a greater number of devices are being reprogrammed to exchange data and commands autonomously in IoT, providing security to the disseminated configuration parameters is very important. Therefore, a strong security authentication mechanism is requiring to prevent the various types of attacks against data dissemination. An energy efficient trust based secured lightweight authentication protocol is introduced to suggest better authenticated and secure data dissemination to the devices of IoT. The proposed protocol provides effective clustering and discovers optimal route by selecting the only trusted nodes during data dissemination process. The proposed protocol provides effective clustering and discovers optimal route by selecting the only trusted nodes during data dissemination process. The benefits of the presented system are it improves the security during data dissemination and optimizes the energy by detecting the relevant sensor nodes which are interested in data dissemination. The proposed system is executed in NS3 simulation. The simulation results provide better authentication with optimised energy consumption during the data dissemination in the proposed protocol.

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Trust Based Secure and Energy Efficient Routing Protocol for Wireless Sensor Networks

Cited by 50 publications

References 38 publications

Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm

Energy-Aware and Trust-Based Secure Routing Protocol for Wireless Sensor Networks Using Adaptive Genetic Algorithm

Trust-Aware Routing Mechanism through an Edge Node for IoT-Enabled Sensor Networks

Energy Efficient Trust Aware Secured Lightweight Authentication Protocol for Efficient Reprogramming in Internet of Things

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