Abstract

How to improve both security and energy efficiency is one of the most prominent issues in wireless sensor networks (WSNs). In this paper, we present a trusted and energy efficient approach for cluster-based WSNs. The approach offers (i) trusted hardware module design; (ii) energy-efficient clustering algorithm; and (iii) network operation. In the cluster-based WSNs, every cluster head is equipped with a designed trusted hardware module (TM) to improve security. Then, for improving the energy efficiency of the network, a trusted hardware based energy efficient clustering (TEEC) algorithm is proposed to select appropriate cluster heads. In the network operation, we use TEEC algorithm to perform clustering and apply TMs to achieve security functions. The analysis shows that our approach does well in resisting the attacks such as data confidentiality attack, data integrity attack, and compromise node attack. In addition, experimental results show that the TEEC algorithm makes more balanced clusters with the variance value of loads around 50% and prolongs the life cycle of the network at least 10% compared to traditional methods.

Highlights

  • Wireless sensor networks (WSNs) have been applied to a variety of applications, such as healthcare, smart home, agriculture, and military

  • The clustering is based on residual energy of the cluster head and distance from sensor nodes to their corresponding cluster head

  • The sensor nodes are randomly distributed in the network areas

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Summary

Introduction

Wireless sensor networks (WSNs) have been applied to a variety of applications, such as healthcare, smart home, agriculture, and military. Software-based methods [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18] are easy to be attacked when there are some compromised nodes To solve this problem, trusted computing [19] has been adopted to detect the attacked nodes in WSNs. The main idea of trusted computing is to establish a trusted root to ensure integrity and security of the system. We propose a trusted and energy efficient approach for cluster-based WSNs. We first design.

Related Work
Preliminaries
Trusted and Energy Efficient Approach
Result
Approach Evaluation
Conclusion
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