An emerging intelligent optimization algorithm based on trust sensing model for wireless sensor networks

Yongmei Wang,Wanneng Shu,Min Zhang

doi:10.1186/s13638-018-1174-6

Abstract

Due to the limitation of battery power, processing capacity, and storage, the sensor nodes are easy to be captured, destroyed, or attacked in an open environment. As a result, the security and reliability of data transmission cannot be guaranteed. In order to resist the internal attacks from malicious nodes, an ant colony optimization algorithm for secured routing based on trust sensing model (ACOSR) in wireless sensor networks is proposed. Firstly, a reliable evaluation model of trust perception is presented, which can estimate the node’s trust value derived from its behavior to identify or isolate the malicious nodes effectively. The penalty function and regulator function are applied to reflect the effect of state changes on the trust value according to the node’s behavior in the process of the communication. Secondly, the trust evaluation model is introduced into the ant colony routing algorithm to improve the security for data forwarding. The simulation results show that the proposed algorithm has improved the performance significantly in terms of packet loss rate, end to end delay, throughput, and energy consumption and demonstrates good resistance to black hole attack.

Highlights

The rapid developments of Internet of things (IoT) give impetus to the construction of cloud computing and constantly promote the popularization of applications for social network service and even the smart city [1]
Our model compares with Detecting dishonest recommendation (DDR) (Detecting Dishonest Recommendation) [29] in terms of trust value under the condition of no attack or malicious node’s attack
The comparison of ACOSR, DDR, and Secure and robust clustering (SRC) (Secure and Robust Clustering) [30] algorithm demonstrates in aspects of the average energy consumption, the average time delay, throughput, and the packet loss rate

Summary

Introduction

The rapid developments of Internet of things (IoT) give impetus to the construction of cloud computing and constantly promote the popularization of applications for social network service and even the smart city [1]. 2 Related works To protect the security of the link or constrain the malicious attack within a certain range, researchers have proposed different defense strategies, such as TTSS, SPINS, and INSENS [9,10,11] Those protocols usually adopt the technology of encryption, authentication, or key management mechanism to resist the attacks, including selective forwarding, SYBIL attack, wormhole attack, and HELLO flooding [12, 13]. Hossein et al [19] proposed a distributed trust management system with fuzzy theory to measure the trust value of nodes in WSNs. Yenumula et al [20] examined the behavior of malicious nodes under the attack of selective forwarding and conducted the performance evaluation of the impact quantitatively. The trust value is expressed by floating point number instead of integer value with single byte, which will result in excessive energy consumption between the nodes while passing the recommendation trust

Trust sensing model

Indirect trust value

Results and discussion

Conclusions