BLTM: Beta and LQI Based Trust Model for Wireless Sensor Networks

Abstract

To defend against internal attacks in wireless sensor networks (WSNs), building a trust model between sensors nodes has been proved to be an effective way in this paper. The most current trust models only consider communication behavior when calculating direct trust, which is directly calculated based on the interactions between sensor nodes. However, this is not enough because of the various types of attacks. Furthermore, the adverse effect of poor-quality links on the trust value of normal nodes is not discussed in the current trust models. In this paper, we propose a beta and link quality indicator (LQI)-based trust model (BLTM) for the WSNs. First, communication trust, energy trust, and data trust are considered when calculating direct trust. Then, the weight of communication trust, energy trust, and data trust are discussed. Finally, an LQI analysis mechanism is proposed to maintain the accuracy and stability of the trust value of normal nodes in a network with poor-quality links. Compared with other models, e.g., beta-based trust and reputation evaluation system (BTRES), the simulation results show that the BLTM can defend against internal attacks, e.g., DoS attack and data tampering attack which the BTRES cannot resist and can reduce the adverse effect of poor-quality links on the trust value of normal nodes effectively. INDEX TERMS Wireless sensor networks, beta distribution, link quality indicator, trust model.

Conjoint belief adaption functionality for statistically secure communication paradigm for CR‐IIoTs

“…The Trust‐reputation 3‐8 and game‐theory 9‐11 ‐based security frameworks have intrigued great attentions in research key groups. In previous studies, 3,11,12 the authors explore statistical interference in licensed spectrum and then adopt a cooperative game theory approach for allocating spectrum holes to in CR‐environment. Subsequently, they propose a novel routing metric based on energy, trust, and social feature for node selection and data forwarding in their proposed opportunistic routing framework.…”

“…In other studies, 6,15 the authors only acknowledge self‐observations for trust computation, whereas the authors inother works 12,16 use this trust value for guiding the interaction of legitimate node in such a manner that the internal confronts and collusion attacks are countered. Nevertheless, the authors in previous works 3,17 propose a novel approach for immunizing the trust of a legitimate SU by introducing an analyzing module based on the Link Quality Indicators. Nevertheless, the computation of direct trust (from self‐observations) only recognize the data and energy beliefs and totally ignores the energy belief.…”

“…The motivation for CBAF comes from the vital need of a comprehensive security framework for safeguarding the critical infrastructure of CR‐IIoTs deployed in hostile environments for continuous monitoring of assembly lines in the manufacturing industries. State‐of‐the‐art works suggest some basic protocols 1‐9 for countering internal and external threats, but when analyzed meticulously, they lack vital security attributes and are susceptible to adverse effects of substandard channel links. CBAF facilitates a cryptographically secure communication paradigm based on CL‐PKC 1,2 and expedites the computation of absolute belief levels of cognitively active SUs for a statistically stable CSS and an efficient idle spectrum access management.…”

A Novel Trust Model Based on Node Recovery Technique for WSN

“…Trust is the key influence factor of relationships in social networks. Individuals in social networks and sensor nodes in WSN share great similarities [20]. erefore, it is quite natural to evaluate each node's reliability based on both direct and recommendation relationship.…”

“…According to formula (20), the entropy of direct trust degree and indirect trust degree can be obtained by the following formula:…”