Performance Analysis of Wireless Sensor Networks Based on Trust Mechanism

Due to the characteristics like limited resources and dynamic topology, wireless sensor networks (WSNs) are facing two major problems such as security and energy consumption. To deal with various improper behaviors of nodes the trust-based solutions are possible but still exist a variety of attacks, high energy consumption, and communication congestion between nodes. Therefore, this paper proposes an advanced and efficient trust-based secure and energy-efficient routing protocol (TBSEER) to solve these network problems and to avoid malicious nodes. Efficient Adaptable Ant Colony Optimization Algorithm (EAACO) calculates the comprehensive trust value through adaptive direct trust value, indirect trust value, and energy trust value, which can be resistant to internal network attacks such as sinkhole, black hole, selective forwarding, and hello flood attacks. In addition, to fast identify the malicious nodes in the WSN, the adaptive penalty mechanism and volatilization factor are used. Moreover, the nodes only need to calculate the direct trust value, and the indirect trust value is obtained by the sink, so as to further reduce the energy consumption caused by iterative calculations. To actively avoid network attacks, the cluster heads find the safest multi-hop routes based on the comprehensive trust value. The simulation results show that the proposed EAACO reduces network energy consumption, speeds up the identification of malicious nodes, as well as resists all common attacks. Keywords: Comprehensive trust value, direct trust value, indirect value, EAACO, network attacks, wireless sensor networks

A maximizing dominance degree model based on trust relationships and TODIM method to reach group consensus

To obtain the suitable alternative(s) for the organization, this paper proposes a more practical method to solve the decision-making problems in society. That is combined with the TODIM (TOmada de decisão interativa multicrit e ´ rio). The maximizing dominance degree model to reach consensus is proposed with two following components: (1) constructing the complete trust relationships network; (2) the maximizing dominance degree feedback mechanism to reach group consensus. Therefore, firstly owing to the complexity of the trust relationships network, judging the direct and indirect trust propagation paths among the decision makers (DMs) to construct the complete trust relationships network and identifying the highest value of Trust Score (TS) as the leader is possible. Then identify the inconsistent DM based on the established consensus index. During the feedback process, inconsistent DMs adopt the feedback mechanism based on the dominance degree of the leader until the group consensus is reached. Later, the corresponding ranking result is calculated by the TODIM method. Finally, a numerical example is applied to illustrate the effectiveness and feasibility of the optimal model.

A Trust-Based Predictive Model for Mobile Ad Hoc Networks

The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.

Adaptive-Sunflower Based Grey Wolf Algorithm For Multipath Routing In Iot Network

This paper devises a routing method for providing multipath routing inan IoT network. Here the Fractional Artificial Bee colony(FABC)algorithm is devised for initiating clustering process. Moreover the multipath routing is performed by the newly devised optimization technique, namely Adaptive-Sunflower based grey wolf(Adaptive-SFG)optimization technique which is designed by incorporating adaptive idea in Sunflower based grey wolf technique. In addition the fitness function is newly devised by considering certain factors that involves Context awareness, link lifetime Energy, Trust, and Delay.For the computation of the trust, additional trust factors like direct trust indirect trust recent trust and forwarding rate factor is considered. Thus, the proposed Adaptive SFG algorithm selects the multipath for routing based on the fitness function.Finally, route maintenance is performed to ensure routing without link breakage.The proposed Adaptive-SFG outperformed other methods with high energy of0.185Jminimal delay of 0.765sec maximum throughput of47.690%and maximum network lifetime of98.7%.

MANET of an Effective Defence Scheme for Suggestion Based Trust Model

The immovable nature of passing on packages through multi -bounce middle hubs is a critical problem in the versatile impromptu organizations (MANETs). The disseminated versatile hubs set up associations with structure the MANET, which may incorporate childish and getting into mischief hubs. Suggestion based trust the board is proposed in the creating as a system to evaluate through the acting up hubs while looking for a bundle conveyance course. Nonetheless, building a trust model that embraces suggestions by different hubs in the organization is a difficult issue because of the danger of deceptive proposals like reviling, voting form stuffing, and conspiracy. we examines the issues identified with assaults presented by getting rowdy hubs while proliferating suggestions in the current trust models. We propose a suggestion based trust model with a safeguard plot, which uses grouping method to progressively sift through assaults identified with exploitative proposals between certain time dependent on number of collaborations, similarity of data and closeness between the hubs. We evaluate the trust degree as two cases like direct and indirect trust values between neighboring nodes from source. To form a clustering routing network from similar trust values from S to D.The model is experimentally tried under a few portable and detached geographies in which hubs experience changes in their local prompting regular course changes. The observational investigation shows heartiness and exactness of the trust model in a dynamic MANET climate.

Continuous Trust Evaluation of Power Equipment and Users Based on Risk Measurement

In power Internet of Things environment, the existing border-based protection system and the “one-time authentication, one-time authorization, and long-term effective” approach are difficult to deal with the threat of attacks from internal and external devices and users with legal authority. In order to solve the problem of authorized access of power equipment and users, combined with behavior risk assessment, a continuous trust evaluation scheme of power equipment and users is presented in this paper. The scheme is evaluated by the combination of direct trust, indirect trust, and comprehensive trust and adds the penalty reward factor and time attenuation function to improve the reliability of the results. In addition, this paper will quantify the risk of the behavior of power equipment and users and regard it as a factor affecting the degree of trust, so as to achieve continuous trust evaluation of equipment and users.

Robust and Accurate Trust Establishment Scheme for Wireless Sensor Network

The success of the mission assigned to a Wireless Sensor Network (WSN) depends heavily on the cooperation between the nodes of this network. Indeed, given the vulnerability of wireless sensor networks to attack, some entities may engage in malicious behavior aimed at undermining the proper functioning of the network. As a result, the selection of reliable nodes for task execution becomes a necessity for the network. To improve the cooperation and security of wireless sensor networks, the use of Trust Management Systems (TMS) is increasingly recommended due to their low resource consumption. The various existing trust management systems differ in their methods of estimating trust value. The existing ones are very rigid and not very accurate. In this paper, we propose a robust and accurate method (RATES) to compute direct and indirect trust between the network nodes. In RATES model, to compute the direct trust, we improve the Bayesian formula by applying the chaining of trust values, a local reward, a local penalty and a flexible global penalty based on the variation of successful interactions, failures and misbehaviors frequency. RATES thus manages to obtain a direct trust value that is accurate and representative of the node behavior in the network. In addition, we introduce the establishment of a simple confidence interval to filter out biased recommendations sent by malicious nodes to disrupt the estimation of a node's indirect trust. Mathematical theoretical analysis and evaluation of the simulation results show the best performance of our approach for detecting on-off attacks, bad-mouthing attacks and persistent attacks compared to the other existing approaches.

Combining Direct Trust and Indirect Trust in Multi-Agent Systems

To assess the trustworthiness of an agent in a multi-agent system, one often combines two types of trust information: direct trust information derived from one's own interactions with that agent, and indirect trust information based on advice from other agents. This paper provides the first systematic study on when it is beneficial to combine these two types of trust as opposed to relying on only one of them. Our large-scale experimental study shows that strong methods for computing indirect trust make direct trust redundant in a surprisingly wide variety of scenarios. Further, a new method for the combination of the two trust types is proposed that, in the remaining scenarios, outperforms the ones known from the literature.

Trusted Location Selection in Vehicular ad-hoc Network

VANET gives the advantage to enhance road safety and assure less or no traffic accidents. However, false messages can result in serious conditions like collision. This paper proposed a new, trust based technique for location selection in VANET. In the paper presents a trust based location selection scheme has two phases computation of direct and indirect trust. However, evaluation of direct trust system using infrastructure (RSU) and trusted authority (TA) and evaluation of indirect trust uses watchdog approach. Results show that the proposed scheme suitable for the actual situation of VANET.