Direct Trust Value Research Articles

Trust-aware and improved density peaks clustering algorithm for fast and secure models in wireless sensor networks

Many trust-based models for wireless sensor networks do not account for trust attacks, which are destructive phenomena that undermine the security and reliability of these models. Therefore, a trust-based fast security model fused with an improved density peaks clustering algorithm (TFSM-DPC) is proposed to quickly identify trust attacks in this paper. First, when calculating direct trust values, TFSM-DPC designs the adaptive penalty factors based on the state of received and sent packets and behaviors, and introduces the volatilization factors to reduce the effect of historical trust values. Second, TFSM-DPC improved density peaks clustering (DPC) algorithm to evaluate the trustworthiness of each recommendation value, thus filtering malicious recommendations before calculating the indirect trust values. Moreover, to filter two types of recommendations, the improved DPC algorithm incorporates artificial benchmark data along with trust values recommended by neighbors as input data. Finally, based on the relationship between direct trust and indirect trust, a secure formula for calculate the comprehensive trust is designed. Therefore, the proposed TFSM-DPC can improve the accuracy of trust evaluation and speed up the identification of malicious nodes. Simulation results show that TFSM-DPC can effectively identify on-off, bad-mouth and collusion attacks, and improve the speed of excluding malicious nodes from the network, compared to other trust-based algorithms.

Trust And Energy-Aware Routing Protocol for Wireless Sensor Networks Based on Secure Routing

Wireless Sensor Network (WSN) is a network area that includes a large number of nodes and the ability of wireless transmission. WSNs are frequently employed for vital applications in which security and dependability are of utmost concern. The main objective of the proposed method is to design a WSN to maximize network longevity while minimizing power usage. In a WSN, trust management is employed to encourage node collaboration, which is crucial for achieving dependable transmission. In this research, a novel Trust and Energy Aware Routing Protocol (TEARP) in wireless sensors networks is proposed, which use blockchain technology to maintain the identity of the Sensor Nodes (SNs) and Aggregator Nodes (ANs). The proposed TEARP technique provides a thorough trust value for nodes based on their direct trust values and the filtering mechanisms generate the indirect trust values. Further, an enhanced threshold technique is employed to identify the most appropriate clustering heads based on dynamic changes in the extensive trust values and residual energy of the networks. Lastly, cluster heads should be routed in a secure manner using a Sand Cat Swarm Optimization Algorithm (SCSOA). The proposed method has been evaluated using specific parameters such as Network Lifetime, Residual Energy, Throughpu,t Packet Delivery Ratio, and Detection Accuracy respectively. The proposed TEARP method improves the network lifetime by 39.64%, 33.05%, and 27.16%, compared with Energy-efficient and Secure Routing (ESR), Multi-Objective nature-inspired algorithm based on Shuffled frog-leaping algorithm and Firefly Algorithm (MOSFA) , and Optimal Support Vector Machine (OSVM).

An Efficient and Secure Fog Based Routing Mechanism in IoT Network

The Internet of Things (IoT) networks are the most prone to internal as well as external attacks in addition to energy consumption problems. Conventional security solutions are not able to address these issues effectively due to the limited resources of sensor nodes participating in IoT communications. In this work, an Efficient and Secure Fog Based Routing Mechanism (ESFRM) is proposed to protect the network from faulty internal as well as external attacks. Every node participating in IoT communications calculates the comprehensive trust value of the next intermediate node which is the addition of direct trust, indirect trust and energy trust values before forwarding the data. This comprehensive trust value is then compared with the comprehensive threshold trust value to decide whether the particular node is a rogue node or a valid normal node. Further, an enhanced RSA (Rivest, Shamir, Adleman) algorithm is implemented to provide three levels of data security from Cluster Head (CH) to fog node, from fog node to cloud server and directly from CH to cloud server. For this purpose, an efficient CH selection technique is also proposed in this work. The proposed methodology is compared with the Secure Energy-efficient Fog-based Routing (SEFR) protocol and Trust-aware Secure Routing Protocol (TSRP). The evaluation results show that the proposed ESFRM outperforms the conventional schemes with respect to energy consumption, malicious node detection and transmission rate.

A recommendation management defense mechanism based on trust model in underwater acoustic sensor networks

Underwater acoustic sensor networks (UASNs) have been applied in many civilian and military scenarios, but it is vulnerable to various security threats due to the broadcast transmission characteristics and the environment in which they are located. Trust management mechanism has been proven to be an effect way to improve network security. However, in the trust assessment process, some nodes may provide false suggestions, which will lead to trust conflicts and affect the normal operation of the trust mechanism. To screen out unreliable recommendations and dishonest nodes in the network and avoid potential dangers, a recommendation management trust mechanism based on collaborative filtering and variable weight fuzzy algorithm (CFFTM) is proposed in this paper. First, three kinds of evidence of trust: communication-based evidence, data-based evidence, and energy-based evidence are select as indicators. Then the variable weight fuzzy comprehensive evaluation algorithm is applied to calculate the direct trust value of the node. Secondly, in order to quantify the honesty ability of nodes, honesty degree is defined. Then the overall recommendation trust value of the node is obtained using the proposed collaborative filtering algorithm. The simulation results show that the mechanism can well filter out unreliable recommendations and improve the recognition rate and stability of the trust model under typical attack scenarios.

A Blockchain-Based IoT Terminal Trust Mechanism Management Scheme

Traditional centralized Internet of Things (IoT) management cannot effectively defend against internal attacks from compromised devices due to its own limitations, while distributed IoT node management has certain requirements for the communication environment and resource consumption of the nodes themselves. And the trust authentication of the nodes cannot be easily resolved in a distributed manner. This paper presents a blockchain-based trust management solution. Trust management of nodes based on blockchain also greatly reduces resource consumption. Specifically, the trust value is derived by weighting the historical trust value and the direct trust value, so that the evaluation node does not rely solely on historical trust data to derive its own independent trust evaluation. A separate system node level mechanism exists in the scheme, and the system increases the system node level trust value for the node when this evaluation reaches a trusted level. If this evaluation is malicious, the system node-level trust value for the evaluation is initialized. Security analysis and experiments have shown that this scheme can effectively detect malicious nodes and takes less time.

A Novel Trust Adaptability Approach for Secure Data Transmissions using Enhanced Collaborative Nodes Trustworthiness in Mobile Ad-hoc Networks

Objectives: To find an efficient security routing model based on trust adaptability by considering various transmission parameters that influence the node’s behavior. Methods: Enhanced Collaborative Trust Based Approach (ECTBA) was applied to isolate the malicious nodes from routing by computing their enhanced collaborative trust value based on the node’s behavior using transmission parameters. Parameters that influence the node’s behavior like the number of data packets and control packets forwarded, dropped, or misrouted by the node are quantified to compute direct trust value and neighbor reputation. Node’s Enhanced Collaborative trust value was generated by the combination of direct and neighbor observations. Findings: The proposed strategy is compared with several cases like the Direct Trust Based Approach (DTBA), where routing involves trustworthy nodes categorized based on only direct trust, existing methods like Belief-dependent trust evolution method(BETM), Novel extended trust-dependent method (NETM) where routing is done with nodes that are categorized as trustworthy depending on direct and indirect observations and simple AODV routing performed with all the possible random nodes without any trust detection. The performance parameters of the proposed ECTBA exhibit a success rate of 10.2% in false positives detection (FPD),network throughput of 438.12 Kbps,and packet delivery ratio (PDR) of 92.3%.This method proves to be a better method when compared with the traditional trust-based security methods(BETM and NETM) in terms of efficiency. Novelty: This research suggested a novel and fine-tuned method for quantifying a node’s trustworthiness and for secure routing that coupled the direct and indirect observations into enhanced collaborative trustbased on the node’s behavior by considering the transmission parameters. The present work highlights the combination of data packets forwarding behavior and control packets forwarding behavior in computing enhanced collaborative trust to decide the involvement of intermediate trustworthy nodes’ which is not tried before but this study does. Keywords: Dynamic Topology; Direct Trust; Neighbor Trust; Secure Routing; Enhanced Collaborative Trust

Secure routing for LEO satellite network survivability

Secure routing algorithm plays an important role in the performance of LEO satellite network survivability. However, due to the instability, openness and exposure of inter-satellite links, the internal routing of LEO satellite network is vulnerable to malicious attacks. Considering that trust management has a better performance in solving the internal attacks, this paper proposes a secure routing algorithm based on node trust for LEO satellite network, called SLT. The SLT is based on the distributed trust evaluation model, which is used to calculate the direct trust, indirect trust and aggregate trust value between satellite nodes through D-S evidence theory. Then, combining the low cost OPSPF routing protocol with the trust evaluation, the SLT algorithm is designed. Through timely detection and isolation of malicious nodes in the satellite network, STL algorithm can reduce the impact of malicious packet dropping caused by internal attacks. Finally, the simulations verifies that SLT algorithm has an average increase of 27% in packet delivery rate and an average decrease of 70% in packet loss rate, compared with OPSPF.

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

Due to the characteristics of limited resources and dynamic topology, wireless sensor networks (WSNs) are facing two major problems: security and energy consumption. Nowadays, the trust based solutions are feasible to cope with different bad behaviors of nodes, but there still exist a variety of attacks, high energy consumption and communication congestion between nodes. Therefore, this paper proposes a new trust based secure and energy efficient routing protocol (TBSEER) to solve these problems. TBSEER calculates the comprehensive trust value through adaptive direct trust value, indirect trust value and energy trust value, which can be resistant to black hole, selective forwarding, sinkhole and hello flood attacks. Moreover, the adaptive penalty mechanism and volatilization factor are used to fast identify the malicious nodes. In addition, 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. Finally, the cluster heads find the safest multi-hop routes based on the comprehensive trust value, which can actively avoid wormhole attack. The simulation results show that the proposed TBSEER reduces network energy consumption, speeds up the identification of malicious nodes, as well as resists all common attacks.

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

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.

Performance Analysis of Wireless Sensor Networks Based on Trust Mechanism

Abstract: 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

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.

The Application of Personalized Cloud Service and Grey System Theory in Network Platforms

In order to better practice the purpose of cloud computing to provide users with cheap on-demand services and meet the personalized needs of service requesters, a dynamic trust model for personalized cloud services is proposed. Personalized cloud service is defined based on the idea of fine-grained service. The direct trust value is modified by introducing time decay factor and establishing an efficient incentive mechanism. The evaluation similarity between entities is calculated based on the grey system theory, and the evaluation similarity and the recommender's recommendation credibility are important factors to synthesize the recommendation trust value, At the same time, a method of self-confidence factor assignment based on Evaluation similarity is proposed to improve the accuracy of synthetic trust value. The experimental results show that, compared with GM-Trust model and CCIDTM model, the interaction success rate of this model is increased by 4% and 11% respectively.

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.

Trust‐aware secure routing protocol for wireless sensor networks

A trust-aware secure routing protocol (TSRP) for wireless sensor networks is proposed in this paper to defend against varieties of attacks. First, each node calculates the comprehensive trust values of its neighbors based on direct trust value, indirect trust value, volatilization factor, and residual energy to defend against black hole, selective forwarding, wormhole, hello flood, and sinkhole attacks. Second, any source node that needs to send data forwards a routing request packet to its neighbors in multi-path mode, and this continues until the sink at the end is reached. Finally, the sink finds the optimal path based on the path's comprehensive trust values, transmission distance, and hop count by analyzing the received packets. Simulation results show that TSRP has lower network latency, smaller packet loss rate, and lower average network energy consumption than ad hoc on-demand distance vector routing and trust based secure routing protocol.

Evaluation method of trust degree of distribution IoT terminal equipment based on information entropy

Power distribution Internet of Things terminal equipment is vulnerable to multiple security threats, such as identity disguise, information theft, data tampering. Traditional security methods cannot resist internal network attacks from compromised terminals. The trust evaluation system is an effective mechanism to protect power distribution IoT terminals from internal attacks. This paper proposes a trust evaluation method based on information entropy for the trust problem of power distribution Internet of Things communication terminal. First, the direct trust value is estimated by the model based on the reputation of exponential distribution, and then the direct trust value is updated by the sliding window and forgetting factor. According to the entropy theory, the uncertainty of the direct trust value is measured, and the indirect trust value is introduced to make up for the inaccuracy of the direct trust judgment, and the judgment accuracy is improved through the comprehensive evaluation of the direct trust value and indirect trust value. Experimental simulations show that the method in this paper can effectively resist switch attacks and collusion attacks. At the same time, the method proposed in this paper can better evaluate malicious and normal terminals than binomial trust management and trust evaluation based on beta distribution.

Dynamic Network Security Mechanism Based on Trust Management in Wireless Sensor Networks

Wireless sensor network is a key technology in Internet of Things. However, due to the large number of sensor nodes and limited security capability, aging nodes and malicious nodes increase. In order to detect the untrusted nodes in the network quickly and effectively and ensure the reliable operation of the network, this paper proposes a dynamic network security mechanism. Firstly, the direct trust value of the node is established based on its behavior in the regional information interaction. Then, the comprehensive trust value is calculated according to the trust recommendation value and energy evaluation value of other high‐trust nodes. Finally, node reliability and management nodes are updated periodically. Malicious nodes are detected and isolated according to the credibility to ensure the dynamic, safe, and reliable operation of the network. Simulation results and analysis show that the node trust value calculated by this mechanism can reflect its credibility truly and accurately. In terms of reliable network operation, the mechanism can effectively detect malicious nodes, with higher detection rate, avoid the risk of malicious nodes as management nodes, reduce the energy consumption of nodes, and also play a defensive role in DOS attacks in wireless sensor networks.

A Recommendation Approach for Rating Prediction Based on User Interest and Trust Value.

Collaborative filtering recommendation algorithm is one of the most researched and widely used recommendation algorithms in personalized recommendation systems. Aiming at the problem of data sparsity existing in the traditional collaborative filtering recommendation algorithm, which leads to inaccurate recommendation accuracy and low recommendation efficiency, an improved collaborative filtering algorithm is proposed in this paper. The algorithm is improved in the following three aspects: firstly, considering that the traditional scoring similarity calculation excessively relies on the common scoring items, the Bhattacharyya similarity calculation is introduced into the traditional calculation formula; secondly, the trust weight is added to accurately calculate the direct trust value and the trust transfer mechanism is introduced to calculate the indirect trust value between users; finally, the user similarity and user trust are integrated, and the prediction result is generated by the trust weighting method. Experiments show that the proposed algorithm can effectively improve the prediction accuracy of recommendations.

Trusted Secure Geographic Routing Protocol: outsider attack detection in mobile ad hoc networks by adopting trusted secure geographic routing protocol

PurposeThis study aims to evaluate the direct trust value for each node and calculate the trust value of all nodes satisfying the condition and update the trust value and value each trust update interval for a secure and efficient communication between sender and destination node. Hence, a Trusted Secure Geographic Routing Protocol (TSGRP) has been proposed for detecting attackers (presence of the hacker), considering the trust value for a node produced by combining the location trusted information and the direct trusted information.Design/methodology/approachAmelioration in the research studies related to mobile ad hoc networks (MANETs) and wireless sensor networks has shown greater concern in the presence of malicious nodes, due to which the delivery percentage in any given network can degrade to a larger extent, and hence make the network less reliable and more vulnerable to security.FindingsTSGRP has outperformed the conventional protocols for detecting attacks in MANET. TSGRP is establishing a trust-based secure communication between the sender and destination node. The evaluated direct trust value is used after the transmission of route-request and route-reply packets, to evaluate the direct trust value of each node and a secure path is established between the sender and the destination node. The effectiveness of the proposed TSGRP is evaluated through NS-2 simulation.Originality/valueThe simulation results show the delay of the proposed method is 92% less than PRISM approach and the overhead of the proposed TSGRP approach is 61% less than PRISM approach.

Measuring trust in social networks based on linear uncertainty theory

In social networks, trust relationships are the basis for interactions among decision nodes. Trust relationships are subjective and dynamic, and there are only few sample data to measure the strength of these connections. Uncertainty theory is a mathematical system that studies the belief degree of experts and provides a new method for measuring trust in social networks. In this paper, uncertainty theory is applied to the modeling of social networks. For any feature where certain information cannot be directly obtained, the recommended trust is derived based on direct trust values, and the constraints of single-path trust chains are established. To avoid secondary uncertainties caused by subjective weighting while considering multi-node, multi-path chains, two weighted trust aggregation operators are developed to accomplish a multi-trust transitive aggregation model. The belief degrees of the nodes, the trust chains and the whole network are quantified, and a social network trust measurement model based on uncertainty theory is constructed. In the case of a lack of data on the trust chain, a trust threshold constraint is used to calculate the range of the incomplete chain.

Trust evaluation model with entropy-based weight assignment for malicious node\u2019s detection in wireless sensor networks

Trust management is considered as an effective complementary mechanism to ensure the security of sensor networks. Based on historical behavior, the trust value can be evaluated and applied to estimate the reliability of the node. For the analysis of the possible attack behavior of malicious nodes, we proposed a trust evaluation model with entropy-based weight assignment for malicious node’s detection in wireless sensor networks. To mitigate the malicious attacks such as packet dropping or packet modifications, multidimensional trust indicators are derived from communication between adjacent sensor nodes, and direct and indirect trust values will be estimated based on the corresponding behaviors of those sensor nodes. In order to improve the validity of trust quantification and ensure the objectivity of evaluation, the entropy weight method is applied to determine the proper value of the weight. Finally, the indirect trust value and direct trust value are synthesized to obtain the overall trust. Experimental results show that the proposed scheme performs well in terms of the identification of malicious node.