Trust Evaluation Techniques Research Articles

Trust Evaluation Techniques for 6G Networks: A Comprehensive Survey with Fuzzy Algorithm Approach

Sixth-generation (6G) networks are poised to support an array of advanced technologies and promising high-quality and secure services. However, ensuring robust security, privacy protection, operational efficiency, and superior service delivery poses significant challenges. In this context, trust emerges as a foundational element that is critical for addressing the multifaceted challenges inherent in 6G networks. This review article comprehensively examines trust concepts, methodologies, and techniques that are vital for establishing and maintaining a secure and reliable 6G ecosystem. Beginning with an overview of the trust problem in 6G networks, this study underscores their pivotal role in navigating the network’s complexities. It proceeds to explore the conceptual frameworks underpinning trust and discuss various trust models tailored to the unique demands of 6G networks. Moreover, this article surveys a range of scholarly works presenting diverse techniques for evaluating trust by using the fuzzy logic algorithm, which is essential for ensuring the integrity and resilience of 6G networks. Through a meticulous analysis of these techniques, this study elucidates their technical nuances, advantages, and limitations. By offering a comprehensive assessment of trust evaluation methodologies, this review facilitates informed decision making in the design and implementation of secure and trustworthy 6G networks.

MarketTrust: blockchain-based trust evaluation model for SIoT-based smart marketplaces

Due to the significance of trust in Social Internet of Things (SIoT)-based smart marketplaces, several research have focused on trust-related challenges. Trust is necessary for a smooth connection, secure systems, and dependable services during trade operations. Recent SIoT-based trust assessment approaches attempt to solve smart marketplace trust evaluation difficulties by using a variety of direct and indirect trust evaluation techniques and other local trust rating procedures. Nevertheless, these methodologies render trust assessment very sensitive to seller dishonesty, and a dishonest seller may influence local trust scores and at the same time pose a significant trust related threats in the system. In this article, a MarketTrust model is introduced, which is a blockchain-based method for assessing trust in an IoT-based smart marketplace. It has three parts: familiarity, personal interactions, and public perception. A conceptual model, assessment technique, and a global trust evaluation system for merging the three components of a trust value are presented and discussed. Several experiments were conducted to assess the model's security, viability, and efficacy. According to results, the MarketTrust model scored a 21.99% higher trust score and a 47.698% lower average latency than both benchmark models. Therefore, this illustrates that using the proposed framework, a potential buyer can efficiently choose a competent and trustworthy resource seller in a smart marketplace and significantly reduce malicious behavior.

ARPVP: Attack Resilient Position-Based VANET Protocol Using Ant Colony Optimization

The position-based routing of Vehicular Ad hoc Network (VANET) vulnerable to various security attacks because of dependency on computing, control, and communication technologies. The Internet of Things (IoT)-enabled VANET application leads to the challenges such as integrity, access control, availability, privacy protection, non-repudiation, and confidentiality. Several security solutions have been introduced for two decades in two categories as cryptography-based and trust-based. Due to the high computation complexity, cryptography-based solutions are outperformed by recent intelligent trust-based mechanisms. The trust-based techniques are lightweight and effective against the well-known security threats in VANET. The objective of this paper has to design a novel position-based routing in which the conduct of vehicles assessed to accomplish reliable VANET communications. Attack Resilient Position-based VANET Protocol (ARPVP) proposed to detect and prevent malicious vehicles in the network using the trust evaluation technique and artificial intelligence (AI). In the first phase of ARPVP, the periodic self-trust assessment algorithm has designed using various trust parameters to detect unreliable vehicles in the network. In the second phase of ARPVP, the position-based route formation algorithm has designed using the AI technique Ant Colony Optimization (ACO). ACO solves the problem of reliable route formation by neglecting the attacker's using a trust-based fitness function. The trust parameters of each vehicle as mobility, buffer occupancy, and link quality parameters had measured in both phases of ARPVP. Simulation outcomes of the proposed model outperformed state-of-art protocols in terms of average throughput, communication delay, overhead, and Packet Delivery Ratio (PDR).

A Novel Multifaceted Trust Management Framework for Vehicular Networks

Maintaining interconnectivity between dynamic vehicular nodes and ensuring trust in vehicular networking is still a challenging issue. It is crucial for the vehicular environments to maintain a stable interconnectivity between the vehicular nodes and further to prevent the vehicular nodes from broadcasting fake messages and simultaneously protect the vehicles against tracking attacks. An efficient Trust Management System (TMS) is proposed in this paper that will ensure trustworthiness and stable interconnectivity between vehicular entities to assure road safety and reliable communication. The proposed approach incorporates a novel timestamp mechanism and block chain concepts to ensure the steady inter-connectivity between the dynamic vehicular nodes. Further, the framework leverages block chain concepts to verify the correctness of the events stored in the Road Side Units (RSUs). It also proposes a versatile hybrid trust model that uses innovative direct and recommended trust evaluation techniques to compute trust between the vehicular entities. Moreover, the framework integrates a threading mechanism to schedule message execution in direct trust evaluation, and clustering techniques to group similar messages in indirect trust evaluation. Various experimental and comparative analyses with other related studies are carried out in a simulated environment to evaluate the performance of the proposed hybrid trust model. The findings show that the proposed trust model produces an accuracy of 92% in identifying malicious nodes.

Peer-to-peer trust management in intelligent transportation system: An Aumann’s agreement theorem based approach

Vehicular ad hoc network (VANETs) has gained wide popularity such that it is necessary to incorporate trust among each node in the network. However, trust management among vehicles is a challenging task as malicious nodes are prone to disturb data transmission among different vehicles. The aim of this work is to establish the truth of consensus, to identify the malicious nodes with no further delay, by considering the decision of each vehicle on finding the trust values. The experimental analysis for the proposed approach done using the NS3 with CAIDA data set, the proposed scheme shows superior results compared to the other existing schemes for the detection rate of malicious nodes. It enhances the attack Detection Rate (DR) as 96.5% for the projected dual weighted trust evaluation technique. But, DR for the triumphing technique firecol is 74.9% and AODV is 60%. Thus, it is experimentally proved that dual weighted trust mechanism has high attack detection rate, comparatively. Also, proposed method outperforms very well with respect to the data transmission parameters like packet delivery ratio, energy Consumption and average latency comparatively over the existing mechanisms.

An improved trust-based security framework for internet of things

The Internet plays a vital role in the massive growth of the emerging Internet of Things (IoT). IoT helps all electronic devices to communicate with other devices and with the human with the help of the Internet. IoT enables the devices to sense environmental changes or mission-critical data. These critical data that are sensed by the IoT devices are forwarded to the public cloud storage with the help of Gateway nodes. Later these sensed data are utilized for decision making. However, high-risk insecurity is a major concern in IoT sensed data. In this paper, a trust-based security method with Direct and Indirect trust evaluation technique has been implemented to provide highly secure data transmission in the network. The simulation result has proven that trust-based security can improve data confidentiality when compared with available protocols.

Blockchain and Trust for Secure, End-User-Based and Decentralized IoT Service Provision

Building trust relationships between different decentralized entities in the IoT ecosystem is essential. Hereof, the combination of blockchain technology and trust evaluation techniques is recently considered as an efficient measure. However, both technologies within the IoT are still facing some limitations which are addressed in this research. First, this publication reviews various blockchain-based trust approaches and depicts their strengths and limitations regarding their usage in decentralized IoT communities. Then, an optimized trust model with a multi-layer adaptive and trust-based weighting system is proposed. Additionally, different trust metric parameters and their mathematical models used for trust evaluation are presented. Moreover, this publication presents a novel approach for incentivization processes in the IoT marketplace using control loops and smart contracts. Thereby, participants are motivated to continuously improve their behavior. Finally, the proposed trust model is proved to be reliable. The experimental results conducted from different scenarios show that the presented approach provides more resiliency against various attacks than existing ones.

A study on hybrid trust evaluation model for identifying malicious behavior in mobile P2P

P2P network has been widely used because of advantages such as efficient use of network bandwidth, saving of computing resources, and quick information exchange. In particular, the infra that manages each nodes centrally in P2P network does not exist and each node is a structure performing the sender and receiver roles. The service applying P2P technique in MANET is increased because this structure is very similar to the structure of MANET. However, the reliability may be lower by providing an erroneous service from malicious nodes because the supervision of management for nodes participating in P2P does not perform. In this paper, we propose hybrid trust evaluation technique based on Trust Zone structure to improve the reliability between nodes. TZM node is elected for trust evaluation of member nodes internal each TrustZone. The certificate of member nodes is issued in the elected TZM and the information is stored in TZMT. The data transmission of malicious nodes is blocked by limiting the data transmission of nodes that do not issued the certificate. The reputation-based trust management technique was applied to perform the fair file transmission of nodes and block the behavior of selfish nodes. The excellent performance of the proposed technique in this paper was confirmed through experiments.

A Policy and Trust-based Secure Communication Protocol in Information Systems

end users have become more responsive of securely sharing or exchanging the vast amount of information. The organizations that do sensitive work such as those with defense contracts, passport issuing agencies, military activities, and health care data at health-insurance, are in need of protecting their information. Nowadays, financial institutions providing various online services to customers are facing situation with customers who submit fake documents for getting services. To defend from that situation, financial institutions enquire customer information at various government departments against the customer submitted proof documents to rovide service to customer. In this study, secure and trusted information sharing environment is a vital requirement to make users interact and share data easily and securely across various networks. The prime challenge is to evaluate the trust of financial institution that characterizes secure information sharing in various government departments. The secondary challenge would be a development of communication protocol that securely exchanges information among various financial institutions and various government organizations. This paper emphasis on policy and trust-based secure protocol that offers confidential and authenticated, and trusted information sharing among financial institutions and government departments without creating any problems to information security by using cryptographic hash, private and public key encryption algorithms, and trust evaluation techniques. Furthermore, it facilitates non-privacy preserving information sharing with probable restrictions based on the rate of trust factor of financial institutions. This protocol assures that secure and stream- lined information sharing among financial institutions and government departments leads to avoid intimidating activities. The experimental results show the effectiveness of the proposed policy and trust-based information sharing approach.

Multi-level delegations with trust management in access control systems

Delegation is a mechanism that allows one agent to act on another’s privilege. It is important that the privileges should be delegated to a person who is trustworthy. In this paper, we propose a multi-level delegation model with trust management in access control systems. We organize the delegation tasks into three levels, Low, Medium, and High, according to the sensitivity of the information contained in the delegation tasks. It motivates us that the more sensitive the delegated task is, the more trustworthy the delegatee should be. In order to assess how trustworthy a delegatee is, we devise trust evaluation techniques to describe a delegatee’s trust history and also predict the future trend of trust. In our proposed delegation model, a delegatee with a higher trust level could be assigned with a higher level delegation task. Extensive experiments show that our proposed multi-level delegation model is effective in accurately predicting trust and avoiding sensitive information disclosure.