Trust Management Method Research Articles

Blockchain Enabled Trust-Based Location Privacy Protection Scheme in VANET

While enjoying the convenience brought by Location Based Service (LBS), the location privacy of vehicles in VANET may be disclosed. Distributed k -anonymity, as one of the most popular privacy protection methods, fails to take the trustworthiness of participants into account, resulting in malicious tracing of vehicles, which further leads to the sensitive information leakage, and even the safety threat of personal property. To address this issue, we propose a blockchain enabled trust-based location privacy protection scheme in VANET. Specifically, by analyzing the different requirements of the request vehicle and the cooperative vehicle during the process of constructing the anonymous cloaking region, as well as combining the characteristics of these two roles, we devise the trust management method based on Dirichlet distribution , such that both the requester and the cooperator will only cooperate with the vehicles they trust. Moreover, by employing blockchain, we also proposed the data structure to record the trustworthiness of vehicles on publicly available blocks timely, so that any vehicle can access the historical trust information of counterparties whenever necessary. Finally, the construction process of anonymous cloaking region is presented. Security analysis and extensive experiments indicate that the proposal is resilient to various trust model attacks, it can effectively detect the malicious vehicles, and preserve the location privacy of vehicles in the anonymous cloaking region construction, while the required time delay is limited.

Application of Grey Relation Analysis Theory to Choose High Reliability of the Network Node

The research on resource sharing network safety problem mainly refers to the concept of trust management in distributed systems, and uses trust management method to realize secure access to shared services and data, etc. This paper describes the method of the grey correlation analysis theory that is used to calculate a reliable resource node trust value, and applies it in the access nodes feedback recommendation algorithm to adjust the recommended resource node trust value. The simulation results show that the method can obviously improve the success rate of resource searching.

Trust Based Routing Algorithm to Improve Quality of Service in DSR Protocol

Wireless sensor networks involve low power fixed and mobile nodes with limited energy resources. Lack of resources such as energy and bandwidth, could reduce cooperation between nodes that may lead to lower quality of service parameters. Lack of cooperation would result in not forwarding incoming packets by each node to save its remaining energy. Also, due to inherent characteristics of wireless sensor networks, they are vulnerable to be attacked by malicious or selfish nodes. Trust management methods can be used to deal with such problems by designing a routing protocol that is based on trust and can improve quality of service parameters. In this paper, we utilize a trust management system and provide a method to reduce energy consumption and improve quality of service parameters. We improved packet delivery ratio and the amount of remaining energy in Dynamic Source Routing protocol, while maintaining the end to end delay.

Secure Content Delivery With Edge Nodes to Save Caching Resources for Mobile Users in Green Cities

To save energy during content delivery in green cities, caching contents on edge nodes that are placed near mobile social users has been advocated recently. However, how to allocate the limited caching resources with secure content delivery becomes a new challenge. Therefore, in this paper, we present a novel theoretical model to deliver secure content with edge nodes in order to save energy for green cities. First, we present a reverse auction game to encourage edge nodes to cooperatively provide caching services with incentives. With the model, mobile users can determine the candidate of edge node to cache content based on the interaction between mobile users and edge nodes. Second, a trust management method is designed to evaluate the reliability of the selected candidate of edge node by considering the direct trust evaluation. Finally, extensive simulations show that the proposal can save energy with a secure content delivery where both the delay to obtain the content and the caching ratio can be improved compared with the conventional methods.

A Customer-Centric Trust Evaluation Model for Personalized Service Selection

Trust is a very important criterion when service customers select desired Web services from a cluster of Web services with the same function. Most existing trust models cannot effectively implement personalized service selection with regard to consumer preferences and expectations. This paper designs a novel trust management method based on peer-to-peer network and presents a customer-centric trust evaluation model for personalized service selection. The trust evaluation model firstly maintains consumer-to-consumer trust values that are calculated according to preference similarity between customers, secondly gathers ratings on services submitted by other consumers, then synthesizes customer-to-customer trust and these ratings to generate personalized consumer-to-service trust, and finally selects the desired services according to the expected trust levels presented by customers. This paper conducts some experiments to demonstrate the details of service selection. Experimental results show that this model has good applicability to implement personalized service selection. The proposed model well simulates the reality.

Trust Management Method of D2D Communication Based on RF Fingerprint Identification

iWith the rapid development and the increasing security threats of D2D communication, the D2D communication security has become more and more important. Device recognition is the foundation of communication security. Traditional device authentication is the cryptographic mechanism and the security protocol that are not enough for the new security threat. RF fingerprint of wireless device has physical characteristics, which is difficult to clone. Therefore, it can be used for D2D device recognition. In this paper, a recognition algorithm of D2D device based on RF fingerprint is proposed. First, Hilbert transform and principal component analysis is used to generate the RF fingerprint of D2D device. Second, support vector machine (SVM) is introduced and CV-SVM is used as the classifier. Finally, simulation results show that the recognition rate is more than 90% under SNR = 5 dB, which proves that the proposed method is effective for D2D device recognition. Therefore, it can be used as the trust management of D2D communication.

A Smart Trust Management Method to Detect On-Off Attacks in the Internet of Things

Internet of Things (IoT) resources cooperate with themselves for requesting and providing services. In heterogeneous and complex environments, those resources must trust each other. On-Off attacks threaten the IoT trust security through nodes performing good and bad behaviors randomly, to avoid being rated as a menace. Some countermeasures demand prior levels of trust knowledge and time to classify a node behavior. In some cases, a malfunctioning node can be mismatched as an attacker. In this paper, we introduce a smart trust management method, based on machine learning and an elastic slide window technique that automatically assesses the IoT resource trust, evaluating service provider attributes. In simulated and real-world data, this method was able to identify On-Off attackers and fault nodes with a precision up to 96% and low time consumption.

A Mutual Evaluation Based Trust Management Method for Wireless Sensor Networks

We propose a lightweight trust system for the clustered wireless sensor networks based on the mutual evaluation between the cluster heads and sensor nodes. We evaluate the trust level of a cluster head in two aspects, namely, trust level as a service provider and a supervisor. We consider multidimensional trust attributes to compute the global trust value of a node. By means of the Petri net (PN), we illustrate the performance of an entity in our trust model. Theoretical analyses as well as simulations are done and the results showed that our model with linear computational complexity had less memory and communication overhead when compared with the current state-of-art trust management scheme. In addition, our model can detect malicious and selfish entities (especially the malicious cluster head) and resist various attacks efficiently.

A Novel Trust Management Method based on Information Visualization for Cloud Computing

A Novel Trust Management Method based on Information Visualization for Cloud Computing

Trust evaluation method for clustered wireless sensor networks based on cloud model

Trust Management has been proved to be an effective method to detect malicious nodes and ensure security in Wireless Sensor Networks (WSNs). While, most existing trust management methods are not good at dealing with uncertainty of trust relationship such as randomness, fuzziness in WSNs, which leads to inaccurate trust metric. In this paper, a trust evaluation method for clustered wireless sensor networks based on cloud model is proposed and evaluated, which implements the conversion between qualitative and quantitative of sensor nodes’ trust metrics in order to achieve better trust evaluation. Firstly, the method considers multi-factors including communication factor, message factor and energy factor and builds mathematical model for each trust factor to get factor trust cloud. Secondly, immediate trust cloud is calculated by assigning adjustive weights for each factor trust cloud and combining them. Thirdly, recommendation trust cloud and immediate trust cloud are synthesized according to time sensitive factor in order to get final trust cloud. Furthermore, the final trust cloud of sensor node is converted to trust grade by trust cloud decision-making. Verification Experiments manifest that the proposed method has feasibility and accuracy in the aspect of evaluating sensor nodes’ trust. Moreover, comparison experiments under different attacks show that our method is sensitive to multiple attacks, it outperforms other trust evaluation methods not only in the accuracy of detecting malicious nodes, but also in the tolerance of abnormal conditions.

Improved trust management based on the strength of ties for secure data aggregation in wireless sensor networks

Secure data aggregation exerts more and more important effects on the research of wireless sensor network. There occurs many groping research subject, via managing nodes' trust and reputation to keep data aggregation secure. The nodes in wireless sensor networks are often compromised and those compromised nodes will do a lot of harmful behaviors to decrease the security of wireless sensor networks. These behaviors include impersonate legal nodes to join routing paths, selectively forward data to an adversary, inject erroneous data, and disrupt data transmission. Thus, the conception of nodes' trust is introduced into data aggregation to judge and evaluate whether the nodes are trustable or not. In this paper, we propose an improved trust management method for data aggregation based on the relationship between nodes that is called the strength of the ties between the nodes. The improved method is developed from the trust model in the iRTEDA protocol and increasing the utilization efficiency of second-hand information coming from neighboring nodes. The aim of the proposed trust model is to obtain a higher level of security for data aggregation. The simulation results show us that data aggregation, based on proposed trust management method, can get higher accuracy of evaluating nodes' trust and reputation and achieve higher data accuracy of aggregating.

Analysis of Trust Issues Based on Evolutionary Game in Cloud Computing

With the development of cloud computing, a number of cloud security issues have emerged. This paper firstly introduce the cloud computing and security risks briefly, then use game theory to analyze strategies between cloud service providers and that between providers and users, finally, put forward the improved methods for trust management.

QUALITATIVE ASSESSMENT DYNAMICS — COMPLEMENTING TRUST METHODS FOR DECISION MAKING

Trust is not only one key ingredient of prosperous organizations and societies, but also an essential factor in decision-making processes. And when it comes to trust, the latest advances in computing sciences area are increasingly supporting the related processes by deployment of so-called trust management systems. These systems are slowly advancing from their early stages of evolution toward more sophisticated and already operationally deployable solutions. As there seems to be no "Swiss-army knife" like methodology for trust management, it is reasonable to assume that not only one, but a few of them will be deployed in the future, depending on their basic principles of functioning,purposes and contexts of use. Therefore there still exists a gap in this area with unaddressed issues where humans (or humans-like agents) would be in focus. Quality Assessment Dynamics, QAD, which is presented in this paper, is taking these issues into account. It is based on operands and operators that model human ways of reasoning as described in many natural languages. Further, it is a formal system and therefore enabled for deployment in computing environments. This way QAD complements existing trust management methods and provides additional means for decision making through deployment in simulations and in trust management engines, while being understandable to ordinary users without requiring sophisticated expert knowledge.

Computational Trust Management, QAD, and Its Applications

Trust is an important factor for successful e-commerce and e-media applications. However, these media inherently disable many ordinary communication channels and means, and affect trust forming factors. Therefore cyber environment requires additional support when it comes to trust. This is also one key reason why computational trust management methods are being developed now for some fifteen years, while another key reason is to enable better decision making through mathematical modeling and simulations in other areas. These methods are grounded on certain premises, which are analyzed in this paper. On this basis, Qualitative assessment dynamics (QAD for short) is presented that complements the above methods. As opposed to other methods, it is aligned with certain principles of human reasoning. Therefore it further extends the scope of other computational trust management technologies that are typically concerned with artificial ways of reasoning, while QAD gives a basis also for applications in ordinary environments where humans are involved. By using this methodology, experimental work will be presented, applied to the area of organizations and human factor management.

Hard and soft security provisioning for computationally weak pervasive computing systems in E-health

We are witnessing increasing penetration of pervasive computing into business and personal environments. Its advances, among other things, enable new opportunities for better health services but, as a side effect, it introduces new threats to privacy. If anywhere, it is in the health care sector that privacy is of utmost importance. Knowing further that internet of things devices typically lack computing and energy resources, the need for providing appropriate privacy is a hard issue. This paper therefore addresses privacy for internet of things technologies by focusing on the most "primitive" members, bare sensors and RFIDs. Based on lessons learned in this domain, a strategy of incrementally adjusting existing protocols is adopted for deployment in the area of wireless medical sensors body area networks. By doing so, new contributions that are quantifiably lightweight and that enable privacy, together with confidential exchange of captured measured quantities, are provided. In addition to such hard security solutions, the paper addresses trust management methods as a complementary, soft mean for security provisioning. This latter contribution also paves the way for further development and for applications of pervasive computing in general.

ReTrust: Attack-Resistant and Lightweight Trust Management for Medical Sensor Networks

Wireless medical sensor networks (MSNs) enable ubiquitous health monitoring of users during their everyday lives, at health sites, without restricting their freedom. Establishing trust among distributed network entities has been recognized as a powerful tool to improve the security and performance of distributed networks such as mobile ad hoc networks and sensor networks. However, most existing trust systems are not well suited for MSNs due to the unique operational and security requirements of MSNs. Moreover, similar to most security schemes, trust management methods themselves can be vulnerable to attacks. Unfortunately, this issue is often ignored in existing trust systems. In this paper, we identify the security and performance challenges facing a sensor network for wireless medical monitoring and suggest it should follow a two-tier architecture. Based on such an architecture, we develop an attack-resistant and lightweight trust management scheme named ReTrust. This paper also reports the experimental results of the Collection Tree Protocol using our proposed system in a network of TelosB motes, which show that ReTrust not only can efficiently detect malicious/faulty behaviors, but can also significantly improve the network performance in practice.

Trust and Publishing Management for Streaming MediaServices

recently, networks are extended in multi-domains with scalabilities. The streaming media services require the dynamic trust management and maintain systems in multi-domains. This paper proposes a trust and publishing management method for streaming media services. The method dynamically maintains trust links for streaming media servers, applications and mobile nodes. It also integrates reputation authentication, forwarded authentication, streaming media publishing, and streaming media evaluation in one system, and improves the performance of trust, reliability and media publishing.

Adaptive trust management framework in P2P grid computing

In P2P Grid computing systems, the authorization decision is often tackled by two different trust management methods: policy-based approach, where authorization are built on logical rules and verifiable properties encoded in signed credentials, and reputation-based approach, based on collecting, aggregating and disseminating reputation among the peers. However, the overhead caused by proof of compliance on authorization and the absence of certifying authorities may negate the strong and objective security advantages of policy-based approach, whilst vagueness, complexity and inaccurate characterization caused by reputation evolution may eliminate the quantitative and flexible advantages of reputation-based approach. We propose an adaptive trust management framework, which combines the merit of policy proof and reputation evolution such that authorization is aware of not only the strong and objective security traits, but also the calculability and the availability security traits. Finally, the framework of system is proposed.