Static and Dynamic Structure Characteristics of a Trust Network and Formation of User Trust in an Online Society

This study investigated the characteristics and formation of the online social trust network of Epinions.com, a general consumer review site. An analysis of the static structure of this social trust network revealed a high clustering coefficient, short average path length, and power-law degree distribution;it is therefore a small-world and scale-free trust network. The dynamic evolutionary characteristics of the online social network (OSN) were also examined. The results showed that the scale of the network followed a sigmoidal curve;the average degree of the network was nonconstant and changed into a bell-shaped distribution;the density of the network decreased and subsequently stabilized;and user trust diffusion in the network conformed to the Bass model. Finally, the formation of trust within the network was researched at the overall network (macro) and individual user (micro) levels. Compared with their accumulated contribution and reputation, user activeness had a larger effect on trust formation in OSNs, indicating a “diminishing returns” phenomenon. This phenomenon contrasts with the Matthew effect (i.e. , the more reputation a person has, the more likely he or she is to be trusted) in real-world social networks.

Building trust networks in the absence of trust relations

User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media platforms.These issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.

Behavior Measurement Model Based on Prediction and Control of Trusted Network

In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation,individual similarity function,group similarity function,direct trust assessment function,and generalized predictive control,this model can guarantee the trust of an end user and users in its network.Compared with traditional measurement model,the model considers different characteristics of various networks.The trusted measurement policies established according to different network environments have better adaptability.By constructing trusted group,the threats to trusted group will be reduced greatly.Utilizing trusted group to restrict individuals in network can ensure the fault tolerance of trustworthiness of trusted individuals and group.The simulation shows that this scheme can support behavior measurement more efficiently than traditional ones and the model resists viruses and Trojans more efficiently than older ones.

A Trusted Measurement Scheme Suitable for the Clients in the Trusted Network

The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network.But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection,it is easy to cause the loss of identity privacy.In order to solve the abovedescribed problems,this paper presents a trust measurement scheme suitable for clients in the trusted network,the scheme integrates the following attributes such as authentication mechanism,state measurement,and real-time state measurement and so on,and based on the authentication mechanism and the initial state measurement,the scheme uses the realtime state measurement as the core method to complete the trust measurement for the client.This scheme presented in this paper supports both static and dynamic measurements.Overall,the characteristics of this scheme such as fine granularity,dynamic,real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.

A Jury-Based Trust Management Mechanism in Distributed Cognitive Radio Networks

In the trust management scheme of the distributed cognitive radio networks, the absence of the central control devices cause many problems such as a lack of standardized control for trust computation, and the absence of the decision makers in trust evaluation and collaborative decision making. A trust management mechanism based on the jury system for distributed cognitive radio networks is proposed in this paper. The "jury user" is designed to collaboratively examine the reputation of the cognitive user in the networks and to perform data fusion and spectrum allocation for distributed cognitive radio networks. Simulation analysis results show that the proposed scheme can ensure accuracy and fairness in trust evaluation and improve effectiveness and flexibility of spectrum allocation.

Development of Trusted Network and Challenges It Faces

As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development requirements. Offering the system with secure and trusted services has become a new focus in network research. This paper first discusses the meaning of and aspects involved in the trusted network. According to this paper, the trusted network should be a network where the network’s and users’ behaviors and their results are always predicted and manageable. The trustworthiness of a network mainly involves three aspects: service provider, information transmission and terminal user. This paper also analyzes the trusted network in terms of trusted model for network/user behaviors, architecture of trusted network, service survivability and network manageability, which is designed to give ideas on solving the problems that may be faced in developing the trusted network.

Trust Degree of Web Services and Its Evaluation with Neural Network

The concept and definition of trust degree of Web service is given. Evaluating trust degree of Web services with the method of neural network from the aspect of trust history sequence is proposed. The principle of the method, applicable neural network structure, neural network construc ting, input standardization, training sample constructing, and the procedure of evaluating trust degree of Web services with trained neural network are described. Experiments show that it is feasible and effective to evaluate trust degree of Web Service with neural network.

An Extended Hierarchical Trusted Model for Wireless Sensor Networks

Cryptography and authentication are traditional approach for providing network security. However, they are not sufficient for solving the problems which malicious nodes compromise whole wireless sensor network leading to invalid data transmission and wasting resource by using vicious behaviors. This paper puts forward an extended hierarchical trusted architecture for wireless sensor network, and establishes trusted congregations by three-tier framework. The method combines statistics, economics with encrypt mechanism for developing two trusted models which evaluate cluster head nodes and common sensor nodes respectively. The models form logical trusted-link from command node to common sensor nodes and guarantees the network can run in secure and reliable circumstance.

METrust: A Mutual Evaluation-based Trust Model for P2P Networks

It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer （P2P） network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers＇ evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers＇ malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers＇ own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.

Self-Organized Public-Key Management for Mobile Ad Hoc Networks Based on a Bidirectional Trust Model

In traditional networks , the authentication is performed by certificate authoritys（CA）,which can＇t be built in distributed mobile Ad Hoc Networks however. In this pa per, we propose a fully self-organized public key management based on bidirectional trust model without any centralized authority that allows users to generate their public-private key pairs, to issue certificates, and the trust relation spreads rationally according to the truly human relations. In contrast with the traditional self-organized public-key management, the average certificates paths get more short, the authentication passing rate gets more high and the most important is that the bidirectional trust based model satisfys the trust re quirement of hosts better.

Research on the Trusted Energy-Saving Transmission of Data Center Network

According to the high operating costs and a large number of energy waste in the current data center network architectures, we propose a kind of trusted flow preemption scheduling combining the energy-saving routing mechanism based on typical data center network architecture. The mechanism can make the network flow in its exclusive network link bandwidth and transmission path, which can improve the link utilization and the use of the network energy efficiency. Meanwhile, we apply trusted computing to guarantee the high security, high performance and high fault-tolerant routing forwarding service, which helps improving the average completion time of network flow.

Research on Beta Trust Model of Wireless Sensor Networks Based on Energy Load Balancing

This paper proposed beta trust model based on energy load balancing combines the recent achievements of the trust models in distributed networks, together with the characteristics of wireless sensor networks. The inter-node trust relation is established after an overall evaluation of node trust value based on the monitor results of the node packets forwarding behavior conducted by inter-node collaboration. Due to the node energy limitation in wireless sensor networks, energy load balancing mechanism is applied to prolong the node survival time. And the redundant routing protocol involves the presented trust model to develop the novel trust routing protocol of beta trust model based on energy load balancing. Simulation performance demonstrates that the beta trust model based on energy load balancing outperforms current schemes in energy consumption.

Real-Time Multi Fractal Trust Evaluation Model for Efficient Intrusion Detection in Cloud

Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks.To address such threats towards cloud services,numerous techniques exist that mitigate the service threats according to different metrics.The rule-based approaches are unsuitable for new threats,whereas trust-based systems estimate trust value based on behavior,flow,and other features.However,the methods suffer from mitigating intrusion attacks at a higher rate.This article presents a novel Multi Fractal Trust Evaluation Model(MFTEM)to overcome these deficiencies.The method involves analyzing service growth,network growth,and quality of service growth.The process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support(TSS).Also,the user’s trust in supporting network stream by computing Trusted Network Support(TNS).Similarly,the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support(TQS).Using all these measures,the method adds the Trust User Score(TUS)value to decide on the clearance of user requests.The proposed MFTEM model improves intrusion detection accuracy with higher performance.

Antecedents of Social Network Trust in SNS Usage: The Moderating Role of Offline Familiarity

With the rapid development of social networks, there is a focus on marketing strategies and business models that are based on social media. In the academic world, scholars believe that online trust is a key factor contributing to online purchasing behavior. This article explored several factors in social media trust and verified the moderating role of offline familiarity by using relevant research on online trust in conjunction with a structure equation model. The results show that independent variables such as reputation, SNS interaction, information quality, reciprocity, satisfaction and shared values have a positive influence on trust, whereas perceived similarity does not, and information quality is the most important factor. In addition, offline familiarity significantly moderates the relations between information quality, reciprocity, reputation, shared values and social media trust. This information is important to assist companies in developing an effective social network marketing strategy.

A Novel Multi-Level Trust Algorithm for Mobile Ad Hoc Networks

Firstly, a multilevel trust algorithm for MANET （mobile ad hoe networks） is presented in this paper and the trust level is defined as a three-tuple type in this multilevel trust algorithm. The paper introduces the multilevel trust into MANET, thereby controlling restricted classified information flows among nodes that have different trust levels. Secondly, the infrastructure of MANET that suit to our multi-level trust is presented, Some conclusions are given at lastly.

A TRUST MECHANISM-BASED CHANNEL ASSIGNMENT AND ROUTING SCHEME IN COGNITIVE WIRELESS MESH NETWORKS WITH INTRUSION DETECTION

Cognitive Wireless Mesh Networks(CWMN) is a novel wireless network which combines the advantage of Cognitive Radio(CR) and wireless mesh networks.CWMN can realize seamless in-tegration of heterogeneous wireless networks and achieve better radio resource utilization.However,it is particularly vulnerable due to its features of open medium,dynamic spectrum,dynamic topology,and multi-top routing,etc..Being a dynamic positive security strategy,intrusion detection can provide powerful safeguard to CWMN.In this paper,we introduce trust mechanism into CWMN with intrusion detection and present a trust establishment model based on intrusion detection.Node trust degree and the trust degree of data transmission channels between nodes are defined and an algorithm of calcu-lating trust degree is given based on distributed detection of attack to networks.A channel assignment and routing scheme is proposed,in which selects the trusted nodes and allocates data channel with high trust degree for the transmission between neighbor nodes to establish a trusted route.Simulation re-sults indicate that the scheme can vary channel allocation and routing dynamically according to network security state so as to avoid suspect nodes and unsafe channels,and improve the packet safe delivery fraction effectively.

A Sensing Layer Network Resource Allocation Model Based on Trusted Groups

There are many heterogeneous sensing nodes in the sensing layer of the Internet of Things, and the amount of data transmission is huge, which puts high requirements on the allocation of network bandwidth. At the same time, untrusted sensing nodes maliciously invade network resources. Therefore, how to confirm whether a sensing node is trusted and reasonably allocate network resources is an urgent problem to be solved. To resolve this issue, this paper proposes a sensing network resource allocation model based on trusted groups. Through the sensing node computing environment and behavior measurement, we can identify and exclude untrusted nodes, so the trusted group can be built. Then the network resources are distributed from a global perspective. Based on the available bandwidth of the link, a network resource fusion model of IPv4 and IPv6 is proposed. On this basis, a global network resource allocation model is further proposed. Afterwards, real-time monitoring of data transmission behavior ensures data security during transmission. Simulation experiments show that this mechanism can effectively optimize the bandwidth allocation in the data transmission process and has little effect on the running efficiency of existing network applications. At the same time, it can effectively guarantee the trust of nodes and achieve trusted data transmission.

A Trust Evaluation Model for Social Commerce Based on BP Neural Network

Recent years we have witnessed the rapid growth of social commerce in China, but many users are not willing to trust and use social commerce. So improving consumers’ trust and purchase intention has become a crucial factor in the success of social commerce. Business factors, environment factors and social factors including twelve secondary indexes build up a social commerce trust evaluation model. Questionnaires are handed out to collect twelve secondary indexes scores as input of BP neural network and composite score of trust as output. Model simulation shows that both training samples and test samples have low level of average error and standard deviation, which certify that the model has good stability and it is a good method for evaluating social commerce trust.