Trust Measurement Model Research Articles

SABDTM: Security-first architecture-based dynamic trusted measurement scheme for operating system of the virtual computing node

In the cloud environment, the virtual computing node has become the dominant form of cloud services used by users. Hence, it is increasingly critical to guarantee the trusted operation of the virtual computing node's operating system (VCNOS). However, previous schemes suffer a lot, such as insufficient consideration of the comprehensive of the measured objects, ignoring the dynamic of trusted, and the trusted measurement mechanisms rarely consider their security. Thus, a three-dimensional dynamic trusted measurement model SABDTM, which integrates the integrity measurement of kernel static data, trusted evaluation of operating system behavior (OSB), and the feedback trust of interacting nodes, is proposed. First, SABDTM divided OSB into multiple atomic behaviors and introduced the Bayesian decision theory to predict trusted expectations of OSBs. Second, the feedback trust of interacting nodes is considered to improve the comprehensiveness of the trusted measurement and evaluate its value based on the Euclidean distance function to reduce the impact of inaccurate feedback from malicious nodes. Subsequently, we set the appropriate weight for trusted measurement values of different moments based on Induced Ordered Weighted Averaging to accurately portray the actual state of VCNOS. Moreover, we designed a lightweight and independent subsystem to perform the trusted measurement, which guarantees the security of the measurement service. The security of our model is proved rigorously based on the non-interference theory. Finally, the experiments and comparative analysis demonstrated our model has better functionality and superiority.

A decentralized and reliable trust measurement for edge computing enabled Internet of Things

SummaryThe combination of edge computing (EC) and the Internet of Things is a hot research topic. And security is one of the most important problems to be solved. The trust measurement of devices is an effective way to solve the security problem, and the lack of a unified trust measurement model makes the untrusted devices destroy the quality of service. Establishing a reliable trust relationship between devices can effectively improve the security of the system. A decentralized trust measurement model for devices is proposed. First, a decentralized trust measurement framework is proposed, which combines EC with blockchain technology to establish a decentralized hierarchical structure; second, the credibility of devices is measured from multilevel and multi‐attribute; finally, a feedback trust filtering mechanism is designed to filter reliable feedback information, and then the trust between devices and the comprehensive trust of devices are calculated. Experiments and analysis show that the proposed decentralized trust measurement model can effectively measure the trust degree of devices and resist various malicious feedback attacks.

Auto-Adaptive Trust Measurement Model Based on Multidimensional Decision-Making Attributes for Internet of Vehicles

As an important branch and application of the Internet of Things (IoT), the Internet of Vehicles (IoV) has the characteristics of wide distribution and dynamic connection. The current research on trust measurement and management in IoV, to some degree, solved vehicles reliability and QoS issues, but these models still have some drawbacks, like insufficient adaptability to the dynamic changes of the context. Therefore, this paper proposes an adaptive trust measurement model for IoV based on multidimensional decision-making attributes. The model not only takes full advantage of the central static trust management role of the local organization but also implements a distributed self-governing mechanism to tackle the dynamic trust management issues. In the process of trust management, the model allows vehicles to handle the trust evaluation according to the service preferences, and vehicles can select some or all of the attributes from the multidimensional trust decision attribute list. For the recommendation trust evaluation, vehicles can select those vehicles which have similar service preferences from the vehicle candidate list. When computing the recommendation trust, the recommendation trust dispersion model is used to handle evaluation bias problems. The method of information entropy is introduced to tackle the weight adaptation problem when computing comprehensive trust evaluation. The simulation results and analysis show that the model can detect and recognize the malicious vehicles in the network and mitigate the risk that malicious vehicles provide the service to normal vehicles.

Research on consumer trust measurement model for agricultural products e-commerce based on D-S evidence theory

ABSTRACT This paper designs a consumer trust measurement model of agricultural e-commerce based on D-S evidence theory for improving the accuracy of consumer trust measurement of agricultural products e-commerce. First of all, the index system of consumer trust of agricultural products e-commerce was constructed. Then, the two sides of the transaction were divided into direct and indirect trust models. Secondly, according to the calculation results of direct trust, combining with redistributive conflict evidence, weight coefficient, time decay and confidence, indirect trust was calculated. Eventually, the comprehensive trust degree of agricultural e-commerce consumers was calculated based on D-S evidence theory. The results show that the model designed in this paper has good application effect and accurately measure consumer trust.

A Trust Verification Architecture with Hardware Root for Secure Clouds

Cloud security has become a vital issue within thousands of inter-connected servers in clouds, as malicious attacks or discovered vulnerabilities may spread more rapidly than ever. Based on the opinion that hardware is more secure and trustworthy, a trust platform module (TPM) is used as an external chip to ensure the trust verification, while it's unsuitable as virtual machine (VM) migration, hybrid servers, distributed storage with a low performance. So, we design a novel cloud architecture with a special physical server named as the trust verification server (TVS) to provide trust services according to the TPM specification, then the servers in the cloud can use TVS remotely as a high-performance TPM chip. In this paper, we design the TVS with accelerator hardware, upgrade the cloud architecture with an additional certificate authority (CA) server, and use TVS with a non-interference trust measurement model. The experiments show that the TVS can work efficiently with huge performance improvements at more than 100 times compared with the use of TPM in the cloud. This can be used to solve the complex cloud security problems such as VM sprawl and VM escape.

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.

A Factored Similarity Model with Trust and Social Influence for Top-N Recommendation

Many trust-aware recommendation systems have emerged to overcome the problem of data sparsity, which bottlenecks the performance of traditional Collaborative Filtering (CF) recommendation algorithms. However, these systems most rely on the binary social network information, failing to consider the variety of trust values between users. To make up for the defect, this paper designs a novel Top-N recommendation model based on trust and social influence, in which the most influential users are determined by the Improved Structural Holes (ISH) method. Specifically, the features in Matrix Factorization (MF) were configured by deep learning rather than random initialization, which has a negative impact on prediction of item rating. In addition, a trust measurement model was created to quantify the strength of implicit trust. The experimental result shows that our approach can solve the adverse impacts of data sparsity and enhance the recommendation accuracy.

Research on security trust measure model based on fuzzy mathematics

Abstract The existing safety measurement model has the disadvantages of poor reliability and stability. In order to improve the reliability of the security trust measurement structure, a fuzzy trust-based security trust measurement model is proposed. The hierarchical fuzzy transmission network is used to establish the mathematical model of the controlled object, and the control objective function is analyzed. The regression analysis model is combined with the convergence constraint function, and the fuzzy adaptive learning is performed according to the security trusted computing output weight, and the parameter analysis is performed. And adjust; on this basis, establish a mathematical model of safety confidence measurement, and perform parameter feedback adjustment and reliability control to improve the reliability of the security trust measurement structure. The simulation results show that the proposed method has good reliability and steady-state convergence, and can effectively improve the reliability calculation ability of the safety confidence measure. It has strong application advantages.

Trusted measurement and evaluation for intelligent transportation system products: A case study for traffic signal controller

This study proposes trusted measurement and evaluation models for intelligent transportation system products to provide technological means for the transport sector and government departments to detect the compliance and availability of intelligent transportation system products and consider the market access of intelligent transportation system products. Then, this study builds a trusted testing platform based on a hardware-in-loop system to test and validate trusted measurement and evaluation models of intelligent transportation system products. Finally, a traffic signal controller is tested and validated in the platform in different operation environments. The result shows that the trusted measurement model can accurately measure the trusted status in normal and non-normal operation conditions, and the trusted evaluation model can dynamically calculate the intelligent transportation system product’s trusted attributes, namely, the trusted evaluation values and comprehensive trusted evaluation values of the intelligent transportation system product, as the intelligent transportation system product’s operation environment changes.

A trusted measurement model based on dynamic policy and privacy protection in IaaS security domain

In Infrastructure as a Service (IaaS) environments, the user virtual machine is the user’s private property. However, in the case of privacy protection, how to ensure the security of files in the user virtual machine and the user virtual machine’s behavior does not affect other virtual machines; it is a major challenge. This paper presents a trusted measurement model based on dynamic policy and privacy protection in IaaS security domain, called TMMDP. The model first proposed a measure architecture, where it defines the trusted measurement of the user virtual machine into the trust of files in the virtual machine and trusted network behavior. The trusted measure was detected through the front-end and back-end modules. It then describes in detail the process of the trusted measurement in the two modules. Because the front-end module is in the guest virtual machine, it also describes the protocol to ensure the integrity of the module. Finally, the model proved to address security challenges of the user virtual machine in IaaS environments by a security analysis.

A Model of Trusted Measurement Model

A model of Trusted Measurement supporting behavior measurement based on trusted connection architecture (TCA) with three entities and three levels is proposed, and a frame to illustrate the model is given. The model synthesizes three trusted measurement dimensions including trusted identity, trusted status and trusted behavior, satisfies the essential requirements of trusted measurement, and unified the TCA with three entities and three levels.

A game theory-based trust measurement model for social networks.

BackgroundIn social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks.MethodsWe propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively.Results and conclusionsWe prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

DTSTM: Dynamic Tree Style Trust Measurement Model for Cloud Computing

In cloud computing infrastructure, current virtual machine trust measurement methods have many shortcomings in dynamism, security and concurrency. In this paper, we present a new method to measure the trust of virtual machine. Firstly, we propose “behavior trace” to describe the state of virtual machine. Behavior trace is a sequence of behaviors. The measurement of behavior trace is conducted on the basis of anticipated trusted behavior, which not only ensures security of the virtual machine during runtime stage but also reduces complexity of the trust measurement. Based on the behavior trace, we present a Dynamic Tree Style Trust Measurement Model (DTSTM). In this model, the measurement of system domain and user domain is separated, which enhances the extensibility, security and concurrency of the measurement. Finally, based on System Call Interceptor (SCI) and Virtual Machine Introspection (VMI) technology, we implement a DTSTM prototype system for virtual machine trust measurement. Experimental results demonstrate that the system can effectively verify the trust of virtual machine and requires a relatively low performance overhead.

Trusted measurement model based on multitenant behaviors.

With a fast growing pervasive computing, especially cloud computing, the behaviour measurement is at the core and plays a vital role. A new behaviour measurement tailored for Multitenants in cloud computing is needed urgently to fundamentally establish trust relationship. Based on our previous research, we propose an improved trust relationship scheme which captures the world of cloud computing where multitenants share the same physical computing platform. Here, we first present the related work on multitenant behaviour; secondly, we give the scheme of behaviour measurement where decoupling of multitenants is taken into account; thirdly, we explicitly explain our decoupling algorithm for multitenants; fourthly, we introduce a new way of similarity calculation for deviation control, which fits the coupled multitenants under study well; lastly, we design the experiments to test our scheme.

Dynamic trusted measurement model of operating system kernel

Dynamic trusted measurement is a hot and difficult research topic in trusted computing.Concerning the measurement difficulty invoked by the dynamic nature of operating system kernel,a Dynamic Trusted Kernel Measurement(DTKM) model was proposed.Dynamic Measurement Variable(DMV) was presented to describe and construct dynamic data objects and their relations,and the method of semantic constraint was proposed to measure the dynamic integrity of kernel components.In DTKM,the collection of memory data was implemented in real-time,and the dynamic integrity was verified by checking whether the constructed DMV was consistent with semantic constraints which were defined based on the security semantics.The nature analysis and application examples show that DTKM can effectively implement dynamic measurement of the kernel and detect the illegal modification of the kernel dynamic data.

一个网构软件可信实体模型及基于评估的信任度量

Dependability management is an essential issue for Internetware which is in open, dynamic and decentralized Internet environment. Most research focuses on trust measurement and evolution model. However, there are some issues of the model in the aspects of source of trust, the constraint on trust relation of entities, and the parameter of trust transition for Internetware. This paper proposes a dependable entity model for Internetware, and presents a method of trust measurement based on Bayesian networks. Dependability of entity is secured by mechanism of self-examination and declaration. Trust relation of entities is constrained by contract trust. The parameter of trust transition is calculated accurately by synthesizing recommendation trust and being amended by evaluation. In the last of this paper, we design an experiment and the results show that the model is correct.

Development-based trust: proposing and validating a new trust measurement model for buyer-seller relationships

This study proposes and validates a trust measurement model for buyer-seller relationships. Baptized as development-based trust, the model encompasses three dimensions of trust: calculus-based, knowledge-based and identification-based. In addition to recognizing that trust is a multidimensional construct, the model also assumes that trust can evolve to take on a different character depending on the stage of the relationship. In order to test the proposed model and compare it to the characteristic-based trust measurement model, the measure most frequently used in the buyer-seller relationship literature, data were collected from 238 clients of an IT product wholesaler. The results show that the scales are valid and reliable and the proposed development-based trust measurement model is superior to the characteristic-based trust measurement model in terms of its ability to explain certain variables of interest in buyer-seller relationships (long-term relationship orientation, information sharing, behavioral loyalty and future intentions). Implications for practice, limitations and suggestions for future studies are discussed.

Adaptive Dynamic Trust Measurement and Prediction Model Based on Behavior Monitoring

In the large-scale distributed systems,trust relationship model is one of the most complex concepts in social relationships,and it also is an abstract psychological cognitive process,involving assumptions,expectations,behavior and the environment,and other factors.So,it is very difficult to quantify and predict trust relationship accurately.In this paper,rough set theory and information entropy theory are combined and applied to the study of distributed dynamic trust measurement and prediction model based on behavior data.The new model works through analysis monitored behavior data by sensors directly,changes the traditional modeling thoughts,brakes away from the fetter of various subjective assumptions in traditional modeling methods,and overcomes the problem of inadequate handling capacity for multi-source behavior data in the traditional trust model.Simulating results shows that the new model can accurately implement trust measurement and prediction process between entities in open and complex distributed environment,and has a better scalable capacity of behavior data.

A Trust Measurement and Evolution Model for Internetware

Internetware is built upon the coordination of the heterogeneous, autonomous software entities in the open coordination environment. But it is very difficult to select the honest coordination software entities with dependable quality of services to build the trusted Internetware because of the openness and dynamic of the Internet. Trust relationships among software entities will provide important information about the selections of trusted coordination entities. The trust relationships are always changing along with the co-operations of software entities. However, the existing trust models cannot support the automatic formation and update of the trust relationships among entities, and cannot reflect the dynamic attribute of the trust relationships. This paper presents a trust measurement and evolution model for the Internetware. The model abstracts the process of the trust measurement, transfer and combination rationally and provides a reasonable approach to form and update trust relationships automatically. This model is helpful to solve the problem of the trustworthiness of the Internetware.