A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

A Dynamic Bayesian-Based Comprehensive Trust Evaluation Model for Dispersed Computing Environment

Dispersed computing is a new resourcecentric computing paradigm.Due to its high degree of openness and decentralization,it is vulnerable to attacks,and security issues have become an important challenge hindering its development.The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks.In this paper,a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment.Specifically,in the calculation of direct trust,a logarithmic decay function and a sliding window are introduced to improve the timeliness.In the calculation of indirect trust,a random screening method based on sine function is designed,which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks.Finally,the comprehensive trust value is dynamically updated based on historical interactions,current interactions and momentary changes.Simulation experiments are introduced to verify the performance of the model.Compared with existing model,the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes,the interaction success rate,and the computational cost.

Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

Recently,Wireless Sensor Network(WSN)becomes most potential technologies for providing improved services to several data gathering and track-ing applications.Because of the wireless medium,multi-hop communication,absence of physical protectivity,and accumulated traffic,WSN is highly vulner-able to security concerns.Therefore,this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis.It is challenging to determine if packet loss is caused by a collision in the medium access path,poor channel quality,or a selective forwarding assault.Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks.As a result,in this study effort,we present a unique Modified Ad Hoc On-Demand Distance Vector(AODV)Routing protocol depending upon the One time password(OTP)method that employs the RSA algorithm.Finally,a trust evaluation process determines which approach is the most optimal.Accord-ing to the simulationfindings of the suggested routing protocol and comparison with existing routing protocols provided in this article,the proposed work is both efficient and cost-effective.

Fuzzy Model for Trust Evaluation

Based on fuzzy set theory, a fuzzy trust model is established by using membership function to describe the fuzziness of trust. The trust vectors of subjective trust are obtained based on a mathematical model of fuzzy synthetic evaluation. Considering the complicated and changeable relationships between various subjects, the multi-level mathematical model of fuzzy synthetic evaluation is introduced. An example of a two-level fuzzy synthetic evaluation model confirms the feasibility of the multi-level fuzzy synthesis evaluation model. The proposed fuzzy model for trust evaluation may provide a promising method for research of trust model in open networks.

Research Progress of Trust Evaluation Model

Software systems in distributed environment are changing from a close and relatively static form, whose users are familiar with each other, to an open and highly dynamic mode, which can be visited by public. In such circumstance, trust evaluation model becomes focus of intense research at current time. Trust evaluation model establishes a management framework of trust relationship between entities, involving expression and measurement of trust, comprehensive calculation of direct trust value and recommended trust value, and recognition of malicious entities and recommendations. Based on the analysis of several typical trust evaluation models, the classification of trust evaluation ideas and modes is discussed, the questions existing in current research and the directions of future research are pointed out.

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.

Trust evaluation model of power terminal based on equipment portrait

As the number of power terminals continues to increase and their usage becomes more widespread,the security of power systems is under great threat.In response to the lack of effective trust evaluation methods for terminals,we propose a trust evaluation model based on equipment portraits for power terminals.First,we propose an exception evaluation method based on the network flow order and evaluate anomalous terminals by monitoring the external characteristics of network traffic.Second,we propose an exception evaluation method based on syntax and semantics.The key fields of each message are extracted,and the frequency of keywords in the message is statistically analyzed to obtain the keyword frequency and time-slot threshold for evaluating the status of the terminal.Thus,by combining the network flow order,syntax,and semantic analysis,an equipment portrait can be constructed to guarantee security of the power network terminals.We then propose a trust evaluation method based on an equipment portrait to calculate the trust values in real time.Finally,the experimental results of terminal anomaly detection show that the proposed model has a higher detection rate and lower false detection rate,as well as a higher real-time performance,which is more suitable for power terminals.

An access control scheme for distributed Internet of Things based on adaptive trust evaluation and blockchain

The Internet of Things(IoT)has the characteristics of limited resources and wide range of points.Aiming at the problems of policy centralization and single point of failure in traditional access control schemes,a distributed access control method based on adaptive trust evaluation and smart contract is proposed to provide fine-grained,flexible and scalable authorization for IoT devices with limited resources.Firstly,a modular access control architecture with integrated blockchain is proposed to achieve hierarchical management of IoT devices.Secondly,an IoT trust evaluation model called AITTE based on adaptive fusion weights is designed to effectively improve the identification of illegal access requests from malicious nodes.Finally,an attribute-based access control model using smart contract called AACSC which is built,which consists of attribute set contract(ASC),registration contract(RC),state judgment contract(SJC),authority permission management contract(AMC),and access control contract(ACC).As experimental results show,the scheme can effectively solve the problem of access security in resource-constrained IoT environments.Moreover,it also ensures the reliability and efficiency of the access control implementation process.

A Cross-Domain Trust Model of Smart City IoT Based on Self-Certification

Smart city refers to the information system with Intemet of things and cloud computing as the core tec hnology and government management and industrial development as the core content,forming a large scale,heterogeneous and dynamic distributed Internet of things environment between different Internet of things.There is a wide demand for cooperation between equipment and management institutions in the smart city.Therefore,it is necessary to establish a trust mechanism to promote cooperation,and based on this,prevent data disorder caused by the interaction between honest terminals and malicious temminals.However,most of the existing research on trust mechanism is divorced from the Internet of things environment,and does not consider the characteristics of limited computing and storage capacity and large differences of Internet of hings devices,resuling in the fact that the research on abstract trust trust mechanism cannot be directly applied to the Internet of things;On the other hand,various threats to the Internet of things caused by security vulnerabilities such as collision attacks are not considered.Aiming at the security problems of cross domain trusted authentication of Intelligent City Internet of things terminals,a cross domain trust model(CDTM)based on self-authentication is proposed.Unlike most trust models,this model uses self-certified trust.The cross-domain process of internet of things(IoT)terminal can quickly establish a trust relationship with the current domain by providing its trust certificate stored in the previous domain interaction.At the same time,in order to alleviate the collision attack and improve the accuracy of trust evaluation,the overall trust value is calculated by comprehensively considering the quantity weight,time attenuation weight and similarity weight.Finally,the simulation results show that CDTM has good anti collusion attack ability.The success rate of malicious interaction will not increase significantly.Compared with other models,the resource consumption of our proposed model is significantly reduced.

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.

Authorization Management Framework Based on Joint Trust-Risk Evaluation

Authorization management is important precondition and foundation for coordinating and resource sharing in open networks. Recently, authorization based on trust is widely used whereby access rights to shared resource are granted on the basis of their trust relation in distributed environment. Nevertheless, dynamic change of the status of credential and chain of trust induces to uncertainty of trust relation. Considering uncertainty of authorization and analyzing deficiency of authorization model only based on trust, we proposes joint trust-risk evaluation and build the model based on fuzzy set theory, and make use of the membership grade of fuzzy set to express joint trust-risk relation. Finally, derivation principle and constraint principle of joint trust-risk relationships are presented. The authorization management model is defined based on joint trust-risk evaluation, proof of compliance and separation of duty are analyzed. The proposed model depicts not only trust relationship between principals, but also security problem of authorization.

Dynamic trust evaluation model for task participants oriented to mobile crowd sensing

In the mobile crowd sensing(MCS)network environment,it is very important to establish an evolutionary process that can dynamically depict the trust degree of task participants.To address this issue,this paper proposes a dynamic trust evaluation model for task participants.Firstly,according to the security requirements and trust strategy of the perceived tasks,the attribute reduction algorithm(ARA)based on rough set is used to obtain the multi-attribute indexes that affect the participants’trust information.Removing the redundant attributes can avoid the lag of trust evaluation and reduce the time cost.Secondly,the grey correlation analysis method is used to solve the correlation degree between the target sequence and the comparison sequence on the trust attributes by integrating the multi-attribute decision-making method,which avoids the distortion of the trust evaluation caused by human subjective factors and improves the quality of the perceived data.Finally,a dynamic trust evaluation model for participants in complex sensing network environment is established.The simulation results show that the proposed model can not only dynamically depict the trust degree of participants in real time,but also have higher accuracy and less time cost.

一种P2P网络信任模型METrust

Peer-to-Peer(P2P)网络的异构性、匿名性、自治性等特点导致了一些安全问题,比如伪造、诋毁、协同作弊等,影响了服务质量.提出了一种基于推荐的P2P网络信任模型METrust,节点在网络中拥有唯一的推荐可信度,引入了更新幅度和更新力度两个参数来更新推荐可信度.给出了节点推荐可信度的更新算法;节点根据评价标准的相似程度选择推荐,其中节点的评价标准通过AHP(Analytic Hierarchy Process)方法确定.仿真实验表明,METrust信任模型可以识别恶意节点,有效提高P2P网络的服务质量.

ELISA法与TRUST法、胶体金法检测梅毒抗体的临床应用和方法学评价

目的探讨酶联免疫吸附试验(ELISA)、甲苯胺红不加热血清试验(TRUST)和胶体金免疫层析法(GICA)对梅毒(Syphilis)诊断的临床应用和价值。方法分别采用ELISA、TRUST及胶体金法3种不同的血清学方法对240例皮肤科门诊患者标本和术前患者标本进行检测,结果均以梅毒螺旋体明胶凝集试验(TPPA)进行确认,比较ELISA、TRUST和胶体金法对梅毒的诊断价值。结果在对79例阳性和161例阴性标本的检测中,TRUST、胶体金法、ELISA诊断梅毒的敏感度分别为64.6%、94.9%、98.7%,特异度分别为97.5%、98.8%、100%;TRUST法与TPPA法检测结果差异有统计学意义(P<0.01χ,2=16.53),而ELISA、胶体金法与TPPA法差异无统计学意义(ELISA:P>0.05,χ2=0.00;胶体金法:P>0.05,χ2=0.17)。结论 ELISA法检测梅毒螺旋体抗体具有较高的敏感度和特异度及TPPA法有较高的一致性,可用于临床大批量样本初筛和梅毒感染的确诊。

TPPA和TRUST联合检测梅毒的临床应用效果评价

目的评价梅毒螺旋体明胶颗粒凝集试验(Treponema pallidum particle agglutination,TPPA)与甲苯胺红不加热试验(Toluidine red unheated serum test,TRUST)两种梅毒血清学检测方法在梅毒诊治中的应用价值,并探讨TPPA联合TRUST用于梅毒螺旋体筛查和确诊的重要性和必要性。方法将确诊的595例各期梅毒患者血清同时用TPPA和TRUST进行检测,然后对其结果进行比较和分析。结果 595份血清中,581份血清TPPA阳性,TRUST试验126份血清为阳性,在一期梅毒,二期梅毒,三期梅毒,隐性梅毒,以及胎传梅毒患者中TPPA的阳性率依次为97.73%,98.57%,100.00%,97.33%,100.00%,TRUST阳性率依次为75.00%,94.28%,100.00%,55.90%,60.00%。结论对临床需要输血患者、疑似梅毒螺旋体感染患者及高危人群献血者应联合采用TPPA和TRUST2种方法对其进行检测,在TPPA出现阳性结果时,应同时进行TRUST及其滴度的检测,以利于梅毒螺旋体感染的早期确诊并阻断其传播途径。

Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.

A personalized trustworthy service selection method

A personalized trustworthy service selection method is proposed to fully express the features of trust, emphasize the importance of user preference and improve the trustworthiness of service selection. The trustworthiness of web service is defined as customized multi-dimensional trust metrics and the user preference is embodied in the weight of each trust metric. A service selection method combining AHP （analytic hierarchy process） and PROMETHEE （preference ranking organization method for enrichment evaluations） is proposed. AHP is used to determine the weights of trust metrics according to users＇ preferences. Hierarchy and pairwise comparison matrices are constructed. The weights of trust metrics are derived from the highest eigenvalue and eigenvector of the matrix. to obtain the final rank of candidate services. The preference functions are defined according to the inherent characteristics of the trust metrics and net outranking flows are calculated. Experimental results show that the proposed method can effectively express users＇ personalized preferences for trust metrics, and the trustworthiness of service ranking and selection is efficiently improved.

投票行为加权的间接信任评估方法TrustRank

本文提出了一种基于投票行为加权的间接信任评估方法 TrustRank,通过对参与投票节点及其行为的量化分析,根据节点的不同权重和可信任度,计算出相应节点的间接信任等级,并给出了TrustRank方法的数学表达。

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.

D-S Evidence Theory Based Trust Ant Colony Routing in WSN

This paper proposes a trust ant colony routing algorithm by introducing a node trust evaluation model based on the D-S evidence theory into the ant colony routing protocol to improve the security of wireless sensor networks. To reduce the influence of conflict evidences caused by malicious nods, the consistent intensity is introduced to preprocess conflict evidences before using the D-S combination rule to improve the reliability of the D-S based trust evaluation. The nodes with high trust values will be selected as the routing nodes to insure the routing security, and the trust values are used as heuristic functions of the ant colony routing algorithm. The simulation tests are conducted by using the network simulator NS2 to observe the outcomes of performance metrics of packets loss rate and average end-to-end delay etc. to indirectly evaluate the security issue under the attack of inside malicious nodes. The simulation results show that the proposed trust routing algorithm can efficiently resist malicious attacks in terms of keeping performances of the average end-to-end delay, the throughtput and the routing packet overhead under attacking from malicious nodes.