A simulation testbed for analyzing trust and reputation mechanisms in unreliable online markets

Modern online markets are becoming extremely dynamic, indirectly dictating the need for (semi-) autonomous approaches for constant monitoring and immediate action in order to satisfy one’s needs/preferences. In such open and versatile environments, software agents may be considered as a suitable metaphor for dealing with the increasing complexity of the problem. Additionally, trust and reputation have been recognized as key issues in online markets and many researchers have, in different perspectives, surveyed the related notions, mechanisms and models. Within the context of this work we present an adaptable, multivariate agent testbed for the simulation of open online markets and the study of various factors affecting the quality of the service consumed. This testbed, which we call Euphemus, is highly parameterized and can be easily customized to suit a particular application domain. It allows for building various market scenarios and analyzing interesting properties of e-commerce environments from a trust perspective. The architecture of Euphemus is presented and a number of well-known trust and reputation models are built with Euphemus, in order to show how the testbed can be used to apply and adapt models. Extensive experimentation has been performed in order to show how models behave in unreliable online markets, results are discussed and interesting conclusions are drawn.     

An integrated trust and reputation model for open multi-agent systems

Trust and reputation are central to effective interactions in open multi-agent systems (MAS) in which agents, that are owned by a variety of stakeholders, continuously enter and leave the system. This openness means existing trust and reputation models cannot readily be used since their performance suffers when there are various (unforseen) changes in the environment. To this end, this paper presents FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance in open systems. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide trust metrics in most circumstances. FIRE is empirically evaluated and is shown to help agents gain better utility (by effectively selecting appropriate interaction partners) than our benchmarks in a variety of agent populations. It is also shown that FIRE is able to effectively respond to changes that occur in an agent’s environment.     

Towards a trust,reputation and recommendation meta model

New trust, reputation and recommendation (TRR) models are continuously proposed. However, the existing models lack shared bases and goals. For this reason, in this work we define an innovative meta model to facilitate the definition and standardization of a generic TRR model. Following the meta model, researchers in the field will be able to define standard models, compare them with other models and reuse parts of them. A standardization is also needed to determine which properties should be present in a TRR model.In accordance with the objectives we were seeking, following our meta model, we have defined a pre-standardized TRR model for e-commerce, identified the fundamental concepts and the main features that contribute to form trust and reputation in that domain, respected the dependence on the context/role of trust and reputation, aggregated only homogeneous trust information; listed and shown how to defend from the main malicious attacks.     

在线信誉系统中的信任模型构建研究

针对现有在线信誉系统中信任模型的缺陷,基于在线拍卖的特点,并结合已有信任研究成果,构建了基于多影响因素的信任模型．本模型适用于在线拍卖环境下对用户信誉状况的全面、准确的评估．仿真实验表明,与现有信任模型相比,本模型的信任度计算精确度较高,具有较好的可行性．     

基于名声评价的信任模型研究

根据交易者在交易环境中的角色划分设立商家名声与消费者名声,提出了基于评价时间顺序、交易金额和消费者信任值权重的信任模型;通过金额和消费者信任值加权计算商家加权平均分,在判断消费者评价可信度基础上,考虑时间衰减因子计算商家信任值。实验证明,该信任模型能够准确地判断诋毁消费者和不诚信商家,提高了信任模型的抗攻击能力和可用性,可有效帮助消费者识别商家的信任值变化趋势。     

Establishing agent trust for contradictory evidence by means of fuzzy voting model: An ontology mapping case study

This paper introduces a novel trust assessment formalism for contradicting evidence in the context of multi-agent ontology mapping. Evidence combination using the Dempster rule tend to ignore contradictory evidence and the contemporary approaches for managing these conflicts introduce additional computation complexity i.e. increased response time of the system. On the Semantic Web, ontology mapping systems that need to interact with end users in real time cannot afford prolonged computation. In this work, we have made a step towards the formalisation of eliminating contradicting evidence, to utilise the original Dempster’s combination rule without introducing additional complexity. Our proposed solution incorporates the fuzzy voting model to the Dempster–Shafer theory. Finally, we present a case study where we show how our approach improves the ontology mapping problem.     

TRIMS,a privacy-aware trust and reputation model for identity management systems

Electronic transactions are becoming more important everyday. Several tasks like buying goods, booking flights or hotel rooms, or paying for streaming a movie, for instance, can be carried out through the Internet. Nevertheless, they are still some drawbacks due to security threats while performing such operations. Trust and reputation management rises as a novel way of solving some of those problems. In this paper we present our work TRIMS (a privacy-aware trust and reputation model for identity management systems), which applies a trust and reputation model to guarantee an acceptable level of security when deciding if a different domain might be considered reliable when receiving certain sensitive user’s attributes. Specifically, we will address the problems which surfaces when a domain needs to decide whether to exchange some information with another possibly unknown domain to effectively provide a service to one of its users. This decision will be determined by the trust deposited in the targeting domain. As far as we know, our proposal is one of the first approaches dealing with trust and reputation management in a multi-domain scenario. Finally, the performed experiments have demonstrated the robustness and accuracy of our model in a wide variety of scenarios.     

Countering the collusion attack with a multidimensional decentralized trust and reputation model in disconnected MANETs

The FIRE trust and reputation model is a de-centralized trust model that can be applied for trust management in unstructured Peer-to-Peer (P2P) overlays. The FIRE model does not, however, consider malicious activity and possible collusive behavior in nodes of network and it is therefore susceptible to collusion attacks. This investigation reveals that FIRE is vulnerable to lying and cheating attacks and presents a trust management approach to detect collusion in direct and witness interactions among nodes based on colluding node’s history of interactions. A witness ratings based graph building approach is utilized to determine possibly collusive behavior among nodes. Furthermore, various interaction policies are defined to detect and prevent collaborative behavior in colluding nodes. Finally a multidimensional trust model FIRE+ is devised for avoiding collusion attacks in direct and witness based interactions. The credibility of the proposed trust management scheme as an enhancement of the FIRE trust model is verified by extensive simulation experiments.     

一种置信于主流评价的P2P环境信誉模型*

针对P2P环境中策略性欺骗和作弊行为识别及防范难的问题,提出一种基于置信于主流意见的信誉模型(PTMTrust)。基于诚实反馈是节点间交互主流的原则,采用最大密度方法,构建滑动窗口定位主流评价值聚类中心。用评价值拟合度、交互活跃度和交易数等参数,确定评价值的可信度,使全局信任度真实反映节点服务或交易质量,惩罚虚假交易行为,抑制不真实评价的影响,增强评价系统的公平性,提高交易成功率。仿真实验验证了模型的保护功能,与传统信誉模型相比,由于推荐权重得到合理分配,有效地缓解了合谋作弊等恶意行为的影响,遏制了不诚实     

An interval type‐2 fuzzy trust evaluation model in social commerce

Trust is crucial for purchasing decisions in social commerce. However, inexperienced users may not have a direct trust relation to experienced users in practice. Besides, users tend to give their trust degrees to others with linguistic labels rather than crisp values. To evaluate the trust degree for inexperienced users to experienced ones, we propose an interval type‐2 fuzzy trust evaluation model in this paper. Interval type‐2 fuzzy linguistic labels are used to represent trust degree among users. An interval type‐2 fuzzy Algebraic t‐norm is addressed to compute propagative trust degrees. Considering the effect of trust path length, the induced ordered weighted averaging (IOWA) operator is extended to aggregate the interval type‐2 fuzzy trust degrees obtained from multiple paths. In addition, the final interval type‐2 fuzzy trust degree is transferred into the corresponding linguistic label to help users make decisions more naturally. Finally, a case study in social commerce and a related comparison are given to verify the effectiveness of the proposed model.     

A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications

As a practical popular methodology for dealing with fuzziness and uncertainty in Multiple Criteria Decision-Making (MCDM), Fuzzy AHP (FAHP) has been applied to a wide range of applications. As of the time of writing there is no state of the art survey of FAHP, we carry out a literature review of 190 application papers (i.e., applied research papers), published between 2004 and 2016, by classifying them on the basis of the area of application, the identified theme, the year of publication, and so forth. The identified themes and application areas have been chosen based upon the latest state-of-the-art survey of AHP conducted by [Vaidya, O., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of operational research, 169(1), 1–29.]. To help readers extract quick and meaningful information, the reviewed papers are summarized in various tabular formats and charts. Unlike previous literature surveys, results and findings are made available through an online (and free) testbed, which can serve as a ready reference for those who wish to apply, modify or extend FAHP in various applications areas. This online testbed makes also available one or more fuzzy pairwise comparison matrices (FPCMs) from all the reviewed papers (255 matrices in total).In terms of results and findings, this survey shows that: (i) FAHP is used primarily in the Manufacturing, Industry and Government sectors; (ii) Asia is the torchbearer in this field, where FAHP is mostly applied in the theme areas of Selection and Evaluation; (iii) a significant amount of research papers (43% of the reviewed literature) combine FAHP with other tools, particularly with TOPSIS, QFD and ANP (AHP’s variant); (iv) Chang’s extent analysis method, which is used for FPCMs’ weight derivation in FAHP, is still the most popular method in spite of a number of criticisms in recent years (considered in 57% of the reviewed literature).     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

An outline of a trust model for electronic commerce

A generic model of trust for electronic commerce is presented. The basic components of the model are party trust and control trust. It is argued that an agent's trust in a transaction with another party is a combination of the trust in the other party and the trust in the control mechanisms for the successful performance of the transaction. The generic trust model can be used for the design of trust related value-added services in electronic commerce. To illustrate this design use of the model, two activities in electronic commerce are compared that require trust, namely electronic payment and cross-border electronic trade. It is shown with the model that these two activities actually require two different types of trust, and that complete different services are needed to create these different types of trust.     

一种基于模糊逻辑的网络认证扩展模型*

摘要：为了解决主体之间的信任关系一般很难用精确方式来描述这一问题,以模糊逻辑为基础对传统基于数字证书的主体认证模型进行了扩展,并对认证路径的构造和信任值计算规则进行了研究,该算法可以信任值为基础给出了信任级别的计算方法,为网络认证的研究提供了一条新思路。     

Manufacturing enterprise collaboration based on a goal-oriented fuzzy trust evaluation model in a virtual enterprise

To cope with the rapidly changing manufacturing environment, enterprise collaboration is getting increasingly more attention than ever before. The virtual enterprise (VE) is a concept that supports temporary alliances of manufacturing enterprises that have various collaboration models, such as extended enterprise, networked enterprise, concurrent enterprise, etc. Selection of trustworthy partners and trust building are important in virtual domains because they have largely been affecting the success of a VE. However, because of its complexity of trust, trust models in the literature are limited in their ability to cope with dynamic and virtual environment. In this paper, we propose a trust evaluation method of supporting enterprise collaboration and maximizing the satisfaction of cooperation. In this context, trust means the goal achievement probability. Trust value of an enterprise can be obtained by a fuzzy inference system whose rule-base is based on the top-level goal of a VE. According to the selector’s preference, various rules can be applied to trust evaluation. For further study, the planning and scheduling problems should be considered along with the trust-based partner selection for collaboration among manufacturing enterprises.     

Neutrosophic classifier: An extension of fuzzy classifer

Fuzzy classification has become of great interest because of its ability to utilize simple linguistically interpretable rules and has overcome the limitations of symbolic or crisp rule based classifiers. This paper introduces an extension to fuzzy classifier: a neutrosophic classifier, which would utilize neutrosophic logic for its working. Neutrosophic logic is a generalized logic that is capable of effectively handling indeterminacy, stochasticity acquisition errors that fuzzy logic cannot handle. The proposed neutrosophic classifier employs neutrosophic logic for its working and is an extension of commonly used fuzzy classifier. It is compared with the commonly used fuzzy classifiers on the following parameters: nature of membership functions, number of rules and indeterminacy in the results generated. It is proved in the paper that extended fuzzy classifier: neutrosophic classifier; optimizes the said parameters in comparison to the fuzzy counterpart. Finally the paper is concluded with justifying that neutrosophic logic though in its nascent stage still holds the potential to be experimented for further exploration in different domains.     

基于模糊理论的主观信任评价模型的研究

针对开放式网络环境中信任的主观性、不确定性等特点, 提出了一个基于模糊理论的主观信任评价模型。该模型运用模糊理论得出节点间的综合信任评价的计算式, 并在信任的计算中引入时间因子、对不诚信节点的约束机制, 利用贴近度反求权重计算综合信任值, 最后利用模糊等价关系实现信任值的聚类分析。通过仿真实验结果分析, 证明了该模型具有有效性和可行性, 并通过仿真实验比较, 验证了该模型能够客观地反映出接近真实的情况。     

基于模糊模拟的主观信任评价模型研究

通过对开放网络环境中主观信任评价方法的讨论,考虑到主观信任的模糊性,提出以可信性理论为基础的主观信任量化表述与评价方法,并给出了主体信任属性评价值为模糊变量情形下主观信任可信性的模拟计算方法。实例分析表明,该方法对主观信任评价是可行和有效的。     

异构无线网络中基于模糊集合的动态信任模型

针对异构无线网络融合带来的安全问题,提出了一个基于模糊集合的动态信任模型DTMBF。使用模糊隶属度标示了信任的主观不确定性,引入直接信任、推荐信任、推荐可信度和信任时间戳4个参量来计算网络的信任度,并通过信任反馈控制机制动态调节上述参量。直接信任和推荐信任反映了网络的历史服务情况,推荐可信度和信任时间戳则反映了信任反馈的可信性和时效性。仿真分析表明,该模型能准确有效地确定网络的信任度,有效地抑制了恶意用户的诋毁行为和合谋欺骗行为。