Trust and Reputation Systems

Eigenvector computations are an important building block for computing authority, trust, and reputation scores in social networks and other graphs. In peer-to-peer networks or other forms of decentralized settings (such as multi-agent platforms), this kind of analysis needs to be performed in a distributed manner and requires bilateral data exchanges between peers. This gives rise to the problem that dishonest peers may cheat in order to manipulate the computation's outcome.

Vehicle platooning is a well-known technique utilized in intelligent and connected vehicles, where a platoon head is responsible to safely lead and guide a group of user
vehicles. Platoon head selection can be optimized for various objectives, such as efficiency, safety, and security. This work considers a reputation system-based approach to enhance the trustworthiness of platoon head selection while maintaining
existing security requirements. The selection of a platoon head is based on the analysis of historical data, collected during previous trips among all participating user vehicles. To enhance trustworthiness, we propose the TrustPH framework, in which cognitive biases in the feedback scores, provided by user vehicles, are examined and the scores are adjusted accordingly. To evaluate TrustPH, a number of datasets are generated including different scenarios of cognitive bias and malicious behavior in user vehicle scoring. The obtained results demonstrate the effectiveness of TrustPH in ignoring cognitive biases in the platoon head selection process while ensuring that certain types of malicious scores are removed.

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.

The advent of socio-technical, cyber-physical and artificial intelligence systems has broadened the scope of requirements engineering, which must now deal with new classes of requirements, concerning ethics, privacy and trust. This brings new challenges to Requirements Engineering, in particular regarding the understanding of the non-functional requirements behind these new types of systems. To address this issue, we propose the Ontology-based Requirements Engineering (ObRE) method, which aims to systematize the elicitation and analysis of requirements, by using an ontology to conceptually clarify the meaning of a class of requirements, such as privacy, ethicality and trustworthiness. We illustrate the working of ObRE by applying it to a real case study concerning trustworthiness requirements.

This paper is concerned with the economics of public private partnerships (PPPs)/private finance initiative (PFIs) and in particular the role of transaction costs and the importance of trust in relational contracting. The discussion is illustrated by reference to the UK defence sector. The paper begins by discussing the nature of PPPs/PFIs before moving on to consider how the economics of contracting literature can shed light on their strengths and weaknesses. The transaction cost literature is reviewed alongside a resource-based perspective of procurement decisions. The concepts of trust and reputation are then considered in the context of minimising procurement transaction costs. The theoretical framework developed is then applied and illustrated through a case study of UK defence contracting, in an attempt to assess whether the use of PPPs will necessarily lead to improved economic efficiency. The case study highlights both the scope of PPPs/PFIs and their potential transaction costs in defence procurement, with the normal perils in terms of contracting given information asymmetry, asset specificity and the resulting scope for opportunistic behaviour. r

"Imagine a world without trust. Without trust even the simplest actions in our lifeworld would hardly ever happen: We would never enter a taxi, never pay with coin or believe in what our doctor says.
We would neither know when and where we are born and might even still believe that the sun rotates around the earth. Trust is an essential trait of our social life and our relation to our environment. Given the pervasiveness of trust in our lives, it comes as a surprise that trust has only very recently started to receive attention in philosophy. Apart from some early consideration on trust amongst friends, on trust in god as well as some contributions regarding the role of trust
in society by Hobbes, Locke and Hume, trust emerged as a topic of philosophical interest only in the last decades of the 20th century. As pervasive trust appears as a phenomenon, as elusive it seems as a concept. What is trust? Is it a belief, an expectation, an attitude or an emotion? Can trust be willed or can I merely decide to act as if I trusted? Moreover, while the intrinsic as well as the instrumental value of trust for cooperation and social life is almost commonsensical, trust always carries the risk of being unwarranted. Trusting those who are not worthy of our trust can lead to exploitation and betrayal. Yet, not trusting those who would be trustworthy can also be a mistake and cause harm. It has been particularly feminist scholars, who have emphasizes the janus-faced nature of trust. How trust is defined and characterized depends strongly on the examples chosen. It makes a difference whether we analyze trust relations between children and their parents, between humans of equal power, between friends, lovers or strangers. Trust in other persons differs from trust in groups, trust in a specific representative of the state differs from trust in more abstract entities such as governments, democracy or society. Technology is yet another important if neglected patient of trust as well as a mediator of many human-to-human trust relations in our contemporary world. Instead of distinguishing proper and improper uses of the term trust, we should carefully attend to these different meanings of the word “trust” to provide a rich and multi-facetted perspective on this complex and important phenomenon."

Research has revealed service industries’ benefits from customer trust including positive effects on commitment, loyalty, sales effectiveness, and collaborative, cooperative, and successful exchange relationships. Yet, despite the relevance of customer trust, gaps remain in our understanding regarding its implications and effective management. Commencing with a consideration of the theoretical foundations of trust, this theoretical review paper highlights the key trust theories synthesising service industries and management literatures on trust, its levels, development, violations and repair. Drawing on this, recommendations are offered for scholars regarding future research, and for service firms and their representatives regarding enabling customer trust.

This research aims to develop a model of trust and reputation that will ensure good interactions amongst software agents in large scale open systems. The following are key drivers for our model: (1) agents may be self-interested and may provide false accounts of experiences with other agents if it is beneficial for them to do so; (2) agents will need to interact with other agents with which they have little or no past experience. Against this background, we have developed TRAVOS (Trust and Reputation model for Agentbased Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents. When there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate.

Many historians prefer to take mercantile trust as a given, particularly when it comes to networks based on religious affiliation, ethnicity and kin ties.1 Too often, trust is taken as an inherent-indeed, defining-quality of a trading diaspora. This chapter seeks to escape that over simplified explanatory trap, by looking beyond the standard models for understanding ethnoreligious merchant networks. It examines the precise mechanisms of establishing creditworthiness within a trading diaspora, with a primary focus on the making and unmaking of merchants' reputa tions. It reveals that trust within Armenian merchant networks depended on the complex interplay of information networks and enforcement mechanisms, as well as grounding ties of kinship, ethnicity and religion.

Hosting the Olympic Games is not merely a sporting endeavor, but is an undertaking that is fraught with political, socio-cultural and economic pressures. Aligning these pressures with reputational issues for the multitude of event stakeholders, most notably the bidding city, if not properly managed as a mega project, can create a "perfect storm", which could result in poor decision making, destructive loss of reputational capital for stakeholders (particularly the host city) and potentially the delivery of a failed Olympic Games. Mega project management, and particularly the management of mega events, deserves special attention in the context of reputation. This is because they come under considerable public scrutiny. For example, the Olympic Games require public sector support and fiscal involvement, without which a city could not bid to host the games (Mules and Dwyer 2005, 350). In fact, due to rising costs of hosting the games, coupled with the growth in interest at an international level, the International Olympic Committee (IOC) cannot, more than ever, risk failure in the delivery of an Olympic Games. Consequently, the IOC decided that governments must act as financial guarantor when a city bids to host the Olympics (Lenskyj 2004, 370). Factors which have historically impacted negatively on the reputation of Olympic stakeholders, the IOC and host cities in particular, include bribery and inequity in the bidding process, human rights issues, international terrorism, poor fiscal forecasting, deficiencies in infrastructure development, optimism-bias, the promise-performance gap and games boycotts. On the positive side have been a limited number of games that have demonstrated successful delivery of the games, profitability and medium to long-term regional sustainable infrastructure development, with corresponding gain in reputational capital to the host city. This paper thus examines reputational issues which have encompassed the Olympics of the past by examining lessons from a review of documented Olympic Games since 1960. The outcomes of the research carry significant lessons for future Olympic host cities, most immediately London 2012 and Rio de Janeiro 2016, and have broader implications for all mega-sporting events.

What is the state of the research on crowdsourcing for policymaking? This article begins to answer this question by collecting, categorizing, and situating an extensive body of the extant research investigating policy crowdsourcing, within a new framework built on fundamental typologies from each field. We first define seven universal characteristics of the three general crowdsourcing techniques (virtual labor markets, tournament crowdsourcing, open collaboration), to examine the relative trade-offs of each modality. We then compare these three types of crowdsourcing to the different stages of the policy cycle, in order to situate the literature spanning both domains. We finally discuss research trends in crowdsourcing for public policy and highlight the research gaps and overlaps in the literature.

Il contributo affronta il tema della Valutazione della Qualità della Ricerca (VQR) sotto il particolare profilo della reputazione, inquadrandolo come vero e proprio “sistema reputazionale”. Dopo aver ripercorso l’evoluzione dei sistemi valutativi della qualità della ricerca in Italia, l’analisi si concentra sull’ultimo esercizio di valutazione – la VQR 2011-2014 – approfondendone, in chiave critica e con particolare riferimento all’area giuridica, criteri valutativi e modalità. Infine, indagati i criteri di aggregazione dei risultati della valutazione dei singoli prodotti della ricerca, sia a livello di dipartimento sia di ateneo, vengono messe in luce le dirette conseguenze dei risultati della VQR in punto di finanziamento e i collaterali effetti distorsivi.

A poco più di un anno dai risultati della Valutazione della Qualità della Ricerca relativa al periodo 2011-2014, iniziano ad essere pubblicate le prime decisioni in cui il sistema reputazione applicato alla ricerca universitaria, vale a dire la Valutazione della Qualità della Ricerca (VQR), è stato posto all'attenzione del Giudice amministrativo.
Commento a TAR Lazio, sez. III, 24 novembre 2017, n. 11691 e a TAR Sardegna, sez. I, 10 gennaio 2018, n. 10.

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items, hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

"Computational trust modeling is a research field with a fast growing development since the last decade, mainly in the scientific area of distributed artificial intelligence and multi-agent systems, and its potential applicability spreads from social networks to distributed resource sharing and electronic markets. The earliest approaches to computational trust addressed the development of algorithms to aggregate the evidence on any given agent under
evaluation into an estimated score of this agent’s trustworthiness. More recently, the research on computational trust has shifted to the inclusion of third-party information about the trustee under evaluation, including opinions and reputation. However, one important aspect of computational trust has being neglected all these years by the majority of the scholars on computational trust, with a few relevant exceptions: trust is a social construct with a cognitive and an emotional account, and it strongly depends on the relationship existing between the agent that trusts and the one that is trusted.
In this thesis, we address the topic of social trust and its consideration for application in computational trust. We first present a thorough multidisciplinary view of trust, and derive important propositions that will guide our work throughout the thesis. Based on these propositions, we present the SOLUM model, our proposal to computational trust comprised of two distinct parts. The first part is a general framework of computational trust that is based on two fundamental characteristics of trust: trust is more than trustworthiness and other important antecedents to trust, such as the truster’s disposition and emotional state, must be considered when estimation the truster’s trust; and trustworthiness is a multi-dimensional construct that includes the ability, integrity, and benevolence dimensions. This framework can be instantiated and applied to a wide range of trust-based problems and applications, and is seen here as the first main contribution of this thesis. The second part of the SOLUM model includes a set of distinct computational components that (partially) instantiate the framework, namely: Sinalpha, Contextual Fitness, Social Tuner, and Integrity Tuner. We propose the use of specific techniques to extract information about the individual dimensions of the agents’ trustworthiness from the set of structured evidence available on these agents, which may be scarce. This constitutes an innovative view over computational trust, and is the second main contribution of this thesis.
We evaluated our approach through experimental simulation. The results of our experiments allowed us to conclude that it is possible to improve in a relevant way the reliability of the trustworthiness estimations – for the same set of evidence – using the proposed techniques. Consequently, our approach contributes for more informative and secure decisions, in all domains where computer-based trust decisions are needed."

What are the similarities and differences between crowdsourcing and sharing economy? What factors influence their use in developing countries? In light of recent developments in the use of IT-mediated technologies, such as crowdsourcing and the sharing economy, this manuscript examines their similarities and differences, and the challenges regarding their effective use in developing countries. We first examine each individually and highlight different forms of each IT-mediated technology. Given that crowdsourcing and sharing economy share aspects such as the use of IT, a reliance on crowds, monetary exchange, and the use of reputation systems, we systematically compare the similarities and differences of different types of crowdsourcing with the sharing economy, thus addressing a gap in the current literature. Using this knowledge, we examine the different challenges faced by developing countries when using crowdsourcing and the sharing economy, and highlight the differences in the applicability of these IT-mediated technologies when faced with specific development issues.

The article is devoted to the analysis of the use of blockchain technology for self-organization of network communities. Network communities are characterized by the key role of trust in personal interactions, the need for repeated interactions, strong and weak ties within the network, social learning as the mechanism of self-organization. Therefore, in network communities reputation is the central component of social action, assessment of the situation, and formation of the expectations. The current proliferation of virtual network communities requires the development of appropriate technical infrastructure in the form of reputation systems-programs that provide calculation of network members reputation and organization of their cooperation and interaction. Traditional reputation systems have vulnerabilities in the field of information security and prevention of abusive behavior of agents. Overcoming these restrictions is possible through integration of reputation systems and blockchain technology that allows to increase transparency of reputation assessment system and prevent attempts of manipulation the system and social engineering. At the same time, the most promising is the use of blockchain-oracles to ensure communication between the algorithms of blockchain-based reputation system and the external information environment. The popularization of blockchain technology and its implementation in various spheres of social management, production control, economic exchange actualizes the problems of using digital technologies in political processes and their impact on the formation of digital authoritarianism, digital democracy and digital anarchism. The paper emphasizes that blockchain technology and reputation systems can equally benefit both the resources of government control and tools of democratization and public accountability to civil society or even practices of avoiding government. Therefore, it is important to take into account the problems of political institutionalization, path dependence and the creation of differentiated incentives as well as the technological aspects.

This thesis introduced two novel reputation models to generate accurate item reputation scores using ratings data and the statistics of the dataset. It also presented an innovative method that incorporates reputation awareness in recommender systems by employing voting system methods to produce more accurate top-N item recommendations. Additionally, this thesis introduced a personalisation method for generating reputation scores based on users' interests, where a single item can have different reputation scores for different users. The personalised reputation scores are then used in the proposed reputation-aware recommender systems to enhance the recommendation quality.

Cloud Computing is an emerging computing paradigm. It shares massively scalable, elastic resources (e.g., data, calculations, and services) transparently among the users over a massive network. The Cloud market is growing rapidly and bringing up numerous research challenges. This paper provides a landscape of Cloud Computing and its research challenges, especially considering the areas of service selection, quality assurance of Cloud services, and trust establishment in Cloud environments. As the latter is known to be one of the major challenges of Cloud Computing, We also provide an overview of the important aspects that need to be considered when integrating trust and reputation concepts into Cloud Computing.

The paper introduces the semiotic definitions of the concepts of textual enunciation, resonance, and reputation, applies them to the analysis of the evolution of the cultural role plaid by Edmondo De Amicis’s novel Heart in both the past and the present-day Italian semiosphere, then compares such evolution with that of other cultural products (such as commercial brands), and underlines the influence of communication media in configuring these semiotic dynamics. The paper ends with some hypotheses on the impact of digitalization and ICTs on the semiotic processes of reputation, and suggests the need to develop a new epidemiology of meaning.

Mobile Ad hoc Networks (MANETs) have lots of applications. Due to the features of open medium, absence of infrastructure, dynamic changing network topology, cooperative algorithms, lack of centralized monitoring and management point, resource constraints and lack of a clear line of defense, these networks are vulnerable to attacks. A vital problem that must be solved in order to realize these

In service-oriented computing, selection of an appropriate web service is a challenging problem. The more services are available, the more difficult is the service selection. Trust and reputation mechanisms have been used to filter good services from bad ones. Trust and reputation system of web services can often be modeled as a multi-agent system where agents are used to manage and reason about trust and reputation on behalf of their users providing or consuming services. In this paper, we propose a trust establishment framework for such a system based on direct experience and recommended trust. While making trust based decision of accessing a web service from a service provider, the value of the trust on which the decision is based is predicted from the direct trust values in the past. If the direct trust values in the past are not available, a recommended trust value is established by mixing the opinions obtained from a number of so-called "experts". These experts are trained to learn regions of different volatilities in a time series constructed from the recommended trust values. The dynamics between the experts and the mixing weights are obtained using a coarse-grain Hidden Markov Model.

—VANETs (Vehicular Ad hoc Networks) são redes de comunicação veiculares em que os participantes não dependem necessariamente de uma infraestrutura de pontos de acesso central para se conectarem. Nos projetos de VANETs atualmente em fase de estudos e realização de testes de campo, um aspecto importante é a segurança da informação nas mensagens trocadas entre os nós de comunicação participantes. Vários mecanismos estão sendo propostos para compor um sistema de confiança nessas redes, tais como: autenticação dos nós, plausibilidade das informações e sistemas de reputação. Este artigo apresenta um survey sobre sistemas de reputação em redes VANET e resultados de simulações de um mecanismo de reputação simplificado para fins didáticos. Os resultados mostram que devido às características particulares das redes VANET, a utilização de mecanismos centralizados de reputação pode contribuir para a confiança no sistema.

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Punishment promotes contributions to public goods, but recent evidence suggests that its effectiveness varies across societies. Prior theorizing suggests that cross-societal differences in trust play a key role in determining the effectiveness of punishment, as a form of social norm enforcement, to promote cooperation. One line of reasoning is that punishment promotes cooperation in low-trust societies, primarily because people in such societies expect their fellow members to contribute only if there are strong incentives to do so. Yet another line of reasoning is that high trust makes punishment work, presumably because in high-trust societies people may count on each other to make contributions to public goods and also enforce norm violations by punishing free riders. This poses a puzzle of punishment: Is punishment more effective in promoting cooperation in high- or low-trust societies? In the present article, we examine this puzzle of punishment in a quantitative review of 83 studies involving 7,361 participants across 18 societies that examine the impact of punishment on cooperation in a public goods dilemma. The findings provide a clear answer: Punishment more strongly promotes cooperation in societies with high trust rather than low trust.

We seek to develop a better understanding of interpersonal trust by bridging the gap between two heretofore distinct paradigms of trust. One paradigm views trust in terms of two dimensions: cognition- and affect-based. The other paradigm views trust as being distinct from trustworthiness, which has four dimensions: ability, behavioral integrity, benevolence, and values congruence. Currently, theoretical consensus is lacking about the antecedents of cognition- and affect-based trust in the first paradigm that incorporates insights from research on trustworthiness in the second paradigm. We show that this lack of consensus is problematic for internal knowledge development and external knowledge expansion. Thus, we join both paradigms by theorizing that ability and behavioral integrity are the most important predictors of cognition-based trust, whereas benevolence and values congruence are the most important predictors of affect-based trust. Across two samples, we found that our predictions were largely supported. Based on relative weights analysis, ability and behavioral integrity were more important than values congruence in predicting cognition-based trust, and benevolence was more important than ability in predicting affect-based trust. Furthermore, we found evidence that these relationships were largely robust to changes in the referent of analysis.

The Internet has caused a revolution in trading. Especially cheap items are now easy to buy and sell on the Internet. As a consequence, sellers nowadays offer a wide range of products on the web, creating an abundance of choice for consumers. Consumers have the opportunity to browse on different auction sites for the item they really want. Along with

It is important to enable peers to represent and update their trust in other peers in open networks for sharing files, and especially services. In this paper, we propose a Bayesian network-based trust model and a method for building reputation based on recommendations in peer-topeer networks. Since trust is multi-faceted, peers need to develop differentiated trust in different aspects of other peers' capability. The peer's needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer's capability or in multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. The evaluation of the model using a simulation shows that the system where peers communicate their experiences (recommendations) outperforms the system where peers do not share recommendations with each other and that a differentiated trust adds to the performance in terms of percentage of successful interactions.

We provide theoretical and empirical analysis of a selling mechanism used by an Internet web-site that combines important features of auctions and gambling. This is the first analysis of such a selling mechanism, which provides insights into how the two kinds of behavior might be related in real life. The winner of the object is the bidder with the highest bid not submitted by any other bidder. In the equilibrium of our game theoretical model, each bid made with positive probability yields the same probability of winning. Bidders are more likely to submit higher bids, and the bid distribution does not depend on the value of the object or the highest bid allowed if one controls for the number of bidders. Most of these key theoretical predictions are confirmed by the data.

The majority of trust models consider two types of knowledge in estimating the trustworthiness of a trustee in an interaction: experiences and recommendations. However, this leads to a nested trust problem; how could we trust the recommendations? Even when the recommenders are not deceptive, there is still a trust related problem due to the subjectivity of human judgment. This paper describes a missing part of the existing trust management models: handling the subjectivity of recommendations. Our approach is based on the idea that a recommender's judgment method can be inferred and the recommended entity can be (re)evaluated according to the value system of the truster who is about to make a decision. Extraction of the judgment method involves abductive reasoning which is implemented in the proposed account using subjective logic. This approach has been quantitatively compared with two other methods. Our experiments show that our proposed solution outperforms an extended version of the "Beta trust model", a trust model without subjectivity elimination. Our suggested method for trust and reputation systems may also be applied to other systems that include a rating mechanism such as recommender systems.

A direct downconversion receiver implemented in 0.13 µm 1P8M process is presented. The circuit is formed by a single-end LNA, an active balun for conversion into balanced mode, a quadrature double-balanced passive switch mixer and a quadrature voltage-controlled oscillator. The receiver operates in the 2.4 GHz ISM band and complies with IEEE 802.15.4 (ZigBee) specifications. The circuit exhibits a very low noise figure of only 2.27 dB and dissipates only 14.6 mW with a 1.2 V supply voltage and is hence suitable for low-power applications.

Trust is a construct of paramount importance in society. Accordingly, computational trust is evolving fast in order to allow trust in artificial societies. Despite the advances in this research field, most computational trust approaches evaluate trust by estimating the trustworthiness of the agents under evaluation (the trustees), without however distinguishing between the different dimensions of trustworthiness, such as ability and benevolence. In this paper, we propose different techniques to extract the ability of the trustee in the task at hand and to infer the benevolence of the trustee toward the truster when the trust judgment is made. Moreover, we propose to dynamically change the relative importance and impact of both ability and benevolence on the perceived trustworthiness of the trustee, taking into consideration the development of the relationship between the truster and the trustee and the disposition of the truster in the specific situation. Finally, we set an experimental scenario to evaluate our approach. The results obtained from these experiments show that the proposed techniques significantly improve the reliability of the estimation of the trustworthiness of agents.

In this paper, we provide a semantic foundation for trust-related concepts in the light of trust management. We extend our previous work, the Reference Ontology of Trust, to clarify and provide a deeper account of some building blocks of trust, such as beliefs and intentions of a trustor, pieces of evidence that indicate that a trustee is trustworthy (or not), as well as the many factors that influence trust. We illustrate our proposal by instantiating and discussing people's trust in vaccines in the time of COVID-19.

Peer-to-Peer networks are very popular these days due to their use in data and resource sharing. Trust and reputation of a peer not only make it easy to take a decision to ask for resource from the trustworthy node but also provide a way to punish evil peers for ...

In Federated Identity Management (FIM), user administration is decentralized: Service Providers (SPs) can request information about the users from their respective Identity Providers (IDPs). The subsequent processing of this data with respect to service provisioning and various privacy aspects are open research issues. We first specify how SPs can use providerwide and service-specific XACML policies to enforce the required quality for the data delivered by the IDPs. Then, we demonstrate how aspects of trust and reputation management can improve the dynamics of Identity Federations and enhance the end users' privacy. We also extend the identity-centric request-response model of today's FIM protocols by group queries and demonstrate their application. Finally, we introduce our prototype and its integration into the Shibboleth FIM software.

Privacy is of crucial importance in order for agent-based e-commerce applications to be of broad use. Privacy can be enhanced minimizing data identifiability, i.e., the degree by which personal information can be directly attributed to a particular individual. However, minimizing data identifiability may directly impact other crucial issues in agent-based e-commerce, such as accountability, trust, and reputation. In this paper,

We argue that a firm's reputation (i.e., central, enduring, and distinctive corporate associations held by individuals outside of an organization), although under-researched relative to trust, is more important than trust in impacting buyer-supplier relationships. Our conceptualization draws on theories and extant research related to transaction cost economics, information economics, and interfirm trust. The constructs of trust and reputation are distinguished and their relative impacts on relationship commitment and willingness to invest in the future of the relationship are examined. Suggestive empirical evidence is provided from a survey of industrial buyers, and implications and specific directions for future research are discussed.

Failure detection is a crucial service for dependable distributed systems. Traditional failure detector implementations usually target homogeneous and static configurations, as their performance relies heavily on the connectivity of each network node. In this paper we propose a new approach towards the implementation of failure detectors for large and dynamic networks: we study reputation systems as a means to detect failures. The reputation mechanism allows efficient node cooperation via the sharing of views about other nodes. Our experimental results show that a simple prototype of a reputation-based detection service performs better than other known adaptive failure detectors, with improved flexibility. It can thus be used in a dynamic environment with a large and variable number of nodes