A Conceptual Framework for Trust Models (original) (raw)
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Research Challenges in Information Science, 2021
Evaluating the quality of resources and the reliability of entities in a system is one of the current needs of modern computer systems. This assessment is the result of two concepts that dominate our real life as well as computer systems, which are Trust and Reputation. To measure them, a variety of computational models have been developed to help users make decisions, and to improve interactions with the system and between users. Due to the wide variety of definitions for reputation and trust topics, this paper attempts to unify these definitions by proposing a unique formalization in terms of graphical and textual notations. It introduces also a deep analysis to understand the behavior and the intuition behind each computational model.
Review on Computational Trust and Reputation Models
Artificial Intelligence Review, 2005
The scientific research in the area of computational mechanisms for trust and reputation in virtual societies is a recent discipline oriented to increase the reliability and performance of electronic communities. Computer science has moved from the paradigm of isolated machines to the paradigm of networks and distributed computing. Likewise, artificial intelligence is quickly moving from the paradigm of isolated and non-situated intelligence to the paradigm of situated, social and collective intelligence. The new paradigm of the so called intelligent or autonomous agents and Multi-Agent Systems (MAS) together with the spectacular emergence of the information society technologies (specially reflected by the popularization of electronic commerce) are responsible for the increasing interest on trust and reputation mechanisms applied to electronic societies. This review wants to offer a panoramic view on current computational trust and reputation models.
Integrating Indicators of Trustworthiness into Reputation-Based Trust Models
IFIP Advances in Information and Communication Technology, 2012
Reputation-based trust models are essentially reinforcement learning mechanisms reliant on feedback. As such, they face a cold start problem when attempting to assess an unknown service partner. State-ofthe-art models address this by incorporating dispositional knowledge, the derivation of which is not described regularly. We propose three mechanisms for integrating knowledge readily available in cyber-physical services (e.g., online ordering) to determine the trust disposition of consumers towards unknown services (and their providers). These reputation-building indicators of trustworthiness can serve as cues for trust-based decision making in eCommerce scenarios and drive the evolution of reputation-based trust models towards trust management systems.
MITRA: A Meta-Model for Information Flow in Trust and Reputation Architectures
We propose MITRA, a meta-model for the information flow in (computational) trust and reputation architectures. On an abstract level, MITRA describes the information flow as it is inherent in prominent trust and reputation models from the literature. We therefore can use MITRA to provide a structured comparison of these models in order to give a clear overview of the complex research area. Furthermore, by doing so, we identify interesting new approaches for trust and reputation modeling that so far have not been investigated.
PATROL: a comprehensive reputation-based trust model
International Journal of Internet Technology and Secured Transactions, 2007
In this paper, we present PATROL, a general and comprehensive reputation-based trust model for distributed computing. The proposed model is an enhancement over our previous model, TRUMMAR, and aims at achieving a truly unique model that incorporates most concepts that are essential to determining trust-based decisions. Among the concepts upon which the trust model is based are reputation values, direct experiences, trust in the credibility of a host to give recommendations, decay of information with time based on a dynamic decay factor, first impressions, similarity, popularity, activity, cooperation between hosts, in addition to a hierarchy of host systems. The simulations performed on this model confirm its correctness and its adaptability to different environments and situations.
A Generic Framework for Modeling Decentralized Reputation-based Trust Models
Decentralized applications do not have a single centralized authority that can safeguard peers in the system from malicious attacks. Each peer is autonomous and must adopt measures to protect itself. Reputation-based trust management systems enable peers to develop trust relationships with each other based on their reputations. These trust relationships help a peer determine the trustworthiness of other peers in the system and thus help safeguard itself from malicious peers. A number of decentralized reputation-based trust models have been discussed in the literature. However, a common understanding of what a trust model is and what its constituents are has been lacking. Further, there has been little work directed towards the creation of a generic framework that will comprehensively help to express existing reputation models as well as create new models. In this paper, we present the 4C framework for modeling decentralized reputation-based trust models. The 4C framework builds upon the common functional aspects of reputation models and consists of four generic sub-models that help to express reputation models. The 4C framework is described using an XML-based schema that makes the 4C framework extensible for enabling the expression of new types of reputation models in the future. We have evaluated the 4C framework by using it to describe three decentralized reputation models and have built a 4C editor to facilitate the generation of XML-based descriptions of reputation models. We have also demonstrated how these trust model descriptions can be leveraged to aid the construction of decentralized trust-enabled applications.
A comprehensive reputation-based trust model for distributed systems
Workshop of the 1st International Conference on Security and Privacy for Emerging Areas in Communication Networks, 2005., 2005
In this paper, we present a general and comprehensive reputation-based trust model for distributed computing. The proposed model is an enhancement over our previous model, TRUMMAR, and aims at achieving a truly unique model that incorporates most concepts that are essential to determining trust-based decisions. Among the concepts upon which the trust model is based are reputation values, direct experiences, trust in the credibility of a host to give recommendations, decay of information with time based on a dynamic decay factor, first impressions, similarity, popularity, activity, cooperation between hosts, in addition to a hierarchy of host systems. The simulations performed on this model confirm its correctness and its adaptability to different environments and situations. [14] Proposed model Hierarchy of trust X X X Position of member in community X X X X
A classification scheme for trust functions in reputation-based trust management
2004
Reputation is an important means to establish trust in decentralized environments such as the Semantic Web. In reputation-based trust management, an entity's reputation is usually built on feedback from those who have direct interactions with the entity. A trust function is used to infer one's trustworthiness based on such feedback. Many trust functions have been proposed in the literature. They are typically designed for specific application domains, thus differ in a variety of aspects, including trust inference methodologies, complexity and accuracy. In this paper, we propose a classification scheme for trust functions, which will help the systematic analysis and selection of trust functions for particular applications.
A computational model of trust and reputation
2002
Despite their many advantages, e-Businesses lag behind brick and mortar businesses in several fundamental respects. This paper concerns one of these: relationships based on trust and reputation. Recent studies on simple reputation systems for e-Businesses such as eBay have pointed to the importance of such rating systems for deterring moral hazard and encouraging trusting interactions. However, despite numerous studies on trust and reputation systems, few have taken studies across disciplines to provide an integrated account of these concepts and their relationships. This paper first surveys existing literatures on trust, reputation and a related concept: reciprocity. Based on sociological and biological understandings of these concepts, a computational model is proposed. This model can be implemented in a real system to consistently calculate agents' trust and reputation scores.