On the Simulation of Global Reputation Systems

Reputation systems evolve as a mechanism to build trust in virtual communities. In this paper we evaluate different metrics for computing reputation in multi-agent systems. We present a formal model for describing metrics in reputation systems and show how different well-known global reputation metrics are expressed by it. Based on the model a generic simulation framework for reputation metrics was implemented. We used our simulation framework to compare different global reputation systems to find their strengths and weaknesses. The strength of a metric is measured by its resistance against different threat-models, i.e. different types of hostile agents. Based on our results we propose a new metric for reputation systems.Reputation System, Trust, Formalization, Simulation

Asymptotically idempotent aggregation operators for trust management in multi-agent systems

The study of trust management in multi-agent system, especially distributed, has grown over the last years. Trust is a complex subject that has no general consensus in literature, but has emerged the importance of reasoning about it computationally. Reputation systems takes into consideration the history of an entity’s actions/behavior in order to compute trust, collecting and aggregating ratings from members in a community. In this scenario the aggregation problem becomes fundamental, in particular depending on the environment. In this paper we describe a technique based on a class of asymptotically idempotent aggregation operators, suitable particulary for distributed anonymous environments

Flow-based reputation: more than just ranking

The last years have seen a growing interest in collaborative systems like electronic marketplaces and P2P file sharing systems where people are intended to interact with other people. Those systems, however, are subject to security and operational risks because of their open and distributed nature. Reputation systems provide a mechanism to reduce such risks by building trust relationships among entities and identifying malicious entities. A popular reputation model is the so called flow-based model. Most existing reputation systems based on such a model provide only a ranking, without absolute reputation values; this makes it difficult to determine whether entities are actually trustworthy or untrustworthy. In addition, those systems ignore a significant part of the available information; as a consequence, reputation values may not be accurate. In this paper, we present a flow-based reputation metric that gives absolute values instead of merely a ranking. Our metric makes use of all the available information. We study, both analytically and numerically, the properties of the proposed metric and the effect of attacks on reputation values

Knowledge society arguments revisited in the semantic technologies era

In the light of high profile governmental and international efforts to realise the knowledge society, I review the arguments made for and against it from a technology standpoint. I focus on advanced knowledge technologies with applications on a large scale and in open- ended environments like the World Wide Web and its ambitious extension, the Semantic Web. I argue for a greater role of social networks in a knowledge society and I explore the recent developments in mechanised trust, knowledge certification, and speculate on their blending with traditional societal institutions. These form the basis of a sketched roadmap for enabling technologies for a knowledge society

Trust Strategies for the Semantic Web

Everyone agrees on the importance of enabling trust on the SemanticWebto ensure more efficient agent interaction. Current research on trust seems to focus on developing computational models, semantic representations, inference techniques, etc. However, little attention has been given to the plausible trust strategies or tactics that an agent can follow when interacting with other agents on the Semantic Web. In this paper we identify five most common strategies of trust and discuss their envisaged costs and benefits. The aim is to provide some guidelines to help system developers appreciate the risks and gains involved with each trust strategy

Robust Trust Establishment in Decentralized Networks

The advancement in networking technologies creates new opportunities for computer users to communicate and interact with one another. Very often, these interacting parties are strangers. A relevant concern for a user is whether to trust the other party in an interaction, especially if there are risks associated with the interaction. Reputation systems are proposed as a method to establish trust among strangers. In a reputation system, a user who exhibits good behavior continuously can build a good reputation. On the other hand, a user who exhibits malicious behavior will have a poor reputation. Trust can then be established based on the reputation ratings of a user. While many research efforts have demonstrated the effectiveness of reputation systems in various situations, the security of reputation systems is not well understood within the research community. In the context of trust establishment, the goal of an adversary is to gain trust. An adversary can appear to be trustworthy within a reputation system if the adversary has a good reputation. Unfortunately, there are plenty of methods that an adversary can use to achieve a good reputation. To make things worse, there may be ways for an attacker to gain an advantage that may not be known yet. As a result, understanding an adversary is a challenging problem. The difficulty of this problem can be witnessed by how researchers attempt to prove the security of their reputation systems. Most prove security by using simulations to demonstrate that their solutions are resilient to specific attacks. Unfortunately, they do not justify their choices of the attack scenarios, and more importantly, they do not demonstrate that their choices are sufficient to claim that their solutions are secure. In this dissertation, I focus on addressing the security of reputation systems in a decentralized Peer-to-Peer (P2P) network. To understand the problem, I define an abstract model for trust establishment. The model consists of several layers. Each layer corresponds to a component of trust establishment. This model serves as a common point of reference for defining security. The model can also be used as a framework for designing and implementing trust establishment methods. The modular design of the model can also allow existing methods to inter-operate. To address the security issues, I first provide the definition of security for trust establishment. Security is defined as a measure of robustness. Using this definition, I provide analytical techniques for examining the robustness of trust establishment methods. In particular, I show that in general, most reputation systems are not robust. The analytical results lead to a better understanding of the capabilities of the adversaries. Based on this understanding, I design a solution that improves the robustness of reputation systems by using accountability. The purpose of accountability is to encourage peers to behave responsibly as well as to provide disincentive for malicious behavior. The effectiveness of the solution is validated by using simulations. While simulations are commonly used by other research efforts to validate their trust establishment methods, their choices of simulation scenarios seem to be chosen in an ad hoc manner. In fact, many of these works do not justify their choices of simulation scenarios, and neither do they show that their choices are adequate. In this dissertation, the simulation scenarios are chosen based on the capabilities of the adversaries. The simulation results show that under certain conditions, accountability can improve the robustness of reputation systems

On the emergent Semantic Web and overlooked issues

The emergent Semantic Web, despite being in its infancy, has already received a lotof attention from academia and industry. This resulted in an abundance of prototype systems and discussion most of which are centred around the underlying infrastructure. However, when we critically review the work done to date we realise that there is little discussion with respect to the vision of the Semantic Web. In particular, there is an observed dearth of discussion on how to deliver knowledge sharing in an environment such as the Semantic Web in effective and efficient manners. There are a lot of overlooked issues, associated with agents and trust to hidden assumptions made with respect to knowledge representation and robust reasoning in a distributed environment. These issues could potentially hinder further development if not considered at the early stages of designing Semantic Web systems. In this perspectives paper, we aim to help engineers and practitioners of the Semantic Web by raising awareness of these issues

Trusted operational scenarios - Trust building mechanisms and strategies for electronic marketplaces.

This document presents and describes the trusted operational scenarios, resulting from the research and work carried out in Seamless project. The report presents identified collaboration habits of small and medium enterprises with low e-skills, trust building mechanisms and issues as main enablers of online business relationships on the electronic marketplace, a questionnaire analysis of the level of trust acceptance and necessity of trust building mechanisms, a proposal for the development of different strategies for the different types of trust mechanisms and recommended actions for the SEAMLESS project or other B2B marketplaces.trust building mechanisms, trust, B2B networks, e-marketplaces

Trust and reputation management in decentralized systems

In large, open and distributed systems, agents are often used to represent users and act on their behalves. Agents can provide good or bad services or act honestly or dishonestly. Trust and reputation mechanisms are used to distinguish good services from bad ones or honest agents from dishonest ones. My research is focused on trust and reputation management in decentralized systems. Compared with centralized systems, decentralized systems are more difficult and inefficient for agents to find and collect information to build trust and reputation. In this thesis, I propose a Bayesian network-based trust model. It provides a flexible way to present differentiated trust and combine different aspects of trust that can meet agents’ different needs. As a complementary element, I propose a super-agent based approach that facilitates reputation management in decentralized networks. The idea of allowing super-agents to form interest-based communities further enables flexible reputation management among groups of agents. A reward mechanism creates incentives for super-agents to contribute their resources and to be honest. As a single package, my work is able to promote effective, efficient and flexible trust and reputation management in decentralized systems