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

Trust and Risk Relationship Analysis on a Workflow Basis: A Use Case

Trust and risk are often seen in proportion to each other; as such, high trust may induce low risk and vice versa. However, recent research argues that trust and risk relationship is implicit rather than proportional. Considering that trust and risk are implicit, this paper proposes for the first time a novel approach to view trust and risk on a basis of a W3C PROV provenance data model applied in a healthcare domain. We argue that high trust in healthcare domain can be placed in data despite of its high risk, and low trust data can have low risk depending on data quality attributes and its provenance. This is demonstrated by our trust and risk models applied to the BII case study data. The proposed theoretical approach first calculates risk values at each workflow step considering PROV concepts and second, aggregates the final risk score for the whole provenance chain. Different from risk model, trust of a workflow is derived by applying DS/AHP method. The results prove our assumption that trust and risk relationship is implicit

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

A Formal Model for Trust in Dynamic Networks

We propose a formal model of trust informed by the Global Computing scenario and focusing on the aspects of trust formation, evolution, and propagation. The model is based on a novel notion of trust structures which, building on concepts from trust management and domain theory, feature at the same time a trust and an information partial order

A Wikipedia Literature Review

This paper was originally designed as a literature review for a doctoral dissertation focusing on Wikipedia. This exposition gives the structure of Wikipedia and the latest trends in Wikipedia research

A flexible architecture for privacy-aware trust management

In service-oriented systems a constellation of services cooperate, sharing potentially sensitive information and responsibilities. Cooperation is only possible if the different participants trust each other. As trust may depend on many different factors, in a flexible framework for Trust Management (TM) trust must be computed by combining different types of information. In this paper we describe the TAS3 TM framework which integrates independent TM systems into a single trust decision point. The TM framework supports intricate combinations whilst still remaining easily extensible. It also provides a unified trust evaluation interface to the (authorization framework of the) services. We demonstrate the flexibility of the approach by integrating three distinct TM paradigms: reputation-based TM, credential-based TM, and Key Performance Indicator TM. Finally, we discuss privacy concerns in TM systems and the directions to be taken for the definition of a privacy-friendly TM architecture.\u

Network as a computer: ranking paths to find flows

We explore a simple mathematical model of network computation, based on Markov chains. Similar models apply to a broad range of computational phenomena, arising in networks of computers, as well as in genetic, and neural nets, in social networks, and so on. The main problem of interaction with such spontaneously evolving computational systems is that the data are not uniformly structured. An interesting approach is to try to extract the semantical content of the data from their distribution among the nodes. A concept is then identified by finding the community of nodes that share it. The task of data structuring is thus reduced to the task of finding the network communities, as groups of nodes that together perform some non-local data processing. Towards this goal, we extend the ranking methods from nodes to paths. This allows us to extract some information about the likely flow biases from the available static information about the network.Comment: 12 pages, CSR 200

Modeling social information skills

In a modern economy, the most important resource consists in\ud human talent: competent, knowledgeable people. Locating the right person for\ud the task is often a prerequisite to complex problem-solving, and experienced\ud professionals possess the social skills required to find appropriate human\ud expertise. These skills can be reproduced more and more with specific\ud computer software, an approach defining the new field of social information\ud retrieval. We will analyze the social skills involved and show how to model\ud them on computer. Current methods will be described, notably information\ud retrieval techniques and social network theory. A generic architecture and its\ud functions will be outlined and compared with recent work. We will try in this\ud way to estimate the perspectives of this recent domain