A survey of trust in computer science and the Semantic Web
Introduction
Trust is a central component of the Semantic Web vision [1], [2], [3]. The Semantic Web stack [3], [4] has included all along a trust layer to assimilate the ontology, rules, logic, and proof layers. Trust often refers to mechanisms to verify that the source of information is really who the source claims to be. Signatures and encryption mechanisms should allow any consumer of information to check the sources of that information. In addition, proofs should provide a tractable way to verify that a claim is valid. In this sense, any information provider should be able to supply upon request a proof that can be easily checked that certifies the origins of the information, rather than expect consumers to have to generate those proofs themselves through a computationally expensive process. The web motto “Anyone can say anything about anything” makes the web a unique source of information, but we need to be able to understand where we are placing our trust.
Trust has another important role in the Semantic Web, as agents and automated reasoners need to make trust judgements when alternative sources of information are available. Computers will have the challenge to make judgements in light of the varying quality and truth that these diverse “open” (unedited, uncensored) sources offer. Today, web users make judgments routinely about which sources to rely on since there are often numerous sources relevant to a given query, ranging from institutional to personal, from government to private citizen, from objective report to editorial opinion, etc. These trust judgements are made by humans based on their prior knowledge about a source's perceived reputation, or past personal experience about its quality relative to other alternative sources they may consider. Humans also bring to bear vast amounts of knowledge about the world they live in and the humans that populate the web with information about it. In more formal settings, such as e-commerce and e-science, similar judgments are also made with respect to publicly available data and services. All of these important trust judgments are currently in the hands of humans. This will not be possible in the Semantic Web, where humans will not be the only consumers of information. Agents will need to automatically make trust judgments to choose a service or information source while performing a task. Reasoners will need to judge which of the many information sources available, at times contradicting one another, are more adequate for answering a question. In a Semantic Web where content will be reflected in ontologies and axioms, how will a computer decide what sources to trust when they offer contradictory information? What mechanisms will enable agents and reasoners to make trust judgments in the Semantic Web?
Trust is not a new research topic in computer science, spanning areas as diverse as security and access control in computer networks, reliability in distributed systems, game theory and agent systems, and policies for decision making under uncertainty. The concept of trust in these different communities varies in how it is represented, computed, and used. While trust in the Semantic Web presents unique challenges, prior work in these areas is relevant and should be the basis for future research.
This paper provides an overview of trust research in computer science relevant to the Semantic Web. We focus on relating how different areas define and use trust in a variety of contexts. The paper begins with a general discussion and definitions of trust from the literature. It describes reputation and policies as two broad categories of research to model trust. It then discusses a third category of trust research in designing general computational models of trust. The fourth and final category of research surveyed is trust in information sources. Along the way, we discuss the relevance of the work presented to ongoing and future Semantic Web research.
Section snippets
Modeling and reasoning about trust
Many have recognized the value of modeling and reasoning about trust computationally. A wide of variety of literature now exists on trust, ranging from specific applications to general models. However, as many authors in the field have noted, the meaning of trust as used by each researcher differs across the span of existing work. In order to give the reader a reference point for understanding trust, we offer three general definitions from existing research. The first definition, from Mui et
Policy-based trust
This section summarizes work using policies to establish trust. Policies allow the expression of when, for what, and even how to determine trust in an entity.
Reputation-based trust
Reputation-based trust uses personal experience or the experiences of others, possibly combined, to make a trust decision about an entity. This section explores work in reputation-based trust, a well-defined area of trust research in computer science.
General models of trust
This section summarizes work that presents a broader view on models of trust and the properties of trust. Work in multiple, differing fields is presented, as it is relevant to and frequently cited by computer scientists.
Trust in information resources
This section summarizes relevant work in web and document retrieval, information filtering, representing the sources of information as its provenance trail, and other factors in trusting content of information resources.
Discussion
Trust has been studied in social sciences, business and management, and psychology, before it became central to computer science research. Considering the research we have reviewed, there are several dimensions to describe trust:
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Target. The entity, which is being evaluated or given trust varies with the perspective of the problem. Users are the target of trust in access control systems. Networks are trusted by agents or users when using communication channels. When seeking a reliable service,
Conclusions
Trust research in the Semantic Web poses new challenges that can be better met by building on the diverse but significant body of work in modeling trust in computer science. In this paper, we have identified four broad categories of existing work in trust and given a brief overview of literature in each category. We have discussed the relevance of each of these areas to important aspects of ongoing and future Semantic Web research.
Acknowledgements
We would like to thank the anonymous reviewers for their valuable comments and feedback on this work. We gratefully acknowledge support from the US Air Force Office of Scientific Research (AFOSR) with grant number FA9550-06-1-0031.
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