http://extev.syros.aegean.gr/papers/J50.pdf

Addressing cloud computing security issues

Web-based social networks have become popular as a medium for disseminating information and connecting like-minded people. The public accessibility of such networks with the ability to share opinions, thoughts, information, and experience offers great promise to enterprises and governments. In addition to individuals using such networks to connect to their friends and families, governments and enterprises have started exploiting these platforms for delivering their services to citizens and customers. However, the success of such attempts relies on the level of trust that members have with each other as well as with the service provider. Therefore, trust becomes an essential and important element of a successful social network. In this article, we present the first comprehensive review of social and computer science literature on trust in social networks. We first review the existing definitions of trust and define social trust in the context of social networks. We then discuss recent works addressing three aspects of social trust: trust information collection, trust evaluation, and trust dissemination. Finally, we compare and contrast the literature and identify areas for further research in social trust.

A survey of trust in social networks

The development and standardization of semantic web technologies has resulted in an unprecedented volume of data being published on the Web as Linked Data (LD). However, we observe widely varying data quality ranging from extensively curated datasets to crowdsourced and extracted data of relatively low quality. In this article, we present the results of a systematic review of approaches for assessing the quality of LD. We gather existing approaches and analyze them qualitatively. In particular, we unify and formalize commonly used terminologies across papers related to data quality and provide a comprehensive list of 18 quality dimensions and 69 metrics. Additionally, we qualitatively analyze the 30 core approaches and 12 tools using a set of attributes. The aim of this article is to provide researchers and data curators a comprehensive understanding of existing work, thereby encouraging further experimentation and development of new approaches focused towards data quality, specifically for LD.

http://www.semantic-web-journal.net/system/files/swj773.pdf

Quality assessment for Linked Data: A Survey

Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user maintains trusts in a small number of other users. We then compose these trusts into trust values for all other users. The result of our computation is not an agglomerate "trustworthiness" of each user. Instead, each user receives a personalized set of trusts, which may vary widely from person to person. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise.

Trust management for the Semantic Web

The patent describes a single location and application on a network where a user can organize public, group, and private/personal information and have this single, location accessible to the public. A new, ontology-driven portal that organizes all three categories of data according to various “facets” using underlying ontologies to define each “facet” and wherein any type of information can be classified and linked to other types of information is disclosed. An application that enables a user to effectively utilize and manage knowledge and data the user posses and allows other users to effectively and seamlessly benefit from the user's knowledge and data over a computer network is also disclosed. A method of processing content created by a user utilizing a semantic, ontology-driven portal on a computer network is described. The semantic portal application provides the user with a content base, such as a semantic form or meta-form, for creating a semantic posting. The semantic portal utilizes a knowledge data structure, such as a taxonomy or ontology, in preparing a semantic posting based on the information provided by the user via the content base. The semantic portal application prepares a preview of a semantic posting for evaluation by the user. The semantic posting is then either modified by the user or accepted and posted by the user for external parties to view.

Semantic web portal and platform

Trust is an integral part of the Semantic Web architecture. While most prior work focuses on entity-centered issues such as authentication and reputation, it does not model the content, i.e. the nature and use of the information being exchanged. This paper discusses content trust as an aggregate of other trust measures that have been previously studied. The paper introduces several factors that users consider in deciding whether to trust the content provided by a Web resource. Many of these factors are hard to capture in practice, since they would require a large amount of user input. Our goal is to discern which of these factors could be captured in practice with minimal user interaction in order to maximize the system's trust estimates. The paper also describes a simulation environment that we have designed to study alternative models of content trust.

/pdf/towards-content-trust-of-web-resources-1la16i46mp.pdf

Towards content trust of web resources

Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the SemanticWeb, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.

/pdf/a-survey-of-trust-in-computer-science-and-the-semantic-web-3flj2cirb7.pdf

A Survey of Trust in Computer Science and the Semantic Web

https://www.isi.edu/~gil/papers/jws-trust-07.pdf

A survey of trust in computer science and the Semantic Web

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Towards content trust of web resources

Towards content trust of web resources

A Survey of Trust in Computer Science and the Semantic Web

A survey of trust in computer science and the Semantic Web