QUATRO is an on-going EC-funded project which aims to provide a common vocabulary and machine readable schema for quality labeling of Web content, as well as ways to automatically show the contents of the label(s) found in a Web resource, and functionalities for checking the validity of these labels. The paper presents the QUATRO processes for label validation and user notification, and outlines the architecture of QUATRO system.
Web spamming describes behavior that attempts to deceive search engine’s ranking algorithms. TrustRank is a recent algorithm that can combat web spam by propagating trust among web pages. However, TrustRank propagates trust among web pages based on the number of outgoing links, which is also how PageRank propagates authority scores among Web pages. This type of propagation may be suited for propagating authority, but it is not optimal for calculating trust scores for demoting spam sites. In this paper, we propose several alternative methods to propagate trust on the web. With experiments on a real web data set, we show that these methods can greatly decrease the number of web spam sites within the top portion of the trust ranking. In addition, we investigate the possibility of propagating distrust among web pages. Experiments show that combining trust and distrust values can demote more spam sites than the sole use of trust values.
Social networks are a popular movement on the web. Trust can be used eectively on the Semantic Web as annotations to social relationships. In this paper, we present a two level approach to integrating trust, provenance, and annotations in Semantic Web systems. We describe an algorithm for inferring trust relationships using provenance information and trust annotations in Semantic Web-based social networks. Then, we present two applications that combine the computed trust values with the provenance of other annotations to personalize websites. The FilmTrust system uses trust to compute personalized recommended movie ratings and to order reviews. An open source intelligence portal, Profiles In Terror, also has a beta system that integrates social networks with trust annotations. We believe that these two systems illustrate a unique way of using trust annotations and provenance to process information on the Semantic Web.
We acknowledge the fact that situational details can have impact on the trust that a Trustor assigns to some Trustee. Motivated by that, we discuss and formalize functions for determining context-aware trust. A system implementing such functions takes into account the Trustee’s profile realized by what we call quality attributes. Furthermore, the system is aware of some context attributes characterizing additional aspects of the Trustee, of the Trustor, and of the environment around them. These attributes can also have impact on trustor’s trust formation process. The trust functions are concretized with running examples throughout the paper.
There has been considerable debate about the apparent irrationality of end users in choosing with whom to share information, with much of the discourse crystallized in research on phishing. Designs for security technology in general, anti-spam technology, and anti-phishing technology has been targeted on specific problems with distinct methods of mitigation. In contrasts, studies of human risk behaviors argue that such specific targets for specific problems are unlikely to provide a significant increase in user trust of the internet, as humans lump and generalize. We initially theorized that communications to users need to be less specific to technical failures and more deeply embedded in social or moral terms. Our experiments indicate that users respond more strongly to a privacy policy failure than an arguably more risky technical failure. From this and previous work we conclude that design for security and privacy needs to be more expansive in that there should be more bundling of signals and products, rather than more delineation of problems into those solvable by discrete tools. Usability must be more than the interface design, but rather integrate security and privacy into a
Social networks in which users or agents are connected to other agents and sources by trust relations are an important part of many web applications where information may come from multiple sources. Trust recommendations derived from these social networks are supposed to help agents develop their own opinions about how much they may trust other agents and sources. Despite the recent developments in the area, most of the trust models and metrics proposed so far tend to lose trust-related knowledge. We propose a new model in which trust values are derived from a bilattice that preserves valuable trust provenance information including partial trust, partial distrust, ignorance and inconsistency. We outline the problems that need to be addressed to construct a corresponding trust learning mechanism. We present initial results on the first learning step, namely trust propagation through trusted third parties (TTPs).
Search engine bias has been seriously noticed in recent years. Several pioneering studies have reported that bias perceivably exists even with respect to the URLs in the search results. On the other hand, the potential bias with respect to the content of the search results has not been comprehensively studied. In this paper, we propose a two-dimensional approach to assess both the indexical bias and content bias existing in the search results. Statistical analyses have been further performed to present the significance of bias assessment. The results show that the content bias and indexical bias are both influential in the bias assessment, and they complement each other to provide a panoramic view with the two-dimensional representation.
As collaborative repositories grow in popularity and use, issues concerning the quality and trustworthiness of information grow. Some current popular repositories contain contributions from a wide variety of users, many of which will be unknown to a potential end user. Additionally the content may change rapidly and information that was previously contributed by a known user may be updated by an unknown user. End users are now faced with more challenges as they evaluate how much they may want to rely on information that was generated and updated in this manner. A trust management layer has become an important requirement for the continued growth and acceptance of collaboratively developed and maintained information resources. In this paper, we will describe our initial investigations into designing and implementing an extensible trust management layer for collaborative and/or aggregated repositories of information. We leverage our work on the Inference Web explanation infrastructure and exploit and expand the Proof Markup Language to handle a simple notion of trust. Our work is designed to support representation, computation, and visualization of trust information. We have grounded our work in the setting of Wikipedia. In this paper, we present our vision, expose motivations, relate work to date on trust representation, and present a trust computation algorithm with experimental results. We also discuss some issues encountered in our work that we found interesting.
volker.fusenig@uni.lu ABSTRACT Nowadays the concept of trust in computer communications starts to get more and more popular. While the idea of trust in human interaction seems to be obvious and understandable it is very difficult to find adequate and precise definitions of the trust-term. Even more difficult is the attempt to find computable models of trust, particularly if one tries to keep all psycho-sociological morality from the real life out of the model. But, apart of all these problems, some approaches have been introduced with more or less success.
This short paper describes an attack that exploits the online marketplace’s susceptibility to covert fraud, opaqueness of embedded software, and social engineering to hijack account access and ultimately steal money. The attacker introduces a fatal security flaw into a trusted embedded system (e.g. computer motherboard, network interface card, network router, cell phone), distributes it through the online marketplace at a plausible bargain, and then exploits the security flaw to steal information. Unlike conventional fraud, consumer risk far exceeds the price of the good. As proof of concept, the firmware on a wireless home router is replaced by an open source embedded operating system. Once installed, its DNS server is reconfigured to selectively spoof domain resolution. This instance of malicious embedded software is discussed in depth, including implementation details, attack extensions, and countermeasures.
