MobiRate: making mobile raters stick to their word
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
From pervasive to social computing: algorithms and deployments
Proceedings of the 2009 international conference on Pervasive services
Multimodal security enforcement framework for wireless ad hoc networks
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
Design and implementation of S-MARKS: A secure middleware for pervasive computing applications
Journal of Systems and Software
Trust based security auto-configuration for smart assisted living environments
Proceedings of the 2nd ACM workshop on Assurable and usable security configuration
A middleware service for pervasive social networking
M-PAC '09 Proceedings of the International Workshop on Middleware for Pervasive Mobile and Embedded Computing
Journal of Systems and Software
Architecture and implementation of a trust model for pervasive applications
Journal of Mobile Multimedia
ACM SIGAPP Applied Computing Review
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Handheld devices have become sufficiently powerful that it is easy to create, disseminate, and access digital content (e.g., photos, videos) using them. The volume of such content is growing rapidly and, from the perspective of each user, selecting relevant content is key. To this end, each user may run a trust model -a software agent that keeps track of who disseminates content that its user finds relevant. This agent does so by assigning an initial trust value to each producer for a specific category (context); then, whenever it receives new content, the agent rates the content and accordingly updates its trust value for the producer in the content category. However, a problem with such an approach is that, as the number of content categories increases, so does the number of trust values to be initially set. This paper focuses on how to effectively set initial trust values. The most sophisticated of the current solutions employ pre-defined context ontologies, using which initial trust in a given context is set based on that already held in similar contexts. However, universally accepted (and time invariant) ontologies are rarely found in practice. For this reason, we propose a mechanism called TRULLO (TRUst bootstrapping by Latently Lifting cOntext) that assigns initial trust values based only on local information (on the ratings of its user's past experiences) and that, as such, does not rely on third-party recommendations. We evaluate the effectiveness of TRULLO by simulating its use in an informal antique market setting.