4th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Research Article

TRULLO - local trust bootstrapping for ubiquitous devices

  • @INPROCEEDINGS{10.1109/MOBIQ.2007.4451015,
        author={Daniele Quercia and Stephen Hailes and Licia Capra},
        title={TRULLO - local trust bootstrapping for ubiquitous devices},
        proceedings={4th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
        publisher={IEEE},
        proceedings_a={MOBIQUITOUS},
        year={2008},
        month={2},
        keywords={Computational efficiency  Computational modeling  Computer science  Educational institutions  Handheld computers  Mobile handsets  Ontologies  Personal digital assistants  Software agents  Videos},
        doi={10.1109/MOBIQ.2007.4451015}
    }
    
  • Daniele Quercia
    Stephen Hailes
    Licia Capra
    Year: 2008
    TRULLO - local trust bootstrapping for ubiquitous devices
    MOBIQUITOUS
    IEEE
    DOI: 10.1109/MOBIQ.2007.4451015
Daniele Quercia1,*, Stephen Hailes1,*, Licia Capra1,*
  • 1: Department of Computer Science, University College London, London, WC1E 6BT, UK.
*Contact email: D.Quercia@cs.ucl.ac.uk, S.Hailes@cs.ucl.ac.uk, L.Capra@cs.ucl.ac.uk

Abstract

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 predefined 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. We also evaluate the computational cost of a J2ME implementation of TRULLO on a mobile phone.