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Developing a trust model for pervasive computing based on Apriori association rules learning and Bayesian classification

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Abstract

Pervasive computing is one of the latest and more advanced paradigms currently available in the computers arena. Its ability to provide the distribution of computational services within environments where people live, work or socialize leads to make issues such as privacy, trust and identity more challenging compared to traditional computing environments. In this work, we review these general issues and propose a pervasive computing architecture based on a simple but effective trust model that is better able to cope with them. The proposed architecture combines some artificial intelligence techniques to achieve close resemblance with human-like decision making. Accordingly, Apriori algorithm is first used in order to extract the behavioral patterns adopted from the users during their network interactions. Naïve Bayes classifier is then used for final decision making expressed in term of probability of user trustworthiness. To validate our approach, we applied it to some typical ubiquitous computing scenarios. The obtained results demonstrated the usefulness of such approach and the competitiveness against other existing ones.

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Authors and Affiliations

  1. Department of Science and Technology, University of Sannio, Via dei Mulini 59A, 82100, Benevento, Italy

    Gianni D’Angelo & Salvatore Rampone

  2. Department of Computer Science, University of Salerno, Via Giovanni Paolo II 132, 84084, Fisciano, SA, Italy

    Francesco Palmieri

Authors
  1. Gianni D’Angelo
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  2. Salvatore Rampone
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  3. Francesco Palmieri
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Correspondence to Gianni D’Angelo.

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There are no authors’ conflicts of interest directly or indirectly related to this research work that can potentially influence or impart bias on it. Furthermore, the work does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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D’Angelo, G., Rampone, S. & Palmieri, F. Developing a trust model for pervasive computing based on Apriori association rules learning and Bayesian classification. Soft Comput 21, 6297–6315 (2017). https://doi.org/10.1007/s00500-016-2183-1

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