Collaboration through computation: incorporating trust model into service-based software systems

The open and dynamic nature of service-based software systems necessitates spontaneous and trustworthy interactions between collaborating entities. Service providers are exposed to users spanned across multiple organizational domains, so can be exploited by potentially untrustworthy service requestors. Given that, service providers need to trust requestors before granting them with services. Trust encompasses a number of quality attributes (e.g., security, competence, honesty) and helps in dynamic decision making. In this paper, we present a trust-based service collaboration approach, facilitated by the analysis of service-based interactions between service providers and requestors, and recommendations between service providers. Service providers exchange recommendations to convey their trust on requestors. This collaboration is quantified using our proposed trust model, called CAT, a Context-Aware Trust model based on service-based interactions by considering services as contexts. We identify a number of collaboration-based trust properties including risk and context-awareness and incorporate them in CAT. A context-similarity parameter is introduced to decide on similar services. A time-based ageing parameter is proposed to decrease trust values over time without any further interactions. Direct and indirect recommendations from other service providers are included in total trust calculation, with a path-based ageing parameter applying over indirect recommendations. A mechanism to calculate the accuracy of recommendations is proposed to differentiate between reliable and unreliable recommendations. These calculation schemes are employed in a trust-based service collaboration algorithm to automatically decide on granting services to requestors. The approach is elaborated using examples from file sharing applications, and successfully evaluated by implementing a prototype service-based file sharing grid. This research is partially funded by the Natural Sciences and Engineering Research Council of Canada (NSERC).