When users need to perform a digital activity, they evaluate available systems according to their functionality, ease of use, QoS, and/or economical aspects. Recently, trust has become another key factor for such evaluation. Two main issues arise in the trust management research community. First, how to define the trust in an entity, knowing that this can be a person, a digital or a physical resource. Second, how to evaluate such value of trust in a system as a whole for a particular activity. Defining and evaluating trust in systems is an open problem because there is no consensus on the used approach. In this work we propose an approach applicable to any kind of system. The distinctive feature of our proposal is that, besides taking into account the trust in the different entities the user depends on to perform an activity, it takes into consideration the architecture of the system to determine its trust level. Our goal is to enable users to have a personal comparison between different systems for the same application needs and to choose the one satisfying their expectations. This paper introduces our approach, which is based on probability theory, and presents ongoing results.

Abstract. Recently, trust emerged as a momentous aspect to evaluate resources, services or persons. In our work, the trust notion focuses on a system as a whole and from the point of view of a particular user to do a particular digital activity as editing a document, mailing, chatting, etc. Our general goals are (i) to enable users to have a personal comparison of applications allowing them to do an activity such that they can choose the one satisfying their personal expectations and (ii) to know how trustworthy their system is to do a particular activity (all applications together). We consider a system as a graph composed of paths where the source is a person and the target is a final application or data. We consider that trust in a system depends on its architecture and we identify two problems (i) how to evaluate trust in a graph having dependent paths i.e., paths having common nodes, and (ii) how to express and deal with uncertainty in evaluating trust in a system. Concerning the first problem, trust approaches based on graphs have been proposed in the domain of social networks. Their solution for dependent paths is either removing paths or just choosing one of them what causes loss of information. Considering the second problem, subjective logic emerged to express trust as a subjective opinion with a degree of uncertainty. In this paper we present SUBJECTIVETRUST, an approach that relies on subjective logic to evaluate trust in distributed systems. It proposes two solutions to treat dependent paths and takes into account the shape of the system architecture in trust evaluation. We analyze SUBJECTIVETRUST in a series of experiments that show its accuracy.

Multi-synchronous collaboration allows people to work concurrently on copies of a shared document which generates divergence. Divergence awareness allows to localize where divergence is located and estimate how much divergence exists among the copies. Existing divergence awareness metrics are highly coupled to their original applications and can not be used outside their original scope. In this paper, we propose the SCHO ontology: a unified formal ontology for constructing and sharing the causal history in a distributed collaborative system. Then we define the existing divergence metrics in a declarative way based on this model. We validate our work using real data extracted from software engineering development projects. createPull(name : String, pushID : int) :PullFeed(name); call Pull(name);

Everyday, people use more and more digital resources (data, application systems, Internet, etc.) for all aspects of their life, like financial management, private exchanges, collaborative work, etc. This leads to non-negligible dependences on the digital distributed resources that reveal strong reliance at the social level. Users are often not aware of their real autonomy regarding the management of their digital resources. People underestimate social dependences generated by the system they use and the resulting potential risks. We argue that it is necessary to be aware of some key aspects of system's architectures to be able to know dependences. This work proposes SOCIOPATH, a generic meta-model to derive dependences generated by system's architectures. It focuses on relations, like access, control, ownership among different entities of the system (digital resources, hardware, persons, etc.). Enriched with deduction rules and definitions, SOCIOPATH reveals the dependence of a person on each entity in the system. This meta-model can be useful to evaluate a system, as a modeling tool that bridges the gap between the digital and the social worlds.