Conceptual framework for dynamic trust monitoring and prediction

AbstractThe dynamic and collaborative nature of mobile and sensor networks raises the issue of how connected mobile devices can be trusted. Despite the existing security paradigms such as cryptographic mechanisms, and reputation and trust models, the assurance of security remains a problem of such environments. These networks have been plagued with internal security issues such as the presence of untrusted nodes that misbehave. Depending on the proportion of misbehaving nodes and their strategies, attacks such as collusions may occur. By covering up malicious behaviour of one another from the remaining part of the network, two or more malicious nodes may collaborate to cause damage to or disrupt the network. The concept of the Dynamic Data-Driven Application Systems paradigm has been suggested for use in diverse fields. This paper proposes a novel framework that utilises the paradigm in the area of reputation and trust-based systems in mobile networks. The proposed framework is critically evaluated and compared with existing work. This framework, which is applicable to social and behavioural modelling in networks, has the advantage of monitoring and predicting the future trustworthiness of members and highlighting malicious regions within the network