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Monday, 12 February 2018

A Computational Dynamic Trust Model for User Authorization(2015)

A Computational Dynamic Trust Model for User 


Development of authorization mechanisms for secure information access by a large community of users in an open environment is an important problem in the ever-growing Internet world. In this paper we propose a computational dynamic trust model for user authorization, rooted in findings from social science. Unlike most existing computational trust models, this model distinguishes trusting belief in integrity from that in competence in different contexts and accounts for subjectivity in the evaluation of a particular trustee by different trusters. Simulation studies were conducted to compare the performance of the proposed integrity belief model with other trust models from the literature for different user behavior patterns. Experiments show that the proposed model achieves higher performance than other models especially in predicting the behavior of unstable users.
Existing System:
                            The everyday increasing wealth of information available online has made secure information access mechanisms an indispensable part of information systems today. The mainstream research efforts for user authorization mechanisms in environments where a potential user’s permission set is not predefined, mostly focus on role-based access control (RBAC), which divides the authorization process into the role-permission and user-role assignment. RBAC in modern systems uses digital identity as evidence about a user to grant access to resources the user is entitled to.
                         Holding evidence does not necessarily certify a user’s good behavior.
Proposed System:
       we propose a computational dynamic trust model for user authorization. Mechanisms for building trusting belief using the first-hand (direct experience) as well as second-hand information (recommendation and reputation) are integrated into the model. The contributions of the model to computational trust literature are:
• The model is rooted in findings from social science, i.e. it provides automated trust management that mimics trusting behaviors in the society, bringing trust computation
for the digital world closer to the evaluation of trust in the real world.
 • Unlike other trust models in the literature, the proposed model accounts for different types of trust. Specifically, it distinguishes trusting belief in integrity from that in competence.
• The model takes into account the subjectivity of trust ratings by different entities, and introduces a mechanism to eliminate the impact of subjectivity in reputation aggregation.

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