Approche robuste pour l’évaluation de la confiance des ressources sur le Web

Zohra Saoud 1, 2
2 SOC - Service Oriented Computing
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : This thesis in Computer Science is part of the trust management field and more specifically recommendation systems. These systems are usually based on users’ experiences (i.e., qualitative / quantitative) interacting with Web resources (eg. Movies, videos and Web services). Recommender systems are undermined by three types of uncertainty that raise due to users’ ratings and identities that can be questioned and also due to variations in Web resources performance at run-time. We propose a robust approach for trust assessment under these uncertainties. The first type of uncertainty refers to users’ ratings. This uncertainty stems from the vulnerability of the system in the presence of malicious users providing false ratings. To tackle this uncertainty, we propose a fuzzy model for users’ credibility. This model uses a fuzzy clustering technique to distinguish between malicious users and strict users usually excluded in existing approaches. The second type of uncertainty refers to user’s identity. Indeed, a malicious user purposely creates virtual identities to provide false ratings. To tackle this type of attack known as Sybil, we propose a ratings filtering model based on the users’ credibility and the trust graph to which they belong. We propose two mechanisms, one for assigning capacities to users and the second one is for selecting users whose ratings will be retained when evaluating trust. The first mechanism reduces the attack capacity of Sybil users. The second mechanism chose paths in the trust graph including trusted users with maximum capacities. Both mechanisms use users’ credibility as heuristic. To deal with the uncertainty over the capacity of a Web resource in satisfying users’ requests, we propose two approaches for Web resources trust assessment, one deterministic and one probabilistic. The first consolidates users’ ratings taking into account users credibility values. The second relies on probability theory coupled with possible worlds semantics. Probabilistic databases offer a better representation of the uncertainty underlying users’ credibility and also permit an uncertain assessment of resources trust. Finally, we develop the system WRTrust (Web Resource Trust) implementing our trust assessment approach. We carried out several experiments to evaluate the performance and robustness of our system. The results show that trust quality has been significantly improved, as well as the system’s robustness in presence of false ratings attacks and Sybil attacks
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Zohra Saoud. Approche robuste pour l’évaluation de la confiance des ressources sur le Web. Web. Université de Lyon, 2016. Français. ⟨NNT : 2016LYSE1331⟩. ⟨tel-01556189⟩

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