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Home / programming language / Online Java Projects / Risk Assessment in Social Networks based on User Anomalous Behaviours
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Risk Assessment in Social Networks based on User Anomalous Behaviours

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SKU: PROJ7558 Categories: 2017 Projects, Final Year Projects, Online Java Projects, Web Services Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Risk Assessment in Social Networks based on
User Anomalous Behaviours

Abstract— Although the dramatic increase in OSN usage, there are still a lot of security and privacy concerns. In such a scenario, it would be very beneficial to have a mechanism able to assign a risk score to each OSN user. In this paper, we propose a risk assessment based on the idea that the more a user behavior diverges from what it can be considered as a ‘normal behavior’, the more it should be considered risky. In doing this, we have takein into account that OSN population is really heterogeneous in observed behaviors. As such, it is not possible to define a unique standard behavioral model that fits all OSN users’ behaviors. However, we expect that similar people tend to follow the similar rules with the results of similar behavioral models. For this reason, we propose a risk assessment organized into two phases: similar users are first grouped together, then, for each identified group, we build one or
more models for normal behavior. The carried out experiments on a real Facebook dataset show that the proposed model outperforms a simplified behavioral-based risk assessment where behavioral models are built over the whole OSN population, without a group identification phase. < final year projects >

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