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Title: To Develop an Efficient Malware Detection Technique for Online Social Networks
Authors: Veena, D. M.
Keywords: Computer Science & Engineering
Issue Date: 2015
Abstract: With this project, we present the design of a Malware detecting system in Online Social Networking Sites. It mainly detects the malicious posts in facebook on wall of user which contains malicious URL link. In our detecting system we process a URL with various stages of filtration process by considering a rigid feature set. The feature set considered are analysed and studied thoroughly through various experiments conducted. For this purpose we adopted few features from existing detection mechanism Mypagekeeper and improvise it with our new features. In this design we also present a prioritization method, which prioritizes the users and helps the detection system in analysing and checking walls and news feeds of most active users first. This prioritization method helps in saving resources and in reducing detecting time of our detection system. The data is collected using a facebook app, and a software module netvizz v1.5. We have proposed a model based on SVM classifier in which weights are assigned to the predetermined features by performing in a sequence of steps on the data collected.
Appears in Collections:01. CSE

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