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Final year IEEE projects 2016 based on Java INFORMATION FORENSICS & SECURITY
  • Final year IEEE projects 2016 based on Java INFORMATION FORENSICS & SECURITY

Profiling Online Social Behaviors for Compromised Account Detection

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Profiling Online Social Behaviors Compromised Account Detection

Account computerization is a serious threat to users of online social networks (OSNs). While relentless spammers exploit the established trust relationships between account owners and their friends to efficiently spread malicious spam, timely detection of compromised accounts is quite challenging due to the well established trust relationship between the service providers, account owners, and their friends.

In the proposed system, the social behaviors of OSN users, i.e., their usage of OSN services, and the application of which in detecting the compromised accounts is studied.Profiling Online Social Behaviors Compromised Account Detection.

In particular, the proposed system provides a set of social behavioral features that can effectively characterize the user social activities on OSNs.Profiling Online Social Behaviors Compromised Account Detection.

The efficacy of these behavioral features by collecting and analyzing real user click streams to an OSN website is validated. Based on the measurement study, individual user’s social behavioral profile by combining its respective behavioral feature metrics is devised. A social behavioral profile accurately reflects a user’s OSN activity patterns.

Profiling Online Social Behaviors Compromised Account Detection While an authentic owner conforms to its account’s social behavioral profile involuntarily, it is hard and costly for impostors to feign.

The capability of the social behavioral profiles in distinguishing different OSN users is evaluated and the experimental results shows the social behavioral profiles can accurately differentiate individual OSN users and detect compromised accounts.

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