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- W2520341794 abstract "Proliferation of internet technologies has changed the way content is created and exchanged through the Internet, prompting expansion of online networking applications and administrations. Online networking empower creation and exchanged the clients produced content and design of a scope of Internet-based applications. This development is fueled by more administrations as well as by the rate of their adoption by the users. While determined spammers misuse the built up trust connections between account proprietors and their companions to proficiently spread malignant spam, auspicious discovery of traded off records is quite challenge, because of the fixed trust association among the administration suppliers, account proprietors, and their companions. The proposed paper depicts a novel method to notice the cooperated user account in systems like Facebook and twitter. Our novel scheme consists of statistical method of modelling and detected to identity accounts that behaves a sudden change along with detected the compromised accounts. This paper gives validation of these behavioral elements by gathering and dissecting genuine client clickstreams to an OSN site. Taking into account our estimation study, further devise every client's social behavioral profile (SBP) by joining its separate behavioral element measurements. We assess the capacity of social behavioral profiles in recognizing distinctive OSN clients, and the simulation results demonstrate the social behavioral profiles precisely separate every OSN clients and distinguish traded off records." @default.
- W2520341794 created "2016-09-23" @default.
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- W2520341794 date "2016-03-01" @default.
- W2520341794 modified "2023-09-28" @default.
- W2520341794 title "Diagnosis of compromised accounts for online social performance profile network" @default.
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- W2520341794 doi "https://doi.org/10.1109/wispnet.2016.7566397" @default.
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