Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1119
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dc.contributor.authorKumara, P.M.I.N.-
dc.contributor.authorDananjaya, K.G.S.-
dc.contributor.authorAmarasena, N.P.N.H.-
dc.contributor.authorPinto, H.M.S.-
dc.contributor.authorYapa, K.-
dc.contributor.authorRupasinghe, L.-
dc.date.accessioned2022-02-14T06:25:04Z-
dc.date.available2022-02-14T06:25:04Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1119-
dc.description.abstractThe usage of online social networking sites is increasing rapidly. But the downside is that the growth of various kinds of ongoing social media threats such as fake profiles, cyberbullying, and fake news. Many important observations can be made to increase the existing knowledge about social media threats by studying various information exchanged through public and organizations. One direction is to conduct studies on human behavior and personality traits using public user profile data and the organizational threat classifying. This research aims to build a system to predict human personality behaviors on social media profiles based on the OCEAN Model and company-based threat profiling. All the data collected relating to everyone in the consumer’s friend list is analyzed to obtain the threatening behaviors and classified according to the OCEAN to generate a threat report. Organizational network gathered log data for filtered log protection against malware. Logs received from these endpoints will be collected by collectors. Those logs will be forwarded to our filter, made of a Machine Learning Algorithm (MLA). This will be a custom MLA specially designed for this purpose. MLA will classify and categorize threats according to their severity, filtered log protection system against malware and other threats.en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectsocial networking sitesen_US
dc.subjectpersonality traitsen_US
dc.subjectocean modelen_US
dc.subjectlog protectionen_US
dc.subjectmachine learning algorithmen_US
dc.titleHuman and Organizational Threat Profiling Using Machine Learningen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671194en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE

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