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DC Field | Value | Language |
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dc.contributor.author | Yapa, K. | - |
dc.contributor.author | Udara, S.W.I. | - |
dc.contributor.author | Wijayawardane, U.P.B. | - |
dc.contributor.author | Kularatne, K.N.P. | - |
dc.contributor.author | Navaratne, N.M.P.P. | - |
dc.contributor.author | Dharmaphriya, W.G.V.U | - |
dc.date.accessioned | 2022-02-07T06:39:46Z | - |
dc.date.available | 2022-02-07T06:39:46Z | - |
dc.date.issued | 2021-12-09 | - |
dc.identifier.issn | 978-1-6654-0862-2/21 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/962 | - |
dc.description.abstract | Social media is one of the most predominantly used online platforms by individuals across the world. However, very few of these social media users are educated about the adverse effects of obliviously using social media. Therefore, this research project, is to develop an advisory system for the benefit of the general public who are victimized by the adverse impacts of their ignorant and oblivious behavior on social media. The system was implemented using a decision tree model with the use of customized datasets; and for the proceeding operational implementations, Python programming language, Pandas, Natural Language Processing and TensorFlow were used. This advisory system can monitor user behaviors and generate customized awareness reports for the users based on category and level of their behaviors on social media. Furthermore, the system is also capable of generating graph reports of the use behavior fluctuations for the reference of the user. With the help of these customized awareness reports and the graph reports, the users can identify their potential vulnerabilities and improve their social media habits. | en_US |
dc.description.sponsorship | Co-Sponsor:Institute of Electrical and Electronic Engineers (IEEE) Academic sponsor:SLIIT UNI Gold Sponsor :London Stock Exchange Group (LSEG) | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.subject | Awareness Report | en_US |
dc.subject | Cyber-Crimes | en_US |
dc.subject | Graph Report | en_US |
dc.subject | Natural Language Processing | en_US |
dc.subject | Social Engineering | en_US |
dc.subject | Social Media | en_US |
dc.title | AI Based Monitoring System for Social Engineering | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC54203.2021.9671218 | en_US |
Appears in Collections: | 3rd International Conference on Advancements in Computing (ICAC) | 2021 Department of Computer systems Engineering-Scopes |
Files in This Item:
File | Description | Size | Format | |
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AI_Based_Monitoring_System_for_Social_Engineering.pdf Until 2050-12-31 | 3.1 MB | Adobe PDF | View/Open Request a copy |
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