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http://dx.doi.org/10.30693/SMJ.2022.11.1.58

Fake SNS Account Identification Technique Using Statistical and Image Data  

Yoo, Seungyeon (조선대학교 컴퓨터공학과)
Shin, Yeongseo (조선대학교 컴퓨터공학과)
Bang, Chaewoon (조선대학교 컴퓨터공학과)
Chun, Chanjun (조선대학교 컴퓨터공학과)
Publication Information
Smart Media Journal / v.11, no.1, 2022 , pp. 58-66 More about this Journal
Abstract
As Internet technology develops, SNS users are increasing. As SNS becomes popular, SNS-type crimes using the influence and anonymity of social networks are increasing day by day. In this paper, we propose a fake account classification method that applies machine learning and deep learning to statistical and image data for fake accounts classification. SNS account data used for training was collected by itself, and the collected data is based on statistical data and image data. In the case of statistical data, machine learning and multi-layer perceptron were employed to train. Furthermore in the case of image data, a convolutional neural network (CNN) was utilized. Accordingly, it was confirmed that the overall performance of account classification was significantly meaningful.
Keywords
machine learning; deep learning; convolutional neural network(CNN); social network service; fake accounts;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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