Article: Detecting malicious users in the social networks using machine learning approach Journal: International Journal of Social Computing and Cyber-Physical Systems (IJSCCPS) 2021 Vol.2 No.3 pp.229 - 243 Abstract: Social networking plays a very important role in today's life. It helps to share ideas, information, multimedia messages and also provides the means of communication between the users. The popular social medias such as Facebook, Twitter, Instagram, etc., where the billions of data are being created in huge volume. Every user has their right to use any social media and a large number of users allowed malicious users by providing private or sensitive information, which results in security threats. In this research, they are proposing an natural language processing (NLP) technique to find suspicious users based on the daily conversations between the users. They demonstrated the behaviour of each user through their anomaly activities. Another machine learning technique called support vector machine (SVM) classifiers to detect the toxic comments in the comments blog. In this paper, the preliminary work concentrates on detecting the malicious user through the anomaly activities, behaviour profiles, messages and comment section. Inderscience Publishers - linking academia, business and industry through research

Title: Detecting malicious users in the social networks using machine learning approach

Authors: H.L. Gururaj; U. Tanuja; V. Janhavi; B. Ramesh

Addresses: Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru – 570002, India ' Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru – 570002, India ' Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru – 570002, India ' Department of Computer Science and Engineering, Malnad College of Engineering, Hassan – 573202, India

Abstract: Social networking plays a very important role in today's life. It helps to share ideas, information, multimedia messages and also provides the means of communication between the users. The popular social medias such as Facebook, Twitter, Instagram, etc., where the billions of data are being created in huge volume. Every user has their right to use any social media and a large number of users allowed malicious users by providing private or sensitive information, which results in security threats. In this research, they are proposing an natural language processing (NLP) technique to find suspicious users based on the daily conversations between the users. They demonstrated the behaviour of each user through their anomaly activities. Another machine learning technique called support vector machine (SVM) classifiers to detect the toxic comments in the comments blog. In this paper, the preliminary work concentrates on detecting the malicious user through the anomaly activities, behaviour profiles, messages and comment section.

Keywords: social networks; malicious users; Naïve bayes; NLP; natural language processing; comments; social media; SVM; support vector machine.

DOI: 10.1504/IJSCCPS.2021.117959

International Journal of Social Computing and Cyber-Physical Systems, 2021 Vol.2 No.3, pp.229 - 243

Received: 25 Jul 2020
Accepted: 18 Nov 2020
Published online: 05 Oct 2021 *

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Title: Detecting malicious users in the social networks using machine learning approach

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