Effect of Social Media Botnets and their Detection Techniques
Amit Jain1, Anand Kumar Shukla2, Raju Kumar3

1Dr. Amit Jain*, Associate Professor, University Institute of Computing, Mohali, India.
2Dr. Anand Kumar Shukla, Associate Professor, University Institute of Computing, Mohali, India.
3Dr. Raju Kumar, Associate Professor, University Institute of Computing, Mohali, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 27, 2020. | Manuscript published on April 10, 2020. | PP: 530-533 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3720049620/2020©BEIESP | DOI: 10.35940/ijitee.F3720.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The Online Social Network (ONS) or Social Media have become most popular platform for millions of users for their activities and at the same time it has become favorite place for cyber criminals for their illegal activities, generally known as social botnets, which uses different techniques to spread their information on social media like facebook, twitter, renren, linkedin etc. Several researchers have tried to detect several social botnets with different detection techniques. To avoid the detection, social botnets are now using advanced command & control (C&C) communication channels like hash tags, fraud click, friend requests, images, videos etc. Image Steganography techniques are now widely being used to carry out attacks. In this paper, the primary discussion is related to effects of social media botnets along with the different techniques for botnet detection. It also, explores the use of machine learning mechanism, thereby detecting the intrusions in stegano images. Thus, an effort has been made to localize the factors that have a major role in social intervention as a whole. 
Keywords: Botnets, Social Media, Steganography
Scope of the Article: Software Engineering Techniques and Production Perspectives