Open AccessEffect of Social Media Botnets and their Detection Techniques
Author(s) -
Amit Jain,
Anand Kumar Shukla,
Raju Kumar
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f3720.049620
Subject(s) - botnet , social media , computer science , computer security , internet privacy , steganography , social network (sociolinguistics) , hash function , world wide web , artificial intelligence , the internet , image (mathematics)
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.