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SocialBot: Behavioral Analysis and Detection

  • Madhuri DewanganEmail author
  • Rishabh Kaushal
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 625)

Abstract

Bots refer to automated software that have the capability to execute commands on receiving instructions from BotMaster. SocialBots are the bots present in Online Social Network (OSN) which mimic the activities of the real users. They have the capability to automatically perform the basic functionalities offered by the OSN platforms. These socialbots have widespread usage in political campaigning and product marketing, but SocialBots can also been used for the purpose of swaying voters, mounting political attacks, manipulating public opinion, etc. Apart from these, SocialBots posses various security risks, one of which is befriending an OSN user thereby gaining access to personal details such as birthday, email id, phone number, address, etc. Detection of these SocialBots is therefore an important problem to be solved in order to maintain the reputation of OSN. Our work concentrates on behavioral analysis of these SocialBots in the OSN and identifying features to be used to develop a model for detection of these Socialbots using machine learning. The model, thus developed, is further used as a background process to create a web-based tool for detection of SocialBots. In our work, we created a SocialBot to perform behavioral analysis. This SocialBot got a good response from the real users and was able to grab 100+ real followers along with some real interactions in form of retweet, mention and direct messages.

Keywords

Online Social Network Social engineering SocialBots Feature extraction Machine learning 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2016

Authors and Affiliations

  1. 1.Department of Information TechnologyIndira Gandhi Delhi Technical University for WomenNew DelhiIndia

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