An Automated Model to Detect Fake Profiles and botnets inOnline Social Networks Using Steganography Technique
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 1
Abstract
Abstract: At the present time, hundreds of millions of active users all around the world are using online socialnetwork, such as Facebook, Twitter, Tumblr and LinkedIn. This service turned out to be one of the most welllikedand accepted services on the Internet. With the quick development of information technology andnetworking, the users became able to share many things on the web such as pictures, videos, their dailyactivities, attended events and even their location. Nonetheless, the majorities of social networks have weak userto user authentication method, which is based on some basic information like displayed name, photo. Theseweaknesses make it effortless to misuse user’s information and do identity cloning attack to form fake profile. Currently, Facebook has 955 million active users. Of this whole, approximately 8.7 percent (which is equal to83 million users) is fake accounts. Fakes can introduce spam, manipulate online rating, or exploit knowledgeextracted from the network. This enormous number of fake profiles can cause hazards for privacy and securitysuch as spying, misusing personal information, identity thievery, and compromise privacy of users and theirfamilies. This paper will be discussing data hiding techniques to hide some information in profile pictures inorder to detect botnets and fake profiles and finally will propose an automated model to detect fake profiles andbotnets instead of current manual method which is costly and labor-intensive.
Authors and Affiliations
Ehsan Ahmadizadeh , Erfan Aghasian , Hossein Pour Taheri , Roohollah Fallah Nejad
Keywords
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