An Automated Model to Detect Fake Profiles and botnets in Online Social Networks Using Steganography Technique
Iosr Journals, Ehsan Ahmadizadeha , Erfan Aghasianb,1 ,Hossein Pour Taheric , Roohollah Fallah Nejadd · Figshare · 2015
At the present time, hundreds of millions of active users all around the world are using online social network, such as Facebook, Twitter, Tumblr and LinkedIn. This service turned out to be one of the most well- liked and accepted services on the Internet. With the quick development of information technology and networking, the users became able to share many things on the web such as pictures, videos, their daily activities, attended events and even their location. Nonetheless, the majorities of social networks have weak user to user authentication method, which is based on some basic information like displayed name, photo. These weaknesses 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 to 83 million users) is fake accounts. Fakes can introduce spam, manipulate online rating, or exploit knowledge extracted from the network. This enormous number of fake profiles can cause hazards for privacy and security such as spying, misusing personal information, identity thievery, and compromise privacy of users and their families. This paper will be discussing data hiding techniques to hide some information in profile pictures in order to detect botnets and fake profiles and finally will propose an automated model to detect fake profiles and botnets instead of current manual method which is costly and labor-intensive. Keywords: Fake book, Trust, Privacy, social Network, Steganography, Watermarking, botnets