Published Paper Details:

In the present generation, social media have emerged as an increasingly popular means for communication, information transfer, gathering and making new connections. The social life of everyone has become associated with online social networks. Day by day the number of users using social media is increasing drastically. Researchers have been studying these online social networks to see the impact they make on the people. These sites have made a drastic change the way we pursue our social life. But all this have provided a way for cyber-attacks such as fake identity, false information, etc. Therefore in this paper, we came up with an idea to build a fake classifier which we have been divided into three different modules in which first module detects the fake profiles that are made on social networking sites, second module detects fake news that is being spread by these particular accounts and third module consists of detecting the fake images posted by these accounts which are being photo shopped. Our related work includes various algorithms that are being implemented in this project in broader aspects and we have used various machine learning algorithms to detect these accounts, news and images. The rapid growth in image generation and manipulation has now reached a point where it is raising questions about the consequences faced by the public. This not only undermines confidence in digital media content but also spreads false information and news. This paper investigates the reality of edited image content, false information and fake profiles as well as how hard it is to find them and how effective strategies can be used to do so.