Blockchain & AI : The Ultimate Sheild Against Fake Identities Online

The majority of the spam accounts are set up to propagate misinformation, disseminate propaganda, etc. Identification and removal of these accounts are crucial to stemming the spread of false information and maintaining the integrity of information disseminated via social media. In this paper, we introduce a new algorithm for creating fake social media profiles through the incorporation of machine learning methods like Gradient Boosting, Random Forest, and Support Vector. The algorithm accepts all kinds of profile features, such as a profile image; features of the username and full name in terms of length, numbers, equality, description length; an external URL, account privacy, and the most important metrics, i.e., the number of posts, followers, and follows. In that regard, the suggested algorithm uses ensemble learning to enhance the overall precision and validity of deception profile detection. We introduce a web application based on Flask to deploy the Random Forest algorithm with block chain security which allows detection and offering an easy to use interface.