Social media news are most important in today’s worlds, it puts positive or negative influence on social views. There is a wide propagation of fake news on social media so it will be difficult to believe on the news. Fake news has negative impacts on individuals as well as on society. Information spreads rapidly over the social media and so there is a need of mechanism which detects and stops the spreading of fake news. Therefore, detection of fake news is the need of time and also a challenging problem. The goal of this proposed research work is to detect fake news and minimize spreading of the fake news. In the proposed research a machine learning approach is used for detection of fake news with blockchain framework. In first section a supervised machine learning techniques is design to identify the trustiness of specific news while blockchain framework revoke the malicious activity of spreading fake news. A blockchain environment is created with mining, smart contract as well as Proof of Work (PoW) of consensus. The current systematic review broadly focuses on the various methods to detect fake news in social media. After partial implementation of system, performance evaluation has done with traditional blockchain framework. It is found that 10% less time for transaction verification by consensus in P2P environment over the existing systems.