The growing prominence of intelligent transportation systems (ITS) has led to increased research on vehicular ad hoc networks (VANETs). Blockchain technology offers promising solutions for ensuring data security, integrity, and immutability within VANETs. However, VANETs remain vulnerable to false data injection attacks (FDIAs), which can significantly disrupt network operations and endanger safety. This paper proposes a novel approach using a blockchain-based decentralized application system (Dapp) for FDIA detection in VANETs. The Dapp leverages smart contracts to manage crucial aspects like data provenance, reputation, and consensus mechanisms. It uses POS consensus algorithm to guarantee data consistency and fault tolerance even in the presence of malicious nodes. To manage the vehicular data, users can access the system via Dapp, an Ethereum—distributed application. By integration of blockchain-based IPFS-Dapps system and AI/ML/big data model with blockchain are aim of the research article for providing the solutions for false data injection attacks (FDIA). We collect the data through Radio Channels, Smart Sensors, Smart Antennas and  RSU and than uploaded using Dapp and than we classified nodes from smart contract and finally send it to Ethereum. We used a machine learning SVR algorithm, i.e., vehicular network-based support vector regression (VBSVR) to identify an attacker node. We have written the pseudocode for using IPFS with Ethereum, proposed research methodology includes integration of blockchain and Dapps with smart contract, integration of AI/ML/big data models with blockchain, and integration of ML Oracle under blockchain that are ideal for detection of false injection attacks nodes, and same is logged in IPFS Decentralized Server.