Blockchain technology supports recording financial transactions as well as other kinds of data using a distributed ledger, showing safe and immutable exchange. Computerized business transactions or the running of logic in blockchain networks are supported by smart contracts. Identity management systems have greatly relied on blockchain technology recently. It thus aims at a new innovative method of detecting anomalies in streaming data through exploitation of the fundamental characteristics of blockchain technology. Even with the advantages of blockchain, real-time anomaly detection algorithms still lack sufficient performance. The proposed project will integrate Apache Isis with smart contracts based on the Ethereum system to create an automated system of audit trails. The proposed solution is going to ensure data integrity, transparency, and nonrepudiation and provide a reliable framework for anomaly detection. Some of the key objectives include investigating how and to what extent immutable audit trails are effective toward security, enhancing security and transparency in such systems, and applying machine learning techniques to improve anomaly detection. The resultant research would lead to the development of more secure and efficient blockchain-based systems that can benefit a wide range of industries, especially those where data security and integrity are of utmost importance.