International Journal of Contemporary Research in Multidisciplinary

As cyber threats evolved, the necessity of secure and effective sharing of threat intelligence in cloud environments has developed ever more urgently. Centralized methods are confronted with serious limitations, such as risks of data integrity, transparency issues, and scalability limitations. It introduces the Enhancing Security Using Blockchain paper, which has been cited for overcoming the aforementioned problems. This system leverages blockchain technology to achieve decentralized threat intelligence sharing, as well as to provide tampering evidence and transparency. The proposed method is to secure the data on an Ethereum blockchain while utilizing ABE for fine-grained access control to ensure that only permissible persons can access sensitive data. Smart contracts also automate the verification process and transactions to be more secure and efficient. Machine learning methods such as logistic regression, random forest, and CNNs are used to capture cyber threat patterns and optimize risk detection. Experimental verification indicates that the ensemble model is 92% accurate, surpassing traditional security measures in detecting cyber-attacks and maintaining data integrity. Moreover, trust between parties is promoted by blockchain, preventing data manipulation and enabling transaction processes with low latency. These advantages notwithstanding, there are future studies in computational overhead, government regulation-compliance, and existing cloud infrastructure integration as their scope. The emphasis of this research will be on how to improve cybersecurity through the sharing of threat intelligence using blockchain with secure, transparent, and scalable methods of managing such threats in cloud environments. The future work will focus on blockchain storage optimization, improving computational efficiency accompanied by better consensus schemes for scalability and acceptance.