Developing a framework for securing blockchain-driven systems with large amounts of data

The rapid expansion of big data has boosted advancements in fields such as healthcare, finance, and marketing. However, handling and storing large amounts of sensitive data have raised significant concerns due to security and privacy risks. Research suggests that blockchain technology could help address these challenges to some extent. This study aims to create a framework for securing big-data systems powered by blockchain, using the design science method. The framework includes seven key components: authentication and access control, data encryption and key management, privacy and confidentiality, data integrity and authenticity, data provenance and audit trails, intrusion detection and prevention, and incident response and recovery. This framework allows organizations to harness the potential of big data without risking data integrity or privacy. The findings indicate that this framework offers comprehensive guidelines for safely using big data across different sectors. Combining blockchain and big data can safeguard sensitive information, ushering in a new era of secure, data-driven innovation and trust.