• Sumit Bhise
• Bindy Wilson

This research explores innovative techniques to beautify database security, inclusive of homomorphic encryption for privacy-preserving computations, blockchain for data integrity, behavioral biometrics for user entry and control, and differential privacy for balancing data software and privacy. It also addresses quantum computing threats, dynamic generation of access to manipulate, AI-push anomaly detection, and computational-physical database security. The proposed Onion model adds, in addition, layer through robotically erasing records in cases of unauthorized get entry to imparting strong safety capabilities for organizations.

Database Security, Homomorphic Encryption, Blockchain for Data Integrity, Behavioral Biometrics, Differential Privacy, Quantum Computing Countermeasures, Dynamic Access Control Policies, Secure multi-party computation, AI-driven anomaly detection, federated learning, Cyber-Physical Database Security, Onion Model, Data Privacy, Encryption Techniques, Tamper-Proof Ledgers, Trust and Reliability, User Access Control, Real-time Access Control, Collaborative Computations, Anomaly Detection, Distributed Learning, Cybersecurity, Privacy-Preserving Techniques, Threat Mitigation, and Preemptive Security Measures.

"Safeguarding Large Datasets: A Multifaceted Approach to Database Security", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.g831-g835, December-2023, Available :http://www.jetir.org/papers/JETIR2312698.pdf

"Safeguarding Large Datasets: A Multifaceted Approach to Database Security", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. ppg831-g835, December-2023, Available at : http://www.jetir.org/papers/JETIR2312698.pdf