Role of AI in Database Security
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I1P110Keywords:
Database Security, Artificial Intelligence, Machine Learning, Intrusion Detection, Anomaly Detection, Cybersecurity, Predictive Analytics, Data EncryptionAbstract
The speed at which digital data is expanding into different fields has created the need to have highly developed security systems to entrap sensitive information. However, the conventional database protection techniques though succeeding to some degree, may fail to manage advanced cyber threats, data breach issues at magnitude and volatile attack patterns. AI has become one of the radonuces in improving the safety of the database by utilizing the machine learning, deep learning, and intelligent algorithms to forecast, identify, and adjust the possible security threat. The paper discusses the use of AI in the security of databases, currently studying its methodologies, applications, and challenges. Anomaly detection, predictive analytics, user behavior profiling, and automated threat response mechanisms (AI-based methods) are examples of proactive means of protecting databases. The integration of AI in systems of access control, encryption management, and intrusion detector is also explored in the study. As the paper illustrates the efficient use of AI in increasing data integrity, confidentiality, and availability, there was a comprehensive literature review, analysis of the methodology, and discussion of the experimental results. The results suggest that AI-based security systems can substantially surpass the traditional systems, but necessary areas of work include model interpretability, computational challenges, and the changing threat environment, with ongoing research necessary. The paper has concluded by highlighting the future opportunities of AI in developing strong, dynamic as well as intelligent database protection solutions
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