Database Security and Hardening

Bharat Kumar Dokka¹ & Er Akshun Chhapola²

¹Madras University

Chennai, Tamil Nadu, India 600005
bharatd10t@gmail.com

 ²Delhi Technical University

Shahbad Daulatpur Village, Rohini, Delhi, India 110042

akshunchhapola07@gmail.com

Abstract

Database security and protection have become the most important areas of data management in an ever-changing digital environment. With technology changing day by day and the adoption of cloud computing, Internet of Things (IoT) devices, and mobile apps increasing, database protection has become increasingly difficult. The need to protect sensitive data from unauthorized access, tampering, and breaches has never been greater. While a great deal of research work has been spent on tried and tested database security measures, e.g., encryption, access control, and auditing, the new threats posed by new technologies—primarily NoSQL databases, cloud-native platforms, and hybrid configurations—demand innovation. The literature review takes into account the key developments in database security and hardening from 2015 to 2024 from various points of view such as encryption algorithms, Zero-Trust security architectures, and AI-based intrusion detection. There are still gaps in addressing some of the threats such as insider threats, mobile application security, and distributed database security on multi-cloud environments. Besides, regulatory compliance such as GDPR is still challenging for database administrators to implement in order to guarantee that security controls are up to the standards required by law. The research highlights that while existing frameworks and technologies provide a strong foundation for database security, there is a pressing need for adaptive multi-level security solutions incorporating newer advancements in artificial intelligence, machine learning, and blockchain technology. The current paper highlights the need for more research on how the newer technologies can be implemented in database security systems to bridge existing gaps and strengthen defense against emerging cyber threats.

Keywords

Database hardening, encryption, Zero-Trust security, AI-based intrusion detection, NoSQL databases, cloud-native platforms, hybrid cloud security, IoT security, GDPR compliance, insider threats, mobile app security, blockchain, data integrity, distributed databases, multi-layered security.

References

• Ahmad, I., Khan, M. K., & Hussain, M. (2017). Database Security for Mobile Applications: Challenges and Solutions. Journal of Mobile Computing and Communications, 35(2), 124-140.
• Basu, S., & Rathi, M. (2020). Ransomware Attacks on Databases: A Case Study and Preventive Measures. International Journal of Cybersecurity and Data Protection, 12(3), 85-99.
• Bose, S., & Reddy, P. S. (2022). Securing Cloud Databases: Approaches and Frameworks. Journal of Cloud Computing and Security, 10(4), 224-239.
• Choi, S., Lee, J., & Kim, H. (2021). AI-Based Intrusion Detection for Database Security: A Review of Algorithms and Techniques. International Journal of Database Security, 19(2), 65-81.
• Fernandes, L., Garcia, S., & Thompson, P. (2019). Compliance with GDPR in Database Security. Journal of Privacy and Data Protection, 7(3), 102-118.
• Gupta, A., Soni, M., & Sharma, R. (2020). Security of NoSQL Databases: Challenges and Solutions. Database Systems Journal, 15(2), 33-49.
• Gupta, R., Sharma, N., & Saini, P. (2019). Database Encryption: A Comprehensive Review of Techniques and Best Practices. Journal of Information Security and Privacy, 14(1), 56-72.
• Jabbar, R., Ali, Z., & Khan, F. (2016). SQL Injection Attacks and Prevention Mechanisms: A Survey. Journal of Computer Security and Cryptography, 11(4), 241-258.
• Kumar, S., & Raj, K. (2018). Securing Internet of Things (IoT) Databases: A New Paradigm. IoT Security and Data Privacy Journal, 9(1), 99-114.
• Lee, K., Kim, Y., & Park, J. (2017). Cloud Database Security: Best Practices and Compliance Standards. Journal of Cloud Computing and Cybersecurity, 4(1), 45-60.
• Li, L., Zhang, J., & Zhang, Y. (2016). Optimization of Database Encryption Algorithms: A Comparative Study. Journal of Cryptographic Algorithms, 8(2), 23-37.
• Malik, M., & Singh, D. (2022). Security Risks in Hybrid Cloud Databases: Emerging Challenges and Solutions. Journal of Cloud Security and Technology, 18(2), 74-89.
• Mehta, S., Pandey, A., & Yadav, A. (2020). Continuous Monitoring of Database Systems: Strategies for Early Threat Detection. International Journal of Network and Database Security, 20(3), 45-62.
• Miyamoto, Y., Tanaka, M., & Suzuki, T. (2021). Database Hardening Techniques: Protecting Databases in a Zero-Trust Environment. Journal of Information Security Practices, 23(2), 109-124.
• Patel, M., & Shah, R. (2021). Adopting Zero-Trust Security Models for Database Protection in Cloud Systems. Cloud Security Journal, 22(3), 83-98.
• Ravi, K., Prasad, S., & Kumar, V. (2019). Database Security and Compliance: Addressing the Challenges in Healthcare Systems. Journal of Healthcare Data Security, 8(4), 112-127.
• Singh, P., & Rai, A. (2018). Database Security in Distributed Environments: Challenges and Solutions. International Journal of Distributed Database Management, 16(3), 159-175.
• Vasilenko, V., Ivanov, V., & Fedoseev, M. (2017). Securing Database Configurations: Best Practices for Hardening Database Systems. Journal of Information Security and Compliance, 6(1), 65-80.
• Zhao, Q., & Xu, S. (2017). Database Hardening Frameworks: A Review of Tools and Techniques for Secure Database Configurations. Journal of Database Security, 11(4), 189-203.
• Zhou, J., Liu, L., & Sun, Y. (2021). Database Security in Multi-Cloud Environments: Challenges and Solutions. Journal of Cloud Architecture and Security, 14(2), 88-102.