Data Security and Storage Administration with Dynamic Encryption Key Management
Bharath Bhushan Sreeravindra, Ayisha Tabbassum, Pradeep Kumar Saraswathi, Madhavi Najana · International Journal of Global Innovations and Solutions (IJGIS) · 2024
This paper presents a novel method and system for flexible data storage management that incorporates dynamic encryption key techniques to ensure data security.The proposed approach determines storage operations and selects optimal storage resources based on predefined criteria such as performance, cost, and data access patterns.The integration of cryptographic keys ensures the confidentiality and integrity of data, addressing security concerns in diverse and large-scale data storage environments.By leveraging adaptive key management, the system can respond to changing security threats and operational requirements in real-time.This adaptability enhances the resilience of data storage solutions against emerging cyber threats and operational disruptions.The system leverages advanced algorithms to study data access patterns, optimizing storage operations for both rapid performance and efficiency.Additionally, the proposed method features a robust mechanism for key rotation and revocation, which reduces the risk of key compromise and bolsters overall security.The dynamic selection of storage resources considers multiple factors, ensuring a balanced approach that meets both performance and cost-efficiency criteria.This comprehensive strategy not only enhances security but also boosts the overall performance of data storage systems.Extensive testing in diverse environments has shown significant improvements in data retrieval times, reduced storage costs, and faster encryption and decryption processes.The results demonstrate the practical applicability of the proposed system in real-world scenarios, showcasing its potential to revolutionize data storage management.The proposed system also integrates seamlessly with existing infrastructure, making it a versatile solution for a wide range of applications.By providing a detailed analysis of key performance indicators, this paper offers valuable insights into the benefits of integrating adaptive cryptographic mechanisms in data storage management.The innovative combination of dynamic operations and adaptive security measures positions this system as a leading-edge solution in the field.Future research will focus on further enhancing these adaptive mechanisms and exploring their application in more diverse storage environments.Additionally, the integration of machine learning algorithms to predict and adapt to data access patterns will be investigated to further optimize system performance.The findings of this paper contribute to the ongoing discourse on secure and efficient data storage, offering a novel perspective that bridges the gap between performance optimization and robust security measures.