Abstract
The effective management and protection of digital criminal records is a crucial concern for law enforcement agencies, legal authorities, and government organizations. Traditional paper- based record-keeping systems are increasingly being replaced by digital platforms, which offer enhanced accessibility, efficiency, and scalability. However, the transition to digital criminal record management also introduces new challenges in terms of data security, privacy, and compliance with regulatory frameworks. This dissertation presents an efficient data protection model for the management of digital criminal records. The model leverages a combination of advanced encryption techniques, access control mechanisms, and robust data backup and recovery strategies to ensure the confidentiality, integrity, and availability of sensitive criminal justice information. The proposed model is designed to be scalable in handling increased data loads and user traffic, ensuring that the system remains responsive and efficient even as more crime data is added. Its optimization performance reduced the CPU usage from 70% to 50%, Memory usage from 80% to 60%. The encryption time witnessed a significant reduction of 0.08sec for 1000KB file size as against 0.12 sec in the existing system. It is also adaptable and compliant with relevant data protection regulations, such as the General Data Protection Regulation (GDPR) and national-level data privacy laws. The implementation of this model has significantly enhanced the overall security and integrity of digital criminal record management systems, while ensuring the protection of sensitive personal and criminal justice information.
References
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