A Secure Digital Evidence Management System for Public Safety Applications

Abstract

This paper presents a Secure Digital Evidence Management System for Public Safety Applications that integrates IoT devices, cryptographic security, and cloud storage to ensure the confidentiality, integrity, and traceability of digital evidence. The system uses an ESP32 microcontroller connected to an ultrasonic sensor for real-time object detection. When an object is detected within a predefined range, the ESP32 sends a trigger signal to a laptop through serial communication. A Python-based application then captures video evidence using a webcam and the OpenCV library, enabling automated real-time evidence collection. The system includes a secure dashboard with role-based access control, allowing authorized users to upload, manage, and retrieve evidence efficiently. To protect sensitive data, a hybrid cryptographic framework is implemented, combining Advanced Encryption Standard (AES) for file encryption and RSA-based key encapsulation for secure key exchange. SHA-256 hashing is used to generate unique digital fingerprints for each evidence file, ensuring data integrity. A blockchain-inspired hash chaining mechanism links records sequentially, making any tampering or unauthorized modifications easily detectable. Encrypted evidence files are stored securely in Microsoft Azure Blob Storage, while metadata such as timestamps, file hashes, user information, and tamper status are maintained in a MySQL database. The system also performs automated cloud integrity checks and chain validation to identify missing or altered records. By combining IoT-based sensing, real-time video acquisition, cryptographic protection, cloud storage, and secure access control, the proposed system provides a reliable and tamper-resistant platform for digital evidence management, significantly improving the effectiveness and trustworthiness of digital forensic investigations in public safety environments.