A Secure Web-Based Crime Management System Using Blockchain and Machine Learning

Authors: Vaishanvi Dokhe, Chaitanya Jadhav, Kundan Kapadnis, Kruhsna Kapkar, Jyoti Vadje

Country: India

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Abstract: The increasing complexity of legal case management and the limitations of traditional judicial processes have created a need for a secure, efficient, and intelligent digital system. Conventional methods of handling legal cases are often slow, prone to data tampering, and lack proper coordination among stakeholders such as judges, police officers, lawyers, and stenographers. This paper presents a web-based Crime Management System that integrates blockchain technology and machine learning to enhance the efficiency, transparency, and reliability of judicial processes. The proposed system enables police to create and manage cases, upload evidence securely, and ensure that all records are stored on a blockchain, making them immutable and tamper-proof. Judges can access case details and utilize a machine learning module that analyzes historical case data to provide decision support. Stenographers can update case records, while lawyers can track case progress and manage schedules effectively. The system also includes automated notification features to inform users about case updates, hearing dates, and important events. Built using a structured architecture with a user-friendly interface, backend processing, and database management, the system ensures smooth and secure operations. The proposed solution reduces manual workload, minimizes errors, and improves coordination among all stakeholders. Experimental analysis shows that the system provides a reliable, transparent, and scalable platform suitable for modern judicial and crime management applications.

Keywords: Crime Management System, Blockchain Technology, Machine Learning, Digital Judicial System, Case Management, Evidence Security, Web-Based Application, Decision Support System, Data Integrity, Judicial Automation.

Paper Id: 233125

Published On: 2026-05-21

Published In: Volume 14, Issue 3, May-June 2026

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