This project was developed for the KSP Datathon with the aim of addressing the challenge of balancing data collection and utilization for effective law enforcement while ensuring public privacy concerns are met. The project proposes innovative solutions to enhance data security, privacy, and transparency in law enforcement activities.

Balancing data collection and utilization for law enforcement requires innovative solutions that address public privacy concerns. Law enforcement agencies need frameworks and technologies that anonymize sensitive data, ensure secure storage and access, and provide clear guidelines for data use in compliance with privacy regulations.

Developing frameworks and technologies that meet the following challenges:

• Anonymizing sensitive data
• Ensuring secure storage and access
• Providing clear guidelines for data use in compliance with privacy regulations

Law enforcement agencies require a robust and secure platform to file cases and manage sensitive information. A web portal integrated with blockchain technology ensures immutable record-keeping, enhancing transparency and trust in the system. By leveraging the InterPlanetary File System (IPFS), evidence storage becomes decentralized and privacy-preserving, safeguarding sensitive data from unauthorized access. Encryption protocols and access controls add layers of security, allowing only authorized personnel to access case files. This integrated solution not only enhances data security but also streamlines the case filing process for law enforcement agencies.

A comprehensive and interactive blockchain-based web 3.0 platform has been meticulously crafted for the seamless uploading and management of case files, including FIRs, chargesheets, and statements. Leveraging existing OCR techniques, alongside pre-trained NLP technologies, enables efficient extraction of pertinent details from these files. Integrating a sophisticated anonymization algorithm within the application ensures the substitution of personal identifiers with randomized placeholders while preserving the integrity and structure of the data. Users benefit from a user-friendly dropdown interface, empowering them to selectively anonymize data based on customizable anonymization rules, thereby enhancing privacy protection and data quality.

Preserving individual privacy while analyzing sensitive data within case files is paramount for maintaining trust and compliance in law enforcement activities. Implementing differential privacy techniques enables accurate analysis while obscuring individual identities and sensitive information. Federated learning techniques facilitate collaborative data analysis across multiple agencies without compromising data privacy, as raw data remains decentralized. Transparent data governance frameworks ensure accountability and adherence to privacy regulations, fostering public confidence in law enforcement practices.

Recognizing the critical role of education in promoting privacy-conscious behaviors among law enforcement personnel, a gamified privacy education platform is designed to engage and educate users effectively. Tailored modules covering data privacy laws, best practices for handling sensitive information, and ethical considerations in surveillance technologies equip personnel with essential knowledge and skills. Incentives and rewards incentivize participation and continuous learning, fostering a culture of privacy awareness and responsible data handling within law enforcement teams.

Home Page 🏠

Outstanding Features ✨

Performance 🚀

Case Filing 📋

Criminal Case Filing System OCR 🔍

Report Response 📄

• Prototype Video
• Crime Lens API (Hosted at Streamlit)
• Web3 Portal (Hosted at Azure)