Divel - Digital Evidence Locker

DiVeL is a blockchain and AI based digital evidence management platform.

Comment

DiVeL – Digital Evidence Locker

Inspiration

With the rapid growth of cybercrime and digital investigations, law enforcement agencies are handling an ever-increasing volume of digital evidence such as images, videos, documents, and audio recordings. Traditional evidence management systems often rely on fragmented storage solutions and manual verification processes, making it difficult to ensure evidence integrity, maintain a reliable chain of custody, and quickly retrieve critical information.

We built DiVeL (Digital Evidence Locker) to address these challenges by combining cloud computing, blockchain, and Generative AI into a secure, intelligent, and scalable platform. Our goal is to empower investigators with a system that preserves evidence authenticity, streamlines investigations, and reduces manual effort.

What it does

DiVeL is a cloud-native Digital Evidence Management System (DEMS) that securely stores, verifies, and analyzes digital evidence.

The platform enables investigators to:

  • Upload images, videos, audio files, and documents securely.
  • Store evidence in Amazon S3 with encrypted cloud storage.
  • Automatically generate a SHA-256 hash for every uploaded file.
  • Record the evidence hash on the Ethereum blockchain to create a tamper-proof chain of custody.
  • Store searchable metadata in Amazon DynamoDB.
  • Generate AI-powered summaries of uploaded evidence using Amazon Bedrock.
  • Interact with an AI Investigation Assistant to quickly retrieve information and analyze evidence using natural language.
  • Search, organize, and manage evidence through an intuitive dashboard.

By combining automation, AI, and blockchain, DiVeL reduces investigation time while increasing trust in digital evidence.

How we built it

Frontend

  • React.js
  • Tailwind CSS
  • JavaScript

The frontend provides investigators with a clean dashboard for uploading evidence, managing cases, viewing metadata, and interacting with the AI assistant.

Backend

  • FastAPI
  • Python

The backend handles authentication, evidence management, API endpoints, and communication with AWS services.

Cloud Infrastructure

Our application is built on AWS using a serverless architecture.

The workflow is as follows:

  1. Investigators upload digital evidence through the React application.
  2. Files are securely stored in Amazon S3.
  3. AWS Lambda is triggered through Amazon API Gateway.
  4. Lambda downloads the uploaded file, computes its SHA-256 hash, stores metadata in Amazon DynamoDB, and records the hash on the Ethereum blockchain.
  5. Amazon Bedrock analyzes evidence and generates AI-powered summaries and responses.
  6. The processed information is displayed back to investigators through the dashboard.

This architecture provides scalability, reliability, and low operational overhead.

Blockchain Integration

Evidence integrity is one of the most critical requirements in digital investigations.

For every uploaded file:

  • SHA-256 hashing creates a unique fingerprint.
  • The fingerprint is anchored on the Ethereum blockchain.
  • Transaction details are linked with the evidence metadata.
  • Future verification ensures that any modification to the evidence can be immediately detected.

This establishes a transparent and immutable chain of custody.

Artificial Intelligence

Amazon Bedrock powers the intelligent capabilities of DiVeL.

The AI assists investigators by:

  • Summarizing lengthy evidence documents.
  • Explaining key findings from uploaded files.
  • Answering natural language questions about case evidence.
  • Helping investigators locate relevant information quickly.
  • Reducing the time required for manual evidence review.

Instead of replacing investigators, the AI acts as an intelligent assistant that accelerates evidence analysis and decision-making.

Challenges we ran into

Developing DiVeL involved several technical challenges.

Integrating multiple AWS services into a seamless workflow required careful coordination between Amazon S3, AWS Lambda, API Gateway, and DynamoDB.

Implementing blockchain-based integrity verification while maintaining fast upload performance required optimizing the evidence processing pipeline.

Designing effective prompts for Amazon Bedrock was another challenge. The AI needed to generate accurate, concise, and context-aware summaries without introducing misleading information.

We also focused heavily on scalability, ensuring that the platform could efficiently handle increasing amounts of evidence and concurrent users while maintaining security and performance.

Accomplishments that we're proud of

  • Built a complete cloud-native Digital Evidence Management System.
  • Successfully integrated blockchain for immutable evidence verification.
  • Developed an AI-powered Investigation Assistant using Amazon Bedrock.
  • Automated evidence hashing and metadata management.
  • Designed a scalable serverless architecture using AWS.
  • Created an intuitive dashboard for evidence management.
  • Combined cloud computing, blockchain, and Generative AI into a single platform.

What we learned

Through DiVeL, we gained practical experience in:

  • Building cloud-native applications on AWS.
  • Designing scalable serverless architectures.
  • Secure file storage using Amazon S3.
  • Metadata management with Amazon DynamoDB.
  • Blockchain integration for tamper-proof verification.
  • Prompt engineering and AI application development using Amazon Bedrock.
  • REST API development with FastAPI.
  • Secure system design for sensitive digital assets.

Most importantly, we learned how modern cloud technologies and Generative AI can transform digital investigations by making evidence management more secure, efficient, and intelligent.

What's next for DiVeL

We envision DiVeL becoming a comprehensive AI-powered Digital Evidence Management Platform for law enforcement agencies worldwide.

Future enhancements include:

  • AI-powered image, video, and audio forensic analysis.
  • Deepfake detection for digital media.
  • Automatic OCR for scanned documents.
  • Speech-to-text transcription for audio evidence.
  • Object, face, and scene detection in multimedia evidence.
  • Semantic search across all case evidence.
  • Automated chain-of-custody reports for court proceedings.
  • Secure multi-agency evidence sharing.
  • Mobile application for field officers.
  • Integration with forensic laboratories and judicial systems.

Our long-term vision is to build a trusted, intelligent, and secure platform that modernizes digital evidence management and helps investigators solve cases faster while preserving the integrity of every piece of evidence.

Built With

Share this project:

Updates

Submission history