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🛡️ AthenaGuard

Real-Time AI Detection of Transformed Sports Media Misuse

Build with AI Solution Challenge Live MVP License Node.js Next.js

AthenaGuard detects unauthorized sports media — even after cropping, mirroring, meme-editing, or compression. Traditional systems fail on transformed content. AthenaGuard doesn't.

🚀 Live Demo📂 GitHub📖 Docs🎬 Demo Video


📌 Table of Contents


🎯 Problem Statement

Sports broadcasters lose billions annually to unauthorized media redistribution. Existing copyright detection tools rely on exact matching or watermarks — both fail when content is:

  • ✂️ Cropped or trimmed
  • 🪞 Mirrored or flipped
  • 🎭 Meme-edited with overlays
  • 📉 Compressed or re-encoded
  • 📱 Re-uploaded as short clips

AthenaGuard solves this using transformation-aware AI detection.


💡 Solution Overview

AthenaGuard is an AI-powered sports media protection platform that:

Capability Description
🔍 Transformation-Aware Detection Detects misuse even after heavy edits
Real-Time Monitoring Simulated stream ingestion pipeline
🖐️ Manual Verification Upload-based on-demand analysis
⚖️ Automated DMCA Auto-generate, send, and track notices
📊 ROI Dashboard Estimated revenue saved + platform analytics
🤖 AI Explainability Shows why content was flagged

How AthenaGuard vs Traditional Systems

Feature Traditional AthenaGuard
Exact match detection
Watermark-dependent ❌ (not required)
Detects transformed content
Real-time monitoring ✅ (simulated)
DMCA automation
ROI analytics

✨ Key Features

🔬 AI-Based Media Detection

  • Generates robust media fingerprints via embeddings + perceptual hashing
  • Detects cropped, mirrored, meme-edited, and compressed variants
  • OCR-based meme text recognition

📡 Real-Time Monitoring (Simulated)

  • Queue-based streaming pipeline simulating live ingestion
  • Scans across multiple platforms concurrently
  • Instant violation flagging via confidence thresholds

🔎 Manual Verification Mode

  • Upload images or video clips for forensic analysis
  • Returns similarity score, detected transformations, and action recommendation

⚖️ Automated DMCA Workflow

  • One-click DMCA notice generation with evidence
  • Status tracking: Generated → Sent → Under Review → Resolved
  • Simulated email dispatch to platform Trust & Safety teams

🧠 AI Explanation Engine

  • Explains why content was flagged (transparency layer)
  • Powered by Google Gemini API
  • Builds legal-grade audit trail

📊 Dashboard & Analytics

  • Violation heatmaps, confidence scores, platform-wise breakdown
  • ROI metrics: estimated revenue protected
  • Alert system with real-time notifications

🔐 Authentication System

  • Firebase Authentication — secure login/signup
  • Role-based access: Admin / Analyst

🏗️ Architecture

┌─────────────────────────────────────────────────────────────────┐
│                        USER LAYER                               │
│   Admin/Analyst → Login/Auth → Dashboard UI → Manual Upload     │
└─────────────────────────────┬───────────────────────────────────┘
                              │
┌─────────────────────────────▼───────────────────────────────────┐
│                      INGESTION LAYER                            │
│   Simulation Mode (Simulated Stream) ←→ Queue/Streaming System  │
│                                      ←→ Manual Upload Input     │
└─────────────────────────────┬───────────────────────────────────┘
                              │
┌─────────────────────────────▼───────────────────────────────────┐
│                   PROCESSING LAYER (AI CORE)                    │
│                                                                 │
│  Preprocessing → Frame Extraction → Feature Extraction          │
│                                      ├─ Image/Video Embeddings  │
│                                      ├─ Perceptual Hashing      │
│                                      └─ OCR / Text Detection    │
│                                  → Similarity Matching Engine   │
│                                  → Decision Engine              │
│                                      ├─ High (>90%) → AUTO DMCA │
│                                      ├─ Medium (75-90%) → Review│
│                                      └─ Low (<75%) → Ignore     │
└─────────────────────────────┬───────────────────────────────────┘
                              │
┌─────────────────────────────▼───────────────────────────────────┐
│                       STORAGE LAYER                             │
│   Media DB │ Vector DB (embeddings) │ Incident DB │ User DB     │
└─────────────────────────────┬───────────────────────────────────┘
                              │
┌─────────────────────────────▼───────────────────────────────────┐
│                    OUTPUT / ACTION LAYER                        │
│  Dashboard │ Alerts │ DMCA Generation → Sending → Status Track  │
│  ROI Analytics Panel                                            │
└─────────────────────────────────────────────────────────────────┘

🛠️ Tech Stack

Frontend

Tech Purpose
React.js / Next.js Responsive dashboard UI
Tailwind CSS Styling

Backend

Tech Purpose
Node.js / FastAPI (Python) API, processing pipeline, DMCA workflow

AI & Machine Learning

Tech Purpose
Google Gemini API Content understanding & DMCA notice generation
OpenCV Image/video processing
Embeddings Semantic similarity detection
Perceptual Hashing (pHash) Transform-resistant fingerprinting
OCR (Tesseract / Cloud Vision) Meme text recognition

Cloud & Database

Tech Purpose
Google Cloud Platform (GCP) Core infrastructure
Firebase / Firestore Real-time database & authentication
Cloud Storage Media file storage

Vector Search

Tech Purpose
FAISS / Pinecone Fast similarity search for media matching

Auth & Streaming

Tech Purpose
Firebase Authentication Secure login/signup, role-based access
Queue-based pipeline Simulated real-time stream ingestion

🚀 Getting Started

Prerequisites

Installation

# 1. Clone the repository
git clone https://github.com/CodeGeek-Garvit/AthenaGuard1.git
cd AthenaGuard1

# 2. Install dependencies
npm install

# 3. Configure environment variables
cp .env.example .env.local

Environment Setup

Create .env.local in the root directory:

# Required
GEMINI_API_KEY=your_gemini_api_key_here

# Firebase (if configuring auth)
NEXT_PUBLIC_FIREBASE_API_KEY=your_firebase_api_key
NEXT_PUBLIC_FIREBASE_AUTH_DOMAIN=your_project.firebaseapp.com
NEXT_PUBLIC_FIREBASE_PROJECT_ID=your_project_id
NEXT_PUBLIC_FIREBASE_STORAGE_BUCKET=your_project.appspot.com
NEXT_PUBLIC_FIREBASE_MESSAGING_SENDER_ID=your_sender_id
NEXT_PUBLIC_FIREBASE_APP_ID=your_app_id

Run Locally

# Development server
npm run dev

# Production build
npm run build
npm start

App runs at http://localhost:3000


🔄 Process Flow

User Auth (Login/Signup)
        │
        ▼
   Mode Selection
   ┌────┴────┐
   ▼         ▼
Monitor    Verify
Mode       Mode
   │         │
   ▼         ▼
Simulated  Upload
Stream     Image/Video
   │         │
   └────┬────┘
        ▼
   AI Detection Engine
   ├─ Feature Extraction (embeddings, hashing)
   ├─ OCR for Meme Text
   └─ Similarity Matching
        │
        ▼
   Decision Engine
   ├─ HIGH (>90%)   → AUTO DMCA + Dashboard Alert
   ├─ MEDIUM (75-90%) → Manual Review Queue
   └─ LOW (<75%)    → Ignore
        │
        ▼
   DMCA Enforcement Flow
   Generate Notice → Send (simulated) → Track Status
        │
        ▼
   Output Layer
   Dashboard │ Alerts │ ROI Metrics

📸 MVP Screenshots

View Description
Security Overview Revenue protection, violation count, confidence, monitored reach
Monitoring Feed Live stream of detected violations with transformation tags
Incident Analysis Side-by-side original vs detected with AI explanation
DMCA Notice Auto-generated legal notice with export & send options
Manual Verification Drag-and-drop forensic scanning interface
Media Library Protected asset management with violation tracking
System & Compliance Stakeholder alignment + integration hooks

Live Demo: https://athenaguard-314163581128.asia-east1.run.app


💰 Cost Estimation

Development

  • Built by student team
  • Development cost: ₹0 (self-developed)

Monthly Cloud & AI (Production)

Service Cost/Month
Google Cloud (Compute + Storage) ₹3,000 – ₹6,000
Firebase (DB + Auth) ₹1,000 – ₹2,000
Gemini API (AI usage) ₹2,000 – ₹5,000
Total ₹6,000 – ₹13,000/month

Scalability Design

  • Cloud-native, pay-as-you-go
  • Parallel stream processing
  • Embedding-based vector search optimization
  • Modular microservice architecture
  • Distributed storage via GCP

🗺️ Roadmap

[NOW]  MVP Prototype
       ✅ Simulated real-time monitoring
       ✅ Manual verification
       ✅ DMCA generation

[NEXT] Platform Integration
       🔲 YouTube Data API v3 integration
       🔲 Instagram Graph API
       🔲 Real-time takedown workflows

[v3]   Advanced AI
       🔲 Full video-level tracking (not just frames)
       🔲 Live stream detection
       🔲 Improved short-clip analysis

[v4]   Automation
       🔲 Direct legal service integration
       🔲 Faster DMCA execution at scale

[v5]   Global Expansion
       🔲 OTT platform support
       🔲 Blockchain-based ownership verification
       🔲 Tamper-proof media authenticity tracking

🤝 Ecosystem Stakeholders

Stakeholder Role Value
BCCI Primary Content Owner IPL digital rights protection
Star Sports Official Broadcaster Exclusive broadcast slot verification
JioCinema Streaming Partner Piracy-led churn reduction
Trust & Safety Teams Platform Moderators Pre-verified flags, 40% faster review

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.


Built with ❤️ for Google Solution Challenge

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About

AthenaGuard is an AI‑powered platform that protects sports media from piracy and misuse. Unlike traditional tools, it detects unauthorized content even after cropping, mirroring, meme overlays, or compression. With real‑time monitoring, manual verification, automated DMCA workflows, and ROI analytics, it safeguards digital rights.

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