The proliferation of AI-generated deepfakes poses severe threats across multiple domains:
Rising Deepfake Threats:
- Deepfakes are increasingly used for misinformation, fraud, impersonation, and breaching law enforcement
- Cybercrime investigations and public safety are compromised
- Corporate environments face employment fraud through "ghost workers" bypassing remote hiring processes
Limitations of Current Detection Systems:
- Existing solutions are cloud-dependent, requiring clean video inputs
- Produce non-explainable binary outputs without confidence scoring
- Fail to comprehend context, nuance, or detect sophisticated manipulations
Real-World Failures:
- Detection models fail on compressed, re-recorded, or low-quality videos
- Cannot handle real-world scenarios with varying lighting, resolution, and compression
- Corporate impact includes millions lost to deepfake-enabled fraud
We propose an agent-driven deepfake detection system that addresses the critical gaps in current solutions through intelligent routing and specialized analysis.
Unlike traditional single-model approaches, INTERCEPTOR employs an intelligent agent with deterministic routing that:
- Fast Initial Screening: Uses a lightweight baseline model for rapid assessment
- Deterministic Smart Routing: Routes videos to specialist models based on file characteristics, not stochastic confidence
- Adaptive Analysis: Routes videos through appropriate specialists (compression, lighting, audio-visual, resolution, temporal)
- Forensic-Grade Consistency: Same video always routes to same specialists - suitable for legal/government use
- Edge Deployment: Functions without cloud dependency for real-time verification
Deterministic Routing vs Static Processing:
- Current systems process all videos through the same pipeline
- INTERCEPTOR adapts its analysis strategy based on deterministic video characteristics
- Same video = same routing every time - forensic consistency guaranteed
- Saves computational resources while maintaining detection quality
Multi-Specialist Architecture:
- Compression Specialist: Detects JPEG artifacts and encoding inconsistencies
- Lighting Specialist: Analyzes illumination patterns in low-light conditions
- Audio-Visual Specialist: Checks lip-sync and audio-visual correlation
- Resolution Specialist: Identifies upsampling and resolution manipulation
- Temporal Specialist: Examines frame-to-frame consistency
Deterministic Routing Innovation:
- File-Characteristic Based: Routing decisions based on bitrate, file size, format, and complexity
- 100% Reproducible: Same video always routes to same specialists across all runs
- Forensic-Grade: Suitable for legal proceedings and government applications
- Audit Trail: Complete documentation of routing decisions and reasoning
- Policy-Driven: Rule-based specialist selection eliminates stochastic behavior
Real-World Robustness:
- Handles compressed, re-recorded, and low-quality videos
- Works across varying lighting conditions and resolutions
- Provides explainable results with confidence scoring
Intel FakeCatcher:
- Cost: Hardware dependent
- Speed: ~20ms processing
- Deployment: Server-dependent
- Detection Strategy: Analyzes biological signals (blood flow)
- Primary Weakness: Cannot run on standard consumer devices, fails on highly compressed media
Microsoft Azure AI:
- Cost: $103k/year for enterprise
- Speed: Medium processing
- Deployment: Cloud API only
- Detection Strategy: Watermarking and content safety
- Primary Weakness: Requires uploading sensitive media to Microsoft servers
Hive AI:
- Cost: $0.50 per minute of video
- Speed: Medium/High processing
- Deployment: Cloud API
- Detection Strategy: Deep learning classifier
- Primary Weakness: Gives a score but no explanation, struggles with new attack types
Reality Defender:
- Cost: $299/month minimum
- Speed: Medium processing
- Deployment: SaaS/On-Prem
- Detection Strategy: Ensemble scanning
- Primary Weakness: Too expensive for individuals or small teams, slow onboarding
Freemium Model:
- Accessible to individuals and small teams
- High-speed processing through intelligent routing
- Web and SaaS deployment options
- Agentic intelligence adapts to video characteristics
- No primary weakness in accessibility or cost
1. Baseline Generalist Model
- Rapid initial assessment
- Identifies obvious manipulations
- Routes uncertain cases to specialists
2. Specialist Models
- Domain-specific detection capabilities
- Activated based on video characteristics
- Provide detailed analysis for specific artifact types
3. Agentic Routing Layer
- Analyzes video metadata (resolution, bitrate, compression)
- Determines optimal specialist combination
- Manages confidence thresholds and escalation
4. Explainability Engine
- Generates human-readable explanations
- Provides confidence scores per detection type
- Highlights specific artifacts detected
Edge Deployment:
- Lightweight models for on-device processing
- No cloud dependency for basic detection
- Privacy-preserving local analysis
Web Application:
- User-friendly interface for video upload
- Real-time processing and results
- Detailed forensic reports
API Integration:
- RESTful API for enterprise integration
- Batch processing capabilities
- Webhook support for automated workflows
"Trust-First" Freemium Model:
- 5 free forensic scans per user for video verification
- Power users (influencers, journalists) get Pro Shield subscription
- Unlimited credits for professional verification needs
"The Legal Bridge":
- Malicious deepfake analysis and reporting
- Generates Cyber Report compliant with Indian Penal Code standards
- Packages AI heatmap evidence for legal proceedings
- Ready-to-use documentation for police and courts
"INTERCEPTOR Validator Dashboard":
- HR and recruitment team integration
- Functions as plagiarism checker for video interviews
- Drag-and-drop candidate interview recording analysis
- Generates Human Verification Certificate
- Ensures hiring authenticity and prevents ghost worker fraud
- Implement baseline detection model using pre-trained EfficientNet
- Build video preprocessing pipeline
- Create basic confidence scoring system
- Develop compression artifact detector
- Implement lighting consistency analyzer
- Build audio-visual correlation checker
- Create simple routing logic based on video characteristics
- Implement agentic routing layer
- Build web interface for video upload
- Create results visualization with confidence scores
- Deploy basic explainability features
- Package for demonstration
Leveraging Existing Resources:
- Pre-trained models (EfficientNet, ResNet) for feature extraction
- Open-source deepfake datasets for validation
- Standard web frameworks (React, FastAPI) for rapid development
- Cloud deployment platforms (Vercel, Render) for quick hosting
Scope Management:
- Focus on 2-3 core specialists (compression, lighting, audio-visual)
- Implement basic routing logic with confidence thresholds
- Create functional MVP with essential features
- Demonstrate concept with real-world test cases
Frontend:
- React for web interface
- TailwindCSS for styling
- ApexCharts for visualization
Backend:
- FastAPI (Python) for API server
- PyTorch for model inference
- OpenCV for video processing
Models:
- EfficientNet-B4 for baseline detection
- Custom specialist modules for artifact detection
- Lightweight architectures for edge deployment
Deployment:
- Docker for containerization
- Vercel for frontend hosting
- Render/Railway for backend deployment
Database:
- PostgreSQL for user data
- MongoDB for analysis results
- Working web application for video upload and analysis
- Agentic routing system that adapts to video characteristics
- Multiple specialist models for different artifact types
- Explainable results with confidence scoring
- API endpoints for programmatic access
- Process various types of deepfake videos
- Show intelligent routing decisions
- Display confidence scores and explanations
- Compare performance against single-model approaches
- Demonstrate edge deployment potential
- First agentic approach to deepfake detection
- Intelligent resource allocation through routing
- Multi-specialist architecture for comprehensive analysis
- Explainable AI for trust and transparency
- Accessible freemium model for widespread adoption
Target Market:
- Individual users concerned about media authenticity
- Journalists and fact-checkers verifying content
- Law enforcement agencies investigating cybercrimes
- HR departments preventing hiring fraud
- Social media platforms moderating content
Competitive Advantage:
- Lower cost than enterprise solutions
- Faster processing through intelligent routing
- Better explainability than black-box systems
- More accessible than hardware-dependent solutions
- More comprehensive than single-model approaches
Post-Hackathon Roadmap:
- Expand specialist model coverage (resolution, temporal analysis)
- Implement advanced ensemble techniques
- Add support for image and audio-only deepfakes
- Develop mobile applications for on-device detection
- Create browser extensions for real-time verification
- Build enterprise features (batch processing, API rate limiting)
- Integrate with social media platforms for automated flagging
INTERCEPTOR represents a paradigm shift in deepfake detection through its agentic intelligence approach. By combining intelligent routing with specialized analysis, we deliver a solution that is faster, more accurate, and more explainable than existing alternatives. Our freemium model ensures accessibility while our technical architecture provides the robustness needed for real-world deployment.