OmniSafe Multi-modal Risk Content Detection

Project Overview

Developed “OmniSafe” (安盾), a comprehensive multi-modal risk content detection platform addressing AI-generated fraudulent content including fake text, deepfake videos, and synthetic audio.

Technical Architecture

Multi-modal Detection System

• Text Detection: DeepSeek-based model with sliding window attention for generated text and fraud detection
• Image Analysis: NoisePrint++ noise fingerprint technology for tampering region localization (97.1% accuracy)
• Video/Audio: Self-supervised learning for temporal feature extraction and audio difference detection
• Cross-modal Fusion: Integrated detection across text, image, video, audio, and multimedia content

Real-time Processing

• Response Time: <800ms real-time monitoring engine response
• Visualization: Automatic risk summary generation with confidence maps and risk heat distribution
• Scalability: Distributed architecture with GPU acceleration and multi-card inference

Platform Overview

OmniSafe Integrated AIGC Forged Content Detection Platform

Core Technologies

Advanced Detection Methods

• Text Analysis: Unknown fraud type detection with high accuracy
• Image Forensics: High-robustness detection in high-compression scenarios
• Temporal Analysis: Self-supervised learning for video and audio content verification
• API Integration: Lightweight API interfaces and plugin services for enterprise deployment

System Performance

• Detection Accuracy: >95% across core modalities with <3% false positive rate
• Performance: 2x better than competing products
• Deployment: Successfully demonstrated at Henan Provincial Public Security Department

Business Impact

Industry Recognition

• National Award: Challenge Cup “List to Solve” National First Prize
• Government Recognition: Included in Wuhan’s Top 10 AI Application Cases
• Enterprise Adoption: Partnership with Public Security Research Institute

Technical Leadership

• Architecture Design: Led multi-modal technology integration across 5 modalities and 12 detection systems
• Algorithm Optimization: Improved text detection accuracy to 95% and image F1-score to 96.5%
• Deployment Success: 60% improvement in solution adaptability for enterprise scenarios

Key Contributions

Innovation

• Multi-modal Integration: First comprehensive system covering text, image, video, audio, and multimedia
• Real-time Processing: Sub-second response time for critical security applications
• Enterprise Ready: Full deployment solution for government and enterprise clients

Research Impact

• Algorithm Development: Advanced methods for AI-generated content detection
• Industry Application: Practical solutions for cybersecurity and content verification
• Award Recognition: 19th Challenge Cup “List to Solve” Special Track - National First Prize