Video Analytics Privacy Preserving Module for Biometric Data Redaction
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Solution Overview
Problem
Existing video streaming technologies face challenges in protecting user-specific sensitive information from leakage, particularly in video analytics, where biometric data is exposed, leading to potential adversarial attacks and privacy concerns.
Innovation Solution
A system incorporating a Video Analytics and Privacy Preserving (VA-PP) module that processes video streams by decoding frames, extracting sensitive information, identifying features, and replacing them with new predefined pixels, using techniques like Up Gradient-False Color Conversion-with Noise and Adversarial Pixel, to create a new section of frames that preserves privacy and prevents sensitive information exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video analytics processing is performed to extract biometric data, then useful information is obtained, but user privacy is compromised and sensitive data leaks
Solution Approach 1:
The patent extracts and removes sensitive biometric information from video frames through automated detection and redaction. The system identifies regions containing biometric data (faces, fingerprints, iris) and extracts them for removal or replacement with placeholder blocks, thereby preventing privacy leakage while preserving useful video analytics
Solution Approach 2:
The patent introduces an intermediary privacy protection module that sits between video capture and analytics processing. This intermediary layer automatically detects, classifies, and redacts sensitive biometric information before it reaches downstream analytics systems, mediating between the need for data extraction and privacy protection
2Measurement precision
If deep learning models are deployed for video analytics, then processing accuracy is improved, but vulnerability to adversarial attacks increases
Solution Approach 1:
The patent applies preliminary anti-action by implementing adversarial training and defense mechanisms before deployment. The system pre-trains deep learning models with adversarial examples and applies input validation to detect and neutralize adversarial perturbations, preventing attacks before they can compromise the analytics accuracy
Solution Approach 2:
The patent modifies model parameters and processing parameters to enhance robustness. This includes changing model architecture parameters, adjusting preprocessing parameters (normalization, augmentation), and modifying inference parameters (temperature, confidence thresholds) to reduce vulnerability to adversarial attacks while maintaining accuracy
3Reliability
If comprehensive video monitoring is implemented, then security coverage is enhanced, but privacy leakage risk increases
Solution Approach 1:
The patent applies local quality by implementing selective privacy protection only in regions containing sensitive information. Instead of obscuring entire video feeds, the system applies redaction masks and blurring effects only to specific local regions (faces, license plates, sensitive objects) while leaving the rest of the video clear for security monitoring
Solution Approach 2:
The patent segments the video processing pipeline into distinct functional modules: capture, sensitive region detection, classification, redaction application, and output. This segmentation allows comprehensive monitoring while isolating privacy-sensitive operations to specific processing stages where controlled intervention occurs
Data Source
AI summary
The present invention provides a robust and effective solution to an entity or an organization by enabling the entity to implement a system for that links together a wide variety of media processing systems to complete complex workflows. The system can be configured to read files in one format, process the files, and export the files in another. The system can be a cross-platform and can be easily ported to various operating systems and can be used to integrate privacy preserving components into the system.