HDCP Stream Analysis via Low-Resolution Artifact Extraction
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Solution Overview
Problem
Conventional predictive analytics for advertisement targeting in content distribution networks face limitations due to 'siloing' of content experiences caused by embedded applications, which restrict visibility into media consumption activities, especially when copy-protected streams are involved, leading to reduced effectiveness in advertising relevance and user interest analysis.
Innovation Solution
The method involves splitting HDCP-encrypted data streams into high-definition and low-resolution components, extracting audio and video artifacts from the low-resolution stream for analysis, deriving signature markers, and sending them to user devices to infer content consumption patterns, thereby enhancing advertising targeting and content synchronization across networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If HDCP-encrypted high-definition streams are transmitted to user devices, then content protection and security are improved, but visibility into media consumption activities is lost
Solution Approach 1:
The system segments the HD stream into multiple lower-resolution streams (e.g., 480p, 360p, 240p) that can be analyzed without compromising the protected HD content. These segmented lower-resolution versions allow content identification and consumption tracking while the original HD stream remains encrypted and protected.
Solution Approach 2:
The system introduces an intermediary analysis process that receives lower-resolution versions of the content, identifies artifacts, and generates signatures without directly accessing or decrypting the protected HD stream. This intermediary layer enables consumption tracking while maintaining content security.
2Measurement precision
If full-resolution streams are analyzed for content identification, then analysis accuracy is improved, but data processing volume and complexity increase
Solution Approach 1:
Instead of analyzing the complete high-resolution stream, the system applies partial action by analyzing only lower-resolution versions (e.g., 480p, 360p, 240p) that contain sufficient artifacts for content identification. This partial analysis achieves adequate precision while significantly reducing processing complexity.
Solution Approach 2:
The system extracts only the necessary lower-resolution components from the full HD stream for analysis purposes. By taking out and analyzing only the essential artifact-containing portions at reduced resolution, the system maintains identification accuracy while minimizing processing demands.
Data Source
AI summary
In one example, a method performed by a processing system including at least one processor includes obtaining a first stream of audio and video data, wherein the first stream of audio and video data comprises a lower-resolution version of a second stream of audio and video data that is transmitted to a first user device over a content distribution network and encrypted using a high-bandwidth digital content protection protocol, performing an analysis technique on the first stream of audio and video data in order to extract audio and video artifacts which from which content of the first stream of audio and video data is inferred, deriving a signature marker from the audio and video artifacts, and sending the signature marker to the first user device.