Session-Specific Watermarking for OTT Piracy Tracking
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Solution Overview
Problem
Existing techniques for preventing piracy of Over The Top (OTT) content are ineffective in determining the type of content being pirated, location, and perpetrator, and face challenges with user session-based watermarking due to high network bandwidth and storage requirements, as well as the difficulty in embedding and tracing watermarks in a large number of simultaneous user sessions.
Innovation Solution
A system and method utilizing an OTT Adaptive Bit Rate Streaming (ABR) engine and Content Delivery Network/Multi-access Edge Computing (CDN/MEC) nodes to dynamically generate and embed unique session-specific watermarks in OTT content media segments, reducing computational load and network bandwidth by shifting watermarking processes closer to the user and using feature detection techniques for embedding and tracing watermarks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user session based unique watermarking is implemented at the server end, then piracy tracking capability is improved, but network bandwidth requirements and storage requirements increase significantly
Solution Approach 1:
The watermarking process is segmented into two parts: a static watermark embedded in the original content at the server end, and a dynamic session-specific watermark applied at the edge computing node closer to the user. This segmentation allows piracy tracking while reducing the bandwidth and storage burden on the central server.
Solution Approach 2:
A CDN/MEC (Content Delivery Network/Multi-access Edge Computing) node is introduced as an intermediary between the server and the user device. This intermediary applies the session-specific watermark locally, eliminating the need for the server to handle individualized watermarked content for each user session, thus reducing network bandwidth and storage requirements.
2Reliability
If traditional fingerprinting or watermarking techniques are used, then content protection is provided, but the techniques fail when pirates clip the fingerprint or watermark before leaking the content
Solution Approach 1:
The watermarking system transitions from static watermarking to dynamic watermarking where the watermark changes with each user session. The session-specific watermark is generated based on user identification information and session parameters, making it impossible for pirates to successfully clip or remove the watermark without detection, as the watermark is continuously varying.
Solution Approach 2:
The system performs preliminary embedding of a static watermark in the original content, and then dynamically overlays session-specific watermarks at the edge computing node before content delivery. This preliminary action ensures that even if pirates attempt to clip watermarks, the underlying structure and session-specific variations allow for accurate piracy identification.
3Measurement precision
If session-specific watermarking is implemented for large number of simultaneous users, then individual piracy tracking is enabled, but computing load at the server end increases significantly
Solution Approach 1:
The CDN/MEC node acts as an intermediary that offloads the computationally intensive session-specific watermarking process from the central server. The server only needs to provide the static watermark and session identification information, while the edge node generates and applies the session-specific watermarks locally, significantly reducing server computing load.
Solution Approach 2:
The computing tasks are segmented between the server and edge computing nodes. The server handles content delivery and session management, while edge nodes handle the computationally intensive watermarking operations. This segmentation enables individual piracy tracking for large numbers of simultaneous users without overwhelming the central server's computing resources.
Data Source
AI summary
A system and a method for watermarking Over The Top (OTT) content delivered through OTT platform is provided. The system comprises an OTT Adaptive Bit Rate Streaming (ABR) engine configured to identify one or more frames associated with one or more OTT content media segments and one or more co-ordinate points associated with the OTT content media segments frames. Further, a unique session specific watermark is dynamically generated based on a received set of instructions from a user for playback of the OTT content media segments. The unique session specific watermark is associated with each user session. The system further comprising a Content Delivery Network/Multi access Edge Computing (CDN/MEC) node and the CDN/MEC node further comprising a watermark embedding unit configured to embed the generated session specific watermark in the identified co-ordinate points associated with the OTT content media segment frames.