While content owners rely on concurrency management techniques and DRM protected content to restrict unauthorized access, these solutions are not efficient to deter piracy on the user end. Watermarking solutions are thus increasingly being adopted by content producers and distributors to protect their digital assets from infringement and piracy.

Watermarking is the process of covertly embedding a signal or codec into a given piece of video content to help identify its ownership, authenticity, and copyrights. In addition, watermarks are also used to track the source of content leakage in the event of an infringement. Watermark detection is therefore the most crucial stage to identify and deter piracy attacks in DRM protected content. The integration of the video watermarking solution to end-to-end discovery, detection, analysis, enforcement, and reporting service therefore helps in identifying the source of leakage and taking timely action.

Content producers must rely on sophisticated web crawlers to detect pirated content at any point. For efficient watermark detection, multiple sites, including link aggregators, cyberlockers, live streaming, web video sites, and torrent sites must be checked. The detection service should also be able to identify which sites receive the highest volumes of pirated content and regularly determine the efficacy of the detection approach. It should also be cognizant of the evolving content distribution and piracy landscape both locally and internationally. This ensures optimal resource and budget allocation for anti-piracy solutions and provides a greater return on investment.

In addition to the aforementioned practices, content producers should also make use of emerging technologies, such as automation and AI, to aid video watermarking detection approaches. With the growing popularity of OTT and VoD content, the number of websites and link aggregators which provide premium content for free has also seen a tremendous rise in recent years. Hence, there is a huge amount of data that needs to be collected and analyzed which would be a time consuming and exhausting exercise without the use of automation.

A hybrid model which uses automation combined with human verification is, therefore, the best approach. In case the watermark payload is detected, the session database is used to find the relevant session information that matches the payload key value. This information can, then, be used to take the desired copyright enforcement approach or improve the video distribution in terms of its anti-piracy measures.

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