This is the public page of the Neural Network Watermarking (MPAI-NNW) standard project. The project is motivated by the use of  Neural Networks in an increasing variety of domains. The process of AI training is costly not only in terms of resources (GPUs, CPUs, memory) but also time. According to ThinkML, the development of a custom AI solution ranges from $ 6.000 to $300.000, while renting a pre-built module may cost around $ 40.000/year. Consequently, for the owner it becomes important to ensure traceability (owner) and for the user integrity of Neural Networks.

Watermarking is a technology inherited from the multimedia domain, regrouping a family of methodological and applicative tools allowing to imperceptibly and persistently insert some metadata into an original content. When applied to the AI world, the following is required:

  • Watermarking shall preserve the commercial value/usage of the original network and not affect the performance of the AI usage.
  • Metadata shall be recoverable even when the watermarked content was subjected to modifications.
  • The inserted metadata generally convey owner and network identity, and usage conditions.

There is significant literature around neural network watermarking presenting different objectives and testing methods. However, any technique can be either white-box, when the watermark is embedded inside the parameters of the network or black-box, when the watermark is embedded in the inference.

The MPAI Neural Network Watermarking (NNW) project is developing requirements for a future MPAI standard enabling the measure, for a given size of the watermarking payload, of

  1. The impact on the performance of the Neural Network.
  2. The resistance to modifications, e.g., transfer learning, pruning.
  3. The processing cost of watermark injection, e.g., time, processing cost.

Read The MPAI Neural Network Watermarking (NNW) project for more details.

If you wish to participate in this work you have the following options

  1. Join MPAI
  2. Participate until the MPAI-NNW Functional Requirements are approved (after that only MPAI members can participate) by sending an email to the MPAI Secretariat.
  3. Keep an eye on this page.

Return to the MPAI-NNW page.