Model watermarking is a term from the fields of Artificial Intelligence, Cybersecurity, and Digital Transformation. It describes a technique used by AI model developers to embed invisible markings or „watermarks“ into their algorithms. These watermarks help to identify an AI model as intellectual property and protect it against unauthorised use or theft.
A clear example: A company develops an artificial intelligence for detecting counterfeit products. The developers incorporate model watermarking, which acts like an invisible fingerprint in the code. If the model appears elsewhere, the developers can prove it is their property.
Model watermarking is becoming increasingly important as AI models are valuable business assets. Companies protect their investments and prevent competitors from using illegally developed models. For IT security, this means additional protection against cyberattacks and data theft.
The principle is comparable to a watermark on banknotes: it is not visible but clearly protects against counterfeiting. This keeps intellectual property better protected in the field of artificial intelligence.
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