The term model fingerprinting originates from the fields of artificial intelligence, cybercrime and cybersecurity as well as digital transformation. The aim is to uniquely identify artificial intelligence models, similar to a human fingerprint. This ensures that a particular AI model is genuine and has not been secretly exchanged, copied or manipulated.
Imagine a company develops an AI model that recognises fraud. Without model fingerprinting, criminals could copy and adapt the model to produce false results or create security vulnerabilities. With model fingerprinting, the model leaves an invisible "fingerprint" that only authorised persons can recognise and check.
For companies and organisations, this means greater security in the use of artificial intelligence. Model fingerprinting not only protects intellectual property, but also preserves the performance and reliability of the AI models used. In a world where digital products are constantly being shared and processed, this technology is an important component of modern cybersecurity.