Protecting artificial intelligence IPs:a survey of watermarking and fingerprinting for machine learning

Artificial intelligence(AI)algorithms achieve outstanding results in many applicationdomains such as computer vision and natural language processing The performance ofAl models is the outcome of complex and costly model architecture design and trainingprocesses.Hence,it is paramount for model owners to protect their AI models frompiracy-model cloning,illegitimate distribution and use.IP protection mechanisms havebeen applied to Al models,and in particular to deep neural networks,to verify themodel ownership.State-of-the-art AI model ownership protection techniques have beensurveyed.The pros and cons of Al model ownership protection have been reported.The majonity of previous works are focused on watermarking,while more advancedmethods such fingerprinting and attestation are promising but not yet explored indepth.This study has been concluded by discussing possible research directions in thearea.