Computer Science ›› 2021, Vol. 48 ›› Issue (7): 9-16.doi: 10.11896/jsjkx.201200204

Special Issue: Artificial Intelligence Security

• Artificial Intelligence Security • Previous Articles     Next Articles

Survey on Artificial Intelligence Model Watermarking

XIE Chen-qi, ZHANG Bao-wen, YI Ping   

  1. School of Cyber Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
  • Received:2020-12-23 Revised:2021-03-19 Online:2021-07-15 Published:2021-07-02
  • About author:XIE Chen-qi,born in 1997,postgra-duate.His main research interests include artificial intelligence security and so on.(deadlyone@sjtu.edu.cn)
    YI Ping,born in 1969,Ph.D,associate professor,is a senior member of China Computer Federation.His main research interests include artificial intelligence security and so on.
  • Supported by:
    National Key Research and Development Project of China(2020YFB1807504,2020YFB1807500).

Abstract: In recent years,with the rapid development of artificial intelligence,it has been used in voice,image and other fields,and achieved remarkable results.However,these trained AI models are very easy to be copied and spread.Therefore,in order to protect the intellectual property rights of the models,a series of algorithms or technologies for model copyright protection emerge as the times require,one of which is model watermarking technology.Once the model is stolen,it can prove its copyright through the verification of the watermark,maintain its intellectual property rights and protect the model.This technology has become a hot spot in recent years,but it has not yet formed a more unified framework.In order to better understand,this paper summarizes the current research of model watermarking,discusses the current mainstream model watermarking algorithms,analyzes the research progress in the research direction of model watermarking,reproduces and compares several typical algorithms,and finally puts forward some suggestions for future research direction.

Key words: Algorithm flow, Algorithm performance comparison, Artificial intelligence security, Information redundancy, Model watermarking

CLC Number: 

  • TP393
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