Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2–4, 2023, Nanchang, China

Research Article

Sensitive Data Discovery Technology Based on Artificial Intelligence

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  • @INPROCEEDINGS{10.4108/eai.2-6-2023.2334615,
        author={Jie  SHI and ShuFang  Cui and Fei  Chen and ChengTao  Wang},
        title={Sensitive Data Discovery Technology Based on Artificial Intelligence},
        proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2023},
        month={8},
        keywords={data sharing; sensitive data; sensitive data discovery},
        doi={10.4108/eai.2-6-2023.2334615}
    }
    
  • Jie SHI
    ShuFang Cui
    Fei Chen
    ChengTao Wang
    Year: 2023
    Sensitive Data Discovery Technology Based on Artificial Intelligence
    ICIDC
    EAI
    DOI: 10.4108/eai.2-6-2023.2334615
Jie SHI1, ShuFang Cui2,*, Fei Chen2, ChengTao Wang2
  • 1: China Todacco SiChuan Industrial LLC
  • 2: WuHan Windoor Information Technology Co., LTD
*Contact email: 228605126@qq.com

Abstract

Enterprises will produce a large number of sensitive data with great value in production activities and management. If handled improperly, it will lead to data security incidents. Effective discovery and desensitization of these sensitive data is the premise of data security sharing. This paper refers to the relevant theoretical research and technical practice of sensitive data discovery at home and abroad, studies the discovery methods of sensitive data according to the application scenarios of manufacturing enterprises, and studies the sensitive data discovery method based on artificial intelligence for manufacturing enterprises which have frequently updated and unfixed sensitive data. Using the artificial intelligence technology to improve the sensitive data discovery, a sensitive data discovery method based on CRF-BiLSTM-CNN model is proposed. The experiment shows that it can provide a new solution for the current and future sensitive data discovery of manufacturing enterprises and provide support for data security governance and digital transformation of manufacturing enterprises.