Risk prediction of information leakage in new product development stage based on data driven model

被引:2
|
作者
Wang Y. [1 ]
机构
[1] Business School, Huanggang Normal University, Huanggang
关键词
Data driven model; Game model; Information leakage; New product development; Risk prediction;
D O I
10.1504/IJPD.2021.116149
中图分类号
学科分类号
摘要
In order to overcome the problem of low prediction accuracy of current information disclosure risk prediction methods, this paper proposes a new risk prediction method for information leakage based on data-driven model. Based on the data-driven model, the new product development implementation process model is established. The generation and transmission characteristics of information in the new product development stage are analysed. The relationship between the information owner and the information thief is analysed by using the game model. According to the analysis results, the information leakage risk evaluation index system is constructed, and the comprehensive fuzzy evaluation method is used to solve the information leakage. According to the evaluation results, the information leakage risk is predicted. The experimental results show that the index significance coefficient of the proposed method is high, the critical ratio value can be controlled within 2, and the prediction accuracy is high. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码:114 / 129
页数:15
相关论文
共 50 条
  • [31] The Research on Risk Assessment of New Product Sample Development Stage in Manufacturing Enterprises
    Liu, Xiao-wei
    Liu, Xu-yun
    APPLIED ECONOMICS, BUSINESS AND DEVELOPMENT, 2011, 208 : 298 - +
  • [32] A data-driven framework to new product demand prediction: Integrating product differentiation and transfer learning approach
    Afrin, Kahkashan
    Nepal, Bimal
    Monplaisir, Leslie
    EXPERT SYSTEMS WITH APPLICATIONS, 2018, 108 : 246 - 257
  • [33] Development and validation of a risk prediction model and nomogram for colon adenocarcinoma based on methylation-driven genes
    Zhu, Liangyu
    Sun, Hongyu
    Tian, Guo
    Wang, Juan
    Zhou, Qian
    Liu, Pu
    Tang, Xuejiao
    Shi, Xinrui
    Yang, Lei
    Liu, Guangjie
    AGING-US, 2021, 13 (12): : 16600 - 16619
  • [34] A Two-Stage Bayesian Data-Driven Method to Improve Model Prediction
    Sun, Xiaozhuo
    Zeng, Xiankui
    Wu, Jichun
    Wang, Dong
    WATER RESOURCES RESEARCH, 2021, 57 (12)
  • [35] Management of information technology driven product development processes
    Joglekar, NR
    Yassine, AA
    NEW DIRECTIONS IN SUPPLY-CHAIN MANAGEMENT: TECHNOLOGY, STRATEGY, AND IMPLEMENTATION, 2002, : 125 - 152
  • [36] Maturity model for product development information
    Sinnwell, Chantal
    Siedler, Carina
    Aurich, Jan C.
    12TH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, 2019, 79 : 557 - 562
  • [37] Development of Cancer Risk Prediction Model that Incorporates Lifestyle and Biomarker Information
    Yamaji, Taiki
    CANCER SCIENCE, 2018, 109 : 404 - 404
  • [38] Process-driven quality improvement for scientific data based on information product map
    Zong, Wei
    Lin, Songtao
    Gao, Yuxing
    Yan, Yanying
    ELECTRONIC LIBRARY, 2022, 40 (03): : 177 - 195
  • [39] A Model Based Testing Approach for Model-Driven Development and Software Product Lines
    Perez Lamancha, Beatriz
    Polo Usaola, Macario
    Piattini Velthius, Mario
    EVALUATION OF NOVEL APPROACHES TO SOFTWARE ENGINEERING, 2011, 230 : 193 - +
  • [40] Combining Product Property Prediction Software and Metallurgical Level 2 Model For New Product Development
    Li, Bingji
    AISTECH 2013: PROCEEDINGS OF THE IRON & STEEL TECHNOLOGY CONFERENCE, VOLS I AND II, 2013, : 2449 - 2450