Information Security Risk Management Model for Big Data

被引:1
|
作者
Yang, Min [1 ]
机构
[1] Chongqing City Vocat Coll, Chongqing 402160, Peoples R China
关键词
All Open Access; Gold;
D O I
10.1155/2022/3383251
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the current society of rapid expansion of information, big data have achieved vigorous development in all walks of life, considerably promoting data transmission and information sharing. Meanwhile, individuals are becoming increasingly reliant on big data and the Internet, but at the same time, the threat of information security posed by big data is becoming increasingly visible. As a result, how to protect the information security of big data has piqued the interest of both government and businesses. The essence of information security management is risk management, which is closely related to each other. Therefore, this study focuses on the following two aspects of research work. On the one hand, most existing risk management models merely describe risk management in the abstract from a macro-level, and they lack research on risk assessment, making them ineffective. This research builds a novel information security risk management model on the basis of existing risk management models based on the concept of multidimensional risk management. To achieve multidimensional dynamic management of big data risks and to keep them within an acceptable range as much as possible, the model is divided into five levels and two dimensions. On the other hand, this research also optimizes and improves the fuzzy mathematical analysis method and proposes a fuzzy comprehensive assessment method as the core algorithm for the risk assessment layer in the model. As a post-event risk assessment method, the advantage of this method is that it can comprehensively consider factors affecting risk and can quantify some assessment factors in the real network to achieve an effective combination of qualitative and quantitative, thereby providing a basis for decision-making in risk analysis and risk control. Finally, the effectiveness of the risk model in the real application is verified by example analysis, and it is intended that the study work would provide assistance and assurance for big data information security management.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Application of Big Data Technology in Enterprise Information Security Management and Risk Assessment
    Wang, Yawen
    Xue, Weixian
    Zhang, Anqi
    JOURNAL OF GLOBAL INFORMATION MANAGEMENT, 2023, 31 (03)
  • [2] Modeling Big Data Management Systems in Information Security
    Poltavtseva, M. A.
    Kalinin, M. O.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2019, 53 (08) : 895 - 902
  • [3] Modeling Big Data Management Systems in Information Security
    M. A. Poltavtseva
    M. O. Kalinin
    Automatic Control and Computer Sciences, 2019, 53 : 895 - 902
  • [4] Enterprise Financial Risk Identification and Information Security Management and Control in Big Data Environment
    Wei, Ran
    Yao, Sheng
    MOBILE INFORMATION SYSTEMS, 2021, 2021
  • [5] Big data and information security
    Gene Badia, Joan
    Gallo de Puelles, Pedro
    de Lecuona, Itziar
    ATENCION PRIMARIA, 2018, 50 (01): : 3 - 5
  • [6] Application of big data technology in enterprise information security management
    Ping Li
    Limin Zhang
    Scientific Reports, 15 (1)
  • [7] Prioritizing and Ranking the Big Data Information Security Risk Spectrum
    Bharathi S.V.
    Global Journal of Flexible Systems Management, 2017, 18 (3) : 183 - 201
  • [8] The Application of Big Data and Artificial Intelligence Technology in Enterprise Information Security Management and Risk Assessment
    Wang, Qi
    Zong, Bangfeng
    Lin, Yong
    Li, Zhuangzhuang
    Luo, Xv
    JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING, 2023, 35 (01)
  • [9] Big Data Management System Security Threat Model
    Poltavtseva, M. A.
    Zegzhda, D. P.
    Kalinin, M. O.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2019, 53 (08) : 903 - 913
  • [10] Big Data Management System Security Threat Model
    M. A. Poltavtseva
    D. P. Zegzhda
    M. O. Kalinin
    Automatic Control and Computer Sciences, 2019, 53 : 903 - 913