An Improved Integrated Prediction Method of Cyber Security Situation Based on Spatial-time Analysis

被引:7
|
作者
Fan, Zhijie [1 ,2 ]
Tan, Zhiping [3 ]
Tan, Chengxiang [1 ]
Li, Xin [4 ]
机构
[1] Tongji Univ, Elect & Informat Engn Sch, Shanghai, Peoples R China
[2] Minist Publ Secur, Res Inst 3, Beijing, Peoples R China
[3] Huawei Technol Co Ltd, Shenzhen, Peoples R China
[4] Peoples Publ Secur Univ China, Coll Informat Technol & Cyber Secur, Beijing, Peoples R China
来源
JOURNAL OF INTERNET TECHNOLOGY | 2018年 / 19卷 / 06期
基金
国家高技术研究发展计划(863计划); 国家重点研发计划;
关键词
Cyber security; Situation prediction; Fuzzy cognitive maps; Time and spatial dimension;
D O I
10.3966/160792642018111906015
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cyber security situation awareness, as an effective supplement in cyber security protection measures, has been one of the research focus in recent years. In particular, cyber security situation prediction has become a hotspot of research. However, the existing cyber security situation prediction methods neglect the influence of future security elements when measuring the future security situation. Another fact is that the relationships among the security elements are always ignored. In this work, we presented an improved integrated cyber security situation prediction method based on spatial-time analysis from a new perspective. We described cyber security elements in different levels by a hierarchical index system. Then we predicted the future security elements independently in time dimension. In the process of spatial dimension prediction, we made a fusion prediction of the future security elements by using Fuzzy Cognitive Maps (FCM), and meanwhile, we corrected the prediction in spatial dimension prediction by using threat intelligence data. Finally, we used DARPA2000 datasets that is from Lincoln Laboratory Scenario (DDOS) to verify and analyze our method. The experimental result shows that the proposed method can model the future cyber security situation in network environment in a more accurate way by comparing with other similar methods.
引用
收藏
页码:1789 / 1800
页数:12
相关论文
共 50 条
  • [41] Dynamic Network Security Situation Prediction based on Bayesian Attack Graph and Big Data
    Lin, Pengwen
    Chen, Yonghong
    PROCEEDINGS OF 2018 IEEE 4TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2018), 2018, : 992 - 998
  • [42] Research on Security Situation Prediction of Equipment Support Information Network Based on Bayesian Network
    Li, Xi
    Lu, Yu
    Liu, Sen
    PROCEEDINGS OF 2017 8TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2017), 2017, : 869 - 873
  • [43] DWT-based anomaly detection method for cyber security of wireless sensor networks
    Saganowski, Lukasz
    Andrysiak, Tomasz
    Kozik, Rafal
    Choras, Michal
    SECURITY AND COMMUNICATION NETWORKS, 2016, 9 (15) : 2911 - 2922
  • [44] Assessing the Security of a Cyber-Physical System Based on an Analysis of Malware Signatures
    Moskvin, D. A.
    AUTOMATIC CONTROL AND COMPUTER SCIENCES, 2023, 57 (08) : 894 - 903
  • [45] Industry 4.0 & cyber security - Technology and requirement analysis based on RAMI 4.0
    Flatt, Holger
    Schriegel, Sebastian
    Trsek, Henning
    Adamczyk, Heiko
    Jasperneite, Juergen
    ATP EDITION, 2016, (7-8): : 32 - 39
  • [46] Assessing the Security of a Cyber-Physical System Based on an Analysis of Malware Signatures
    D. A. Moskvin
    Automatic Control and Computer Sciences, 2023, 57 : 894 - 903
  • [47] An Actor-Based Approach for Security Analysis of Cyber-Physical Systems
    Moradi, Fereidoun
    Asadollah, Sara Abbaspour
    Sedaghatbaf, Ali
    Causevic, Aida
    Sirjani, Marjan
    Talcott, Carolyn
    FORMAL METHODS FOR INDUSTRIAL CRITICAL SYSTEMS, FMICS 2020, 2020, 12327 : 130 - 147
  • [48] Multiscale Entropy-based Weighted Hidden Markov Network Security Situation Prediction Model
    Liang, Wei
    Chen, Zuo
    Yan, Xiaolong
    Zheng, Lxiaodong
    Zhuo, Ping
    2017 IEEE 2ND INTERNATIONAL CONGRESS ON INTERNET OF THINGS (IEEE ICIOT), 2017, : 97 - 104
  • [49] Social Relationships and Temp-Spatial Behaviors Based Community Discovery to Improve Cyber Security Practices
    Cao, Jiuxin
    Liu, Weijia
    Cao, Biwei
    Wang, Pan
    Li, Shancang
    Liu, Bo
    Iqbal, Muddesar
    IEEE ACCESS, 2019, 7 : 105973 - 105986
  • [50] Quantitative Method for Security Situation of the Power Information Network Based on the Evolutionary Neural Network
    Yuan, Quande
    Pi, Yuzhen
    Kou, Lei
    Zhang, Fangfang
    Ye, Bo
    FRONTIERS IN ENERGY RESEARCH, 2022, 10