Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (3)
  • Open Access

    ARTICLE

    Identifying Industrial Control Equipment Based on Rule Matching and Machine Learning

    Yuhao Wang, Yuying Li, Yanbin Sun, Yu Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 577-605, 2023, DOI:10.32604/cmes.2023.026791 - 23 April 2023

    Abstract To identify industrial control equipment is often a key step in network mapping, categorizing network resources, and attack defense. For example, if vulnerable equipment or devices can be discovered in advance and the attack path can be cut off, security threats can be effectively avoided and the stable operation of the Internet can be ensured. The existing rule-matching method for equipment identification has limitations such as relying on experience and low scalability. This paper proposes an industrial control device identification method based on PCA-Adaboost, which integrates rule matching and machine learning. We first build a More >

  • Open Access

    ARTICLE

    Research on Network Resource Optimal Allocation Algorithm Based on Game Theory

    Xiaojuan Yuan1,2,*

    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 249-257, 2021, DOI:10.32604/iasc.2021.013637 - 07 January 2021

    Abstract This paper briefly introduced the structure of heterogeneous cellular network and two algorithms which are used for optimizing the network resource allocation scheme: dynamic game algorithm based on spectrum allocation and the game allocation algorithm based on power allocation and alliance. After that, the two algorithms were simulated in MATLAB software and compared with another power iterative allocation algorithm based on non-cooperative game. The results showed that the system energy efficiency of the three algorithms decreased with the increase of the number of small base stations in the network; with the increase of the number More >

  • Open Access

    ARTICLE

    Hierarchical Optimization of Network Resource for Heterogeneous Service in Cloud Scenarios

    Dong Huanga,b, Yong Baib, Jingcheng Liuc, Hongtao Chend, Jinghua Lind, Jingjing Wud

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 883-889, 2018, DOI:10.1080/10798587.2017.1327634

    Abstract With limited homogeneous and heterogeneous resources in a cloud computing system, it is not feasible to successively expand network infrastructure to adequately support the rapid growth in the cloud service. In this paper, an approach for optimal transmission of hierarchical network for heterogeneous service in Cloud Scenarios was presented. Initially, the theoretical optimal transmission model of a common network was transformed into the hierarchical network with the upper and lower optimization transmission model. Furthermore, the computation simplification and engineering transformation were presented for an approximation method at the low cost of computational complexity. In the More >

Displaying 1-10 on page 1 of 3. Per Page