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2022-11-25
Hou, Jundan, Jia, Xiang.  2021.  Research on enterprise network security system. 2021 2nd International Conference on Computer Science and Management Technology (ICCSMT). :216—219.
With the development of openness, sharing and interconnection of computer network, the architecture of enterprise network becomes more and more complex, and various network security problems appear. Threat Intelligence(TI) Analysis and situation awareness(SA) are the prediction and analysis technology of enterprise security risk, while intrusion detection technology belongs to active defense technology. In order to ensure the safe operation of computer network system, we must establish a multi-level and comprehensive security system. This paper analyzes many security risks faced by enterprise computer network, and integrates threat intelligence analysis, security situation assessment, intrusion detection and other technologies to build a comprehensive enterprise security system to ensure the security of large enterprise network.
2020-01-02
Shabanov, Boris, Sotnikov, Alexander, Palyukh, Boris, Vetrov, Alexander, Alexandrova, Darya.  2019.  Expert System for Managing Policy of Technological Security in Uncertainty Conditions: Architectural, Algorithmic, and Computing Aspects. 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). :1716–1721.

The paper discusses the architectural, algorithmic and computing aspects of creating and operating a class of expert system for managing technological safety of an enterprise, in conditions of a large flow of diagnostic variables. The algorithm for finding a faulty technological chain uses expert information, formed as a set of evidence on the influence of diagnostic variables on the correctness of the technological process. Using the Dempster-Schafer trust function allows determining the overall probability measure on subsets of faulty process chains. To combine different evidence, the orthogonal sums of the base probabilities determined for each evidence are calculated. The procedure described above is converted into the rules of the knowledge base production. The description of the developed prototype of the expert system, its architecture, algorithmic and software is given. The functionality of the expert system and configuration tools for a specific type of production are under discussion.