A network security posture assessment model based on binary semantic analysis.

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Title: A network security posture assessment model based on binary semantic analysis.
Authors: Wu, Dasheng1 (AUTHOR) 0107090@yzpc.edu.cn
Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications. Oct2022, Vol. 26 Issue 20, p10599-10606. 8p.
Subject Terms: *SUPERVISED learning, *COMPUTER network security, *DECISION support systems, *INTRUSION detection systems (Computer security), *POSTURE, *SEQUENTIAL analysis, *DECISION making
Abstract: Advancements of modern-day industry and the decision support systems have improved the progress of intelligent applications for performing critical tasks. Decision support system is any system or tool which has the potential or ability to support decision making activities. In this paper, a network security posture assessment model for decision making based on binary semantic analysis is proposed to address the problems of traditional network security. By semantic analysis of pre-compiled script files, the behavioral features of script files are obtained based on abstract syntax trees and the supervised learning of samples is performed using BP neural networks to obtain a detection model that can be used for unknown samples. Different from the existing detection methods based on semantic analysis, the network security posture assessment index system is first established, the weights of the indexes are determined by using the sequential relationship analysis method, and finally the binary semantic analysis method is introduced into the decision matrix to realize the network security posture assessment model. The simulation results of the study show that the introduction of binary semantic analysis and sequential relational analysis significantly improves the accuracy of network security posture assessment, and the proposed WebShell detection method has much high accuracy and recall rate. [ABSTRACT FROM AUTHOR]
Database: Academic Search Index
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  Data: A network security posture assessment model based on binary semantic analysis.
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  Data: <searchLink fieldCode="AR" term="%22Wu%2C+Dasheng%22">Wu, Dasheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 0107090@yzpc.edu.cn</i>
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  Data: *<searchLink fieldCode="DE" term="%22SUPERVISED+learning%22">SUPERVISED learning</searchLink><br />*<searchLink fieldCode="DE" term="%22COMPUTER+network+security%22">COMPUTER network security</searchLink><br />*<searchLink fieldCode="DE" term="%22DECISION+support+systems%22">DECISION support systems</searchLink><br />*<searchLink fieldCode="DE" term="%22INTRUSION+detection+systems+%28Computer+security%29%22">INTRUSION detection systems (Computer security)</searchLink><br />*<searchLink fieldCode="DE" term="%22POSTURE%22">POSTURE</searchLink><br />*<searchLink fieldCode="DE" term="%22SEQUENTIAL+analysis%22">SEQUENTIAL analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22DECISION+making%22">DECISION making</searchLink>
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  Data: Advancements of modern-day industry and the decision support systems have improved the progress of intelligent applications for performing critical tasks. Decision support system is any system or tool which has the potential or ability to support decision making activities. In this paper, a network security posture assessment model for decision making based on binary semantic analysis is proposed to address the problems of traditional network security. By semantic analysis of pre-compiled script files, the behavioral features of script files are obtained based on abstract syntax trees and the supervised learning of samples is performed using BP neural networks to obtain a detection model that can be used for unknown samples. Different from the existing detection methods based on semantic analysis, the network security posture assessment index system is first established, the weights of the indexes are determined by using the sequential relationship analysis method, and finally the binary semantic analysis method is introduced into the decision matrix to realize the network security posture assessment model. The simulation results of the study show that the introduction of binary semantic analysis and sequential relational analysis significantly improves the accuracy of network security posture assessment, and the proposed WebShell detection method has much high accuracy and recall rate. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s00500-021-06720-2
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 10599
    Subjects:
      – SubjectFull: SUPERVISED learning
        Type: general
      – SubjectFull: COMPUTER network security
        Type: general
      – SubjectFull: DECISION support systems
        Type: general
      – SubjectFull: INTRUSION detection systems (Computer security)
        Type: general
      – SubjectFull: POSTURE
        Type: general
      – SubjectFull: SEQUENTIAL analysis
        Type: general
      – SubjectFull: DECISION making
        Type: general
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      – TitleFull: A network security posture assessment model based on binary semantic analysis.
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            NameFull: Wu, Dasheng
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              M: 10
              Text: Oct2022
              Type: published
              Y: 2022
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              Value: 20
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            – TitleFull: Soft Computing - A Fusion of Foundations, Methodologies & Applications
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