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Guidance of Enterprise Team Division Based on Security Awareness and Interaction

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Intelligent Human Systems Integration (IHSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 722))

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Abstract

In order to reduce the occurrence of unsafe behavior and aggregate the personal employee safety consciousness, a personal security awareness model based on social cluster self-organization is presented. First of all, according to the individual number of employees N, the number of topology K between individual employees is traversed, and the dynamic trend of individual security awareness of employees is simulated by using Matlab software. Then, using the statistical data analysis software package SPSS, the obvious tendency of aggregation when N and the minimum number of topology K are analyzed, we get that there is a linear relationship between N and K by fitting. Thus, it can combine the Behavior-Based Safety (BBS) theory and the enterprise scale to guide the security partition of the enterprise teams and groups, so that the individual safety awareness of employees can reach the same level.

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Acknowledgments

This research reported herein was supported by the NSFC of China under Grants No. 71571091 and 71771112.

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Authors and Affiliations

  1. School of Electronics and Information Engineering, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, People’s Republic of China

    Yun-lu Zhang

  2. Graduate School, University of Science and Technology Liaoning, Anshan, 114051, Liaoning, People’s Republic of China

    Xue-bo Chen

Authors
  1. Yun-lu Zhang
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  2. Xue-bo Chen
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Corresponding author

Correspondence to Xue-bo Chen .

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Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Waldemar Karwowski

  2. University of Central Florida, Orlando, Florida, USA

    Tareq Ahram

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Zhang, Yl., Chen, Xb. (2018). Guidance of Enterprise Team Division Based on Security Awareness and Interaction. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_64

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  • DOI: https://doi.org/10.1007/978-3-319-73888-8_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73887-1

  • Online ISBN: 978-3-319-73888-8

  • eBook Packages: EngineeringEngineering (R0)

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