A Novel SMP-based Survivability Evaluation Metric and Approach in Wireless Sensor Network
- School of Computer & Communication Engineering, University of Science and Technology
Beijing 100083,China
chenhs@ustb.edu.cn - Railway Police College
Zhengzhou, Henan, 450053, China
zhuanghaiyan@rpc.edu.cn - State Information Center of China
Beijing 100045, China
shanzg@sic.gov.cn - Department of Electronic Engineering, National Taipei University of Technology
Taipei City, China
chlee@ntut.edu.tw - Department of computer science, Harbin Institute of Technology
Harbin 150001, China
15124585561@163.com
Abstract
In Industrial Internet of Things (IIoT) device and network, wireless sensor network (WSN) is an important component.Routing protocol is the critical component of WSN. As the WSN may be attacked by all kinds of intruders, the survivability of WSN is important to IIoT security. To precisely evaluate the systematic survivability ability under external attack and internal security mechanism,a novel survivability entropy-based quantitative evaluation metric is proposed to calculate the systematic survivability ability of WSN routing protocol. Numerical analysis and simulation experiments are combined to precisely calculate the survivability entropy metric.To validate the evaluation approach, NS2 (Network simulator) is used to simulate the DoS attack and security mechanism in WSN. Experimental results show that the novel survivability evaluation metric and method can precisely evaluate the systematic survivability ability of WSN.
Key words
survivability entropy, quantitative evaluation, systematic survivability, wireless sensor network
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS180918024C
Publication information
Volume 16, Issue 3 (October 2019)
Recent Advances in Information Processing and Security
Year of Publication: 2019
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
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How to cite
Chen, H., Zhuang, H., Shan, Z., Lee, C., Fu, Z.: A Novel SMP-based Survivability Evaluation Metric and Approach in Wireless Sensor Network. Computer Science and Information Systems, Vol. 16, No. 3, 733–751. (2019), https://doi.org/10.2298/CSIS180918024C