Research on Network Security Situational Awareness Based on Crawler Algorithm

Author:

Wu Xu1ORCID,Wei Dezhi2ORCID,Vasgi Bharati P.3ORCID,Oleiwi Ahmed Kareem4ORCID,Bangare Sunil L.5ORCID,Asenso Evans6ORCID

Affiliation:

1. Laboratory Management Center, Chengyi College, Jimei University, Xiamen, Fujian 361021, China

2. Department of Information Engineering, Chengyi College, Jimei University, Xiamen, Fujian 361021, China

3. Department of Information Technology, Marathwada Mitra Mandal’s College of Engineering, Pune, India

4. Department of Computer Technical Engineering, The Islamic University, Najaf 54001, Iraq

5. Department of Information Technology, Sinhgad Academy of Engineering, Savitribai Phule Pune University, Pune, India

6. Department of Agricultural Engineering, School of Engineering Sciences, University of Ghana, Accra, Ghana

Abstract

Network security situation awareness is a critical basis for security solutions because it displays the target system’s security state by assessing actual or possible cyber-attacks in the target system. Aiming at the security and stability of global information flow, this paper studies the perception and measurement of the overall situation of network security. Through the Scrappy web crawler framework, data were collected from several Zhiming network security event websites, and based on the vulnerability database of China Computer Network Intrusion Prevention Center, the network security event database was designed and established, which enriched the data of situational awareness research. This study investigates the analysis and processing of network security events, a crucial parameter in the stage of security insight and perception, and builds and implements a text-based network security event analysis tool. By designing a network security event analysis tool based on text processing, the data cleaning of network security time text information is completed, and a set of network security event processing solutions with high applicability and comprehensiveness are formed. Statistical experimental results show that the network security event database built based on the crawler algorithm contains 43,848 pieces of data, which increases the capacity by 12.79% and 29.33% compared with the traditional algorithm, and reduces the reading time by 63.5% and 87.2%.

Funder

Science and Technology Department of Henan Province

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

Reference37 articles.

1. Application of Machine Learning in Network Security Situational Awareness;Y. Zhao

2. Security challenges of big data computing;G. S. Sriram;International Research Journal of Modernization in Engineering Technology and Science,2022

3. Implementation of python data in online translation crawler website design

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