Application of Time Series and Clustering in Research of Information Vulnerabilities
- 10.2991/assehr.k.210407.101How to use a DOI?
- information security, clustering, text analysis, time series analysis
With the advent of the era of big data, computer networks have penetrated into every aspect of people’s life and work. While people enjoy the convenience brought by the Internet, they also face the threat of network security vulnerabilities, and it is urgent to strengthen network security. China National Information Security Vulnerability Database classifies information security vulnerabilities into 26 categories, such as configuration errors and SQL injection. With the increasing complexity of information security in the past two years, the traditional vulnerability classification standard has been subjected to new tests. In this paper, we use crawler technology to obtain vulnerability data from China National Information Security Vulnerability Database from 2004 to September 2020, time series analysis to predict the number of vulnerabilities, and use text analysis and clustering technology to re-cluster the vulnerabilities and derive new vulnerability classification levels and criteria.
- © 2021, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jing Nan AU - Ruiying Jin PY - 2021 DA - 2021/04/08 TI - Application of Time Series and Clustering in Research of Information Vulnerabilities BT - Proceedings of the 2021 6th International Conference on Social Sciences and Economic Development (ICSSED 2021) PB - Atlantis Press SP - 519 EP - 522 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.210407.101 DO - 10.2991/assehr.k.210407.101 ID - Nan2021 ER -