Title: Automatic detection method of OSN content vulnerabilities based on big data analysis

Authors: Wei Chen

Addresses: Xianyang Normal University, Xianyang City, Shaanxi Province, 712000, China

Abstract: In order to realise the accurate and automatic detection of optical switch network (OSN) content vulnerability, an automatic detection method of OSN content vulnerability based on big data analysis is proposed. First, build OSN content vulnerability big data distribution model. Then, the detection statistics of its big data distribution are established. The association rule feature quantity of statistical time series is extracted for the data, and the association rule item of OSN content vulnerability is analysed by principal component analysis (PCA). Finally, fuzzy information clustering method is used to detect the location of OSN content vulnerability. The simulation results show that the method has the advantages of high precision, strong anti-interference ability and low time cost, and improves the safety and leakage-proof capability of the OSN content.

Keywords: big data analysis; OSN content; vulnerability; automatic detection; PCA; principal component analysis; simulation.

DOI: 10.1504/IJAACS.2020.109812

International Journal of Autonomous and Adaptive Communications Systems, 2020 Vol.13 No.2, pp.166 - 177

Received: 20 Aug 2019
Accepted: 07 Jan 2020

Published online: 24 Sep 2020 *

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