Automatic detection method of OSN content vulnerabilities based on big data analysis Online publication date: Thu, 24-Sep-2020
by Wei Chen
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 13, No. 2, 2020
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.
Online publication date: Thu, 24-Sep-2020
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Autonomous and Adaptive Communications Systems (IJAACS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org