Network anomaly detection using a cross‐correlation‐based long‐range dependence analysis-Reference-Cited by-同舟云学术

Network anomaly detection using a cross‐correlation‐based long‐range dependence analysis

Published:2020-07-30 Issue:6 Volume:30 Page:
ISSN:1055-7148
Container-title:International Journal of Network Management
language:en
Short-container-title:Int J Network Mgmt

Author:

AsSadhan Basil¹^ORCID,Alzoghaiby Abraham²^ORCID,Binsalleeh Hamad³,Kyriakopoulos Konstantinos G.⁴,Lambotharan Sangarapillai⁴

Affiliation:

1. Department of Electrical Engineering King Saud University Riyadh Saudi Arabia

2. National Center for Radar and EW King Abdulaziz City for Science and Technology Riyadh Saudi Arabia

3. Department of Computer Science Al‐Imam Mohammad Ibn Saud Islamic University Riyadh Saudi Arabia

4. Wolfson School of Mechanical, Electrical and Manufacturing Engineering Loughborough University Loughborough UK

Funder

Gulf Science, Innovation, and Knowledge Economy Programme of the U.K. Government

Research Center at the College of Engineering, King Saud University.

Publisher

Wiley

Subject

Computer Networks and Communications,Computer Science Applications

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nem.2129

Reference44 articles.

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3. Anomaly detection

4. Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection

5. Cloud in the crosshairs.14th Annual Worldwide Infrastructure Security Report.tech. rep. NETSCOUT Systems Inc;2019.https://www.netscout.com/report/

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