MF‐RF: A detection approach based on multi‐features and random forest algorithm for improved collusive interest flooding attack-Reference-Cited by-同舟云学术

MF‐RF: A detection approach based on multi‐features and random forest algorithm for improved collusive interest flooding attack

Published:2022-11-28 Issue: Volume: Page:
ISSN:1751-8709
Container-title:IET Information Security
language:en
Short-container-title:IET Information Security

Author:

Yue Meng¹,Peng Silin²^ORCID,Feng Wenzhi³

Affiliation:

1. College of Safety Science and Engineering Civil Aviation University of China Tianjin China

2. College of Electronic Information and Automation Civil Aviation University of China Tianjin China

3. University of the Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing China

Funder

Natural Science Foundation of Tianjin City

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Networks and Communications,Information Systems,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ise2.12100

Reference34 articles.

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2. A survey of information-centric networking

3. Gasti P. et al.:DoS and DDoS in named data networking Proc. Int. Conf. Computer Communications and Networks Nassau Bahamaspp.1–7(2013)

4. Yonghui X. et al.:Detection of collusive interest flooding attacks in named data networking using wavelet analysis. In:IEEE Military Commun. Conf. Baltimore MD USA pp.557–562(2017)

5. FR-RED: Fractal Residual Based Real-Time Detection of the LDoS Attack

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