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Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC
Joint Authors
An, Xingshuo
Lin, Fuhong
Yang, Lei
Zhou, Xianwei
Lü, Xing
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-14
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Fog computing, as a new paradigm, has many characteristics that are different from cloud computing.
Due to the resources being limited, fog nodes/MEC hosts are vulnerable to cyberattacks.
Lightweight intrusion detection system (IDS) is a key technique to solve the problem.
Because extreme learning machine (ELM) has the characteristics of fast training speed and good generalization ability, we present a new lightweight IDS called sample selected extreme learning machine (SS-ELM).
The reason why we propose “sample selected extreme learning machine” is that fog nodes/MEC hosts do not have the ability to store extremely large amounts of training data sets.
Accordingly, they are stored, computed, and sampled by the cloud servers.
Then, the selected sample is given to the fog nodes/MEC hosts for training.
This design can bring down the training time and increase the detection accuracy.
Experimental simulation verifies that SS-ELM performs well in intrusion detection in terms of accuracy, training time, and the receiver operating characteristic (ROC) value.
American Psychological Association (APA)
An, Xingshuo& Zhou, Xianwei& Lü, Xing& Lin, Fuhong& Yang, Lei. 2018. Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC. Wireless Communications and Mobile Computing،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216231
Modern Language Association (MLA)
An, Xingshuo…[et al.]. Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC. Wireless Communications and Mobile Computing No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1216231
American Medical Association (AMA)
An, Xingshuo& Zhou, Xianwei& Lü, Xing& Lin, Fuhong& Yang, Lei. Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC. Wireless Communications and Mobile Computing. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1216231
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1216231