BotDetector: An extreme learning machine‐based Internet of Things botnet detection model-Reference-Cited by-同舟云学术

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BotDetector: An extreme learning machine‐based Internet of Things botnet detection model

Published:2020-06-16 Issue:5 Volume:32 Page:
ISSN:2161-3915
Container-title:Transactions on Emerging Telecommunications Technologies
language:en
Short-container-title:Trans Emerging Tel Tech

Author:

Dong Xudong¹²^ORCID,Dong Chen¹²³⁴^ORCID,Chen Zhenyi⁵^ORCID,Cheng Ye¹^ORCID,Chen Bo¹³^ORCID

Affiliation:

1. College of Mathematics and Computer Science Fuzhou University Fuzhou China

2. Key Lab of Information Security of Network Systems Fuzhou University Fuzhou China

3. Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

4. Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Systems Fuzhou China

5. Department of Electrical Engineering University of South Florida Tampa Florida USA

Funder

The Foundation of the Education Department of Fujian Province, China

The National Natural Science Foundation of China

The Science Foundation of the Fujian Province, China

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ett.3999

Reference40 articles.

1. Runtime model based approach to IoT application development

2. An empirical investigation of botnet as a service for cyberattacks

3. FeilyM ShahrestaniA RamadassS. A survey of botnet and botnet detection. Paper presented at: 2009 Third International Conference on Emerging Security Information Systems and Technologies. IEEE;2009:268‐273.

4. RonenE ShamirA. Extended functionality attacks on IoT devices: The case of smart lights. Paper presented at: 2016 IEEE European Symposium on Security and Privacy (EuroS&P). IEEE;2016: 3‐12.

5. DDoS in the IoT: Mirai and Other Botnets

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