Unknown Attack Traffic Classification in SCADA Network Using Heuristic Clustering Technique-Reference-Cited by-同舟云学术

Unknown Attack Traffic Classification in SCADA Network Using Heuristic Clustering Technique

Published:2023-09 Issue:3 Volume:20 Page:2625-2638
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Sheng Chuan¹,Yao Yu²^ORCID,Li Wenxuan²,Yang Wei³,Liu Ying²^ORCID

Affiliation:

1. Key Laboratory of Networked Control Systems and the Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China

2. School of Computer Science and Engineering and the Engineering Research Center of Security Technology of Complex Network System, Ministry of Education, Northeastern University, Shenyang, China

3. Software College, Northeastern University, Shenyang, China

Funder

National Key Research and Development Program of China

Special Research Assistant Program of Chinese Academy of Sciences

Doctoral Research Start-up Fund Project of Liaoning Province

2022 General Project of Basic Research Program of Shenyang Institute of Automation, Chinese Academy of Sciences

Independent Subject of State Key Laboratory of Robotics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/4275028/10274602/10023526.pdf?arnumber=10023526

Reference43 articles.

1. Clustering based semi-supervised machine learning for DDoS attack classification

2. Attack-classification;sheng,2022

3. A Survey of Android Malware Detection with Deep Neural Models

4. Honeyeye: A Network Traffic Collection Framework for Distributed ICS Honeynets

5. An effective network traffic classification method with unknown flow detection;jun;IEEE Trans Netw Service Manage,2013

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