A DDoS Attack Detection System for Industry 5.0 using Digital Twins and Machine Learning-Reference-Cited by-同舟云学术

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A DDoS Attack Detection System for Industry 5.0 using Digital Twins and Machine Learning

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)
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Author:

Gaurav Akshat¹,Gupta Brij B.²,Tai Chui Kwok³,Arya Varsha⁴,Benkhelifa Elhadj⁵

Affiliation:

1. Ronin Institute,Montclair,NJ,USA

2. Asia University,International Center for AI and Cyber Security Research and Innovations (CCRI),Department of Computer Science and Information Engineering,Taichung,Taiwan,413

3. Hong Kong Metropolitan University (HKMU)

4. Asia University,Taichung,Taiwan

5. Staffordshire University,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10315246/10315146/10315663.pdf?arnumber=10315663

Reference20 articles.

1. Advanced Cryptographic Standards-Based Secure Data Protocol for Distributed Data Storage and Communication in the Cloud

2. Business Process Discovery Using Process Mining Techniques and Distributed Framework

3. Understanding Universal Adversarial Attack and Defense on Graph

4. A Review on Detection and Mitigation Analysis of Distributed Denial of Service Attacks and Their Effects on the Cloud

5. Spintronics Based Non-Volatile MRAM for Intelligent Systems

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analysis of Anomaly with Machine Learning Based Model for Detecting HTTP DDoS Attack;2024 International Conference on Green Energy, Computing and Sustainable Technology (GECOST);2024-01-17

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