Denial-of Service (DoS) Attack Detection Using Edge Machine Learning


연구 분야: Artificial Intelligence



학회: 2023 International Conference on Machine Learning and Applications (ICMLA)


초록

Developing lightweight algorithms to implement DoS attack mitigation on edge devices is a growing interest in edge cybersecurity. Various types of micro-controller boards can be programmed to capture network traffic and implement lightweight machine learning models to analyze the supplied traffic data for signs of intrusion and attacks. This study experimented with building Support Vector Machine and Logistic Regression models on real-time DoS attack scenario data and the CICIoT2023 dataset. The main contribution of this study is to propose a framework for data capturing, processing, and analysis to produce edge machine learning models for DoS attack mitigation,


Author Profile
Ngoc Suong Huynh

Department of Computer Science Texas State University San Marcos USA

United States
Author Profile
Sebastian De La Cruz

Department of Electrical and Computer Engineering Florida International University Miami USA

Andorra
Author Profile
Alexander Perez-Pons

Department of Electrical and Computer Engineering Florida International University Miami USA

Andorra

📄 논문 정보

발행 연도 2023년
인용수 1
출판 국가 Andorra, United States
사이트 IEEE
좋아요 수 0

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