Enhancing Detection of Malicious Traffic Through FPGA-Based Frequency Transformation and Machine Learning
Author:
Affiliation:
1. Graduate School of Informatics, Nagoya University, Nagoya, Japan
2. Center for Strategic Cyber Resilience Research and Development, National Institute of Informatics, Tokyo, Japan
3. Information Technology Center, Nagoya University, Nagoya, Japan
Funder
Nagoya University Interdisciplinary Frontier Fellowship
Nagoya University and Japan Science and Technology Agency
Japan Society for the Promotion of Science (JSPS) KAKENHI
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10376060.pdf?arnumber=10376060
Reference46 articles.
1. Decision-making and biases in cybersecurity capability development: Evidence from a simulation game experiment
2. A Framework for Malicious Traffic Detection in IoT Healthcare Environment
3. Chimera: A declarative language for streaming network traffic analysis;Borders
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