Network Intrusion Detection via Flow-to-Image Conversion and Vision Transformer Classification
Author:
Affiliation:
1. Faculty of Engineering and Applied Sciences, University of Regina, Regina, Canada
2. Global AI Accelerator (GAIA) Team, Ericsson Canada Inc., Saint-Laurent, Canada
3. Global AI Accelerator (GAIA) Team, Ericsson Inc., Santa Clara, CA, USA
Funder
Ericsson—Global Artificial Intelligence Accelerator in Montreal through the Mitacs Accelerate Program
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/ielx7/6287639/9668973/09862964.pdf?arnumber=9862964
Reference40 articles.
1. Network Intrusion Detection Based on Extended RBF Neural Network With Offline Reinforcement Learning
2. Deep Belief Network Integrating Improved Kernel-Based Extreme Learning Machine for Network Intrusion Detection
3. An image is worth 16×16 words: Transformers for image recognition at scale;dosovitskiy;arXiv 2010 11929,2020
4. Attention is all you need;vaswani;Proc Adv Neural Inf Process Syst,2017
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