A Technical Survey of Network Intrusion Detection Based on Deep Learning

Ruibo Shi

doi:10.47297/taposatWSP2633-456923.20260702

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A Technical Survey of Network Intrusion Detection Based on Deep Learning

Volume 7, Issue 2

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A Technical Survey of Network Intrusion Detection Based on Deep Learning
A Technical Survey of Network Intrusion Detection Based on Deep Learning
College of Computer Science and Mathematics, Anyang University, Xinxiang, Henan, 453500, China
Vol. 7, Issue 2, Pages: 116-121(2026)
Published：28 February 2026
DOI：10.47297/taposatWSP2633-456923.20260702
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Shi Ruibo.A Technical Survey of Network Intrusion Detection Based on Deep Learning[J].Theory and Practice of Science and Technology,2026,07(02):116-121.
DOI：

Shi Ruibo.A Technical Survey of Network Intrusion Detection Based on Deep Learning[J].Theory and Practice of Science and Technology,2026,07(02):116-121. DOI： 10.47297/taposatWSP2633-456923.20260702.

摘要

Abstract

Traditional Intrusion Detection Systems (IDS) exhibit notable limitations in addressing complex network attacks

failing to meet the requirements of practical intrusion detection scenarios.Leveraging its robust feature learning capability

deep learning offers an effective solution to overcome the shortcomings of traditional IDS and enhance the performance of network intrusion detection.This paper systematically reviews deep learning-based network intrusion detection technologies

summarizes mainstream models

various learning paradigms

and key challenges in practical deployment

proposes future research directions based on the limitations of existing studies

and provides insights for the development of efficient and deployable intelligent intrusion detection systems.

关键词

Keywords

references

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