Research on Website Attack Behavior Detection Technology Based on Machine Learning Models

The behavior of network attacks is becoming increasingly serious, and website attack behavior detection is of great significance for protecting the network from malicious attacks. This article uses machine learning models to create a traffic detection module that intercepts illegal traffic requests such as SQL injection and cross site scripting attacks, improving network security and ensuring the stable operation of information systems.

Authors

Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/dsins64146.2024.10992211
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
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article

Research on Website Attack Behavior Detection Technology Based on Machine Learning Models

Xinjia Ou, Jie Tian
Network Security and Intrusion Detection
article

Research on Website Attack Behavior Detection Technology Based on Machine Learning Models

Xinjia Ou, Jie Tian
article en

Abstract

The behavior of network attacks is becoming increasingly serious, and website attack behavior detection is of great significance for protecting the network from malicious attacks. This article uses machine learning models to create a traffic detection module that intercepts illegal traffic requests such as SQL injection and cross site scripting attacks, improving network security and ensuring the stable operation of information systems.

Openalex Percentile: Top 64%
Network Security and Intrusion Detection
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Research on Website Attack Behavior Detection Technology Based on Machine Learning Models — Xinjia Ou, Jie Tian · (2024) | TGRS Research Map | TGRS