A Comparative Analysis of Support Vector Machine and K-Nearest Neighbors Models for Network Attack Traffic Detection
With the continuous advancement of Internet technology, cybersecurity threats are growing more urgent as attack techniques become increasingly sophisticated. Conventional intrusion detection systems struggle to address these emerging threats because they depend heavily on predefined signatures and r...
Saved in:
Main Author: | Han Zhuoxi |
---|---|
Format: | Article |
Language: | English |
Published: |
EDP Sciences
2025-01-01
|
Series: | ITM Web of Conferences |
Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01018.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Performance analysis of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries
by: Zhenlong Li, et al.
Published: (2017-09-01) -
Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and k-Nearest Neighbor
by: Junfeng Yang, et al.
Published: (2020-01-01) -
Consistency of the $k$-nearest neighbors rule for functional data
by: Younso, Ahmad
Published: (2023-01-01) -
Radar Target Detection with K-Nearest Neighbor Manifold Filter on Riemannian Manifold
by: Dongao Zhou, et al.
Published: (2024-01-01) -
An Orthogonal Wavelet Transform-Based K-Nearest Neighbor Algorithm to Detect Faults in Bearings
by: Weipeng Li, et al.
Published: (2022-01-01)