信息工程大学学报2025，Vol.26Issue(5)：520-527,8.DOI:10.3969/j.issn.1671-0673.2025.05.003
基于ViT-KANs的双头通信网络协议数据类别概念漂移检测分类算法
A ViT-KANs-Based Dual-Head Algorithm for Communication Network Protocol Data Category Concept Drift Detection and Classification
王润泽 1张效义 1李青 1任俊康 1陈奕凡1
作者信息
摘要
Abstract
To address the issue of category concept drift in network protocol data,a ViT-KANs-based dual-head algorithm for communication network protocol data category concept drift detection and clas-sification is proposed.The global perception capability of vision transformer(ViT)and the flexible function approximation ability of kolmogorov-arnold networks(KANs)are integrated to construct an ef-ficient feature extraction network in this algorithm.A dual-head parallel output structure is adopted to handle the classification of old-class data and the detection of category concept drift,respectively.Fur-thermore,the validation set data is utilized to adaptively compute the confidence threshold,which ef-fectively alleviates the lack of concept drift samples during the training phase.Experiments are con-ducted on three datasets,namely the Moore dataset,the Canadian Institute for Cybersecurity Intrusion Detection Evaluation Dataset 2017(CICIDS2017),and the improved version of the Network Security Lab(NSL)-Knowledge Discovery and Data Mining Competition Dataset(NSL-KDD).The results show that the detection error rate of the proposed method is reduced significantly,compared to those of mod-els and out-of-distribution detection methods,while superior classification accuracy category is maintained.关键词
类别概念漂移/ViT-KANs模型/双头网络/置信度阈值/网络协议数据Key words
category concept drift/ViT-KANs/dual-head network/confidence threshold/network protocol data分类
电子信息工程引用本文复制引用
王润泽,张效义,李青,任俊康,陈奕凡..基于ViT-KANs的双头通信网络协议数据类别概念漂移检测分类算法[J].信息工程大学学报,2025,26(5):520-527,8.
