东南大学学报（自然科学版）2026，Vol.56Issue(3)：461-468,8.DOI:10.3969/j.issn.1001-0505.2026.03.015
基于约束集的半监督未知协议识别方法
A semi-supervised method for unknown protocol identification based on constraint sets
摘要
Abstract
Due to the absence of explicit prior features in unknown protocols and the scarcity of labeled samples,traditional identification approaches—such as port-based methods and deep packet inspection—as well as supervised learning techniques that rely heavily on large labeled datasets,become ineffective for traffic classification.To overcome these limitations,this paper proposes a semi-supervised unknown proto-col identification method based on constraint sets.The approach constructs multidimensional features by combining statistical features with protocol fingerprint features and applies constrained Laplace scores for feature selection.In addition,constraint information is derived from the correlation between labeled samples and real network traffic,and then incorporated into the K-means clustering process to enhance the recognition accuracy and efficiency.Experimental results demonstrate that this method significantly im-proves clustering performance compared with traditional clustering algorithms;in scenarios with multiple unknown protocols,the recognition accuracy exceeds 97%,providing a new solution for unknown protocol identification.关键词
未知协议识别/半监督聚类/特征融合/约束拉普拉斯分数Key words
unknown protocol identification/semi-supervised clustering/feature fusion/constrained Laplace score分类
信息技术与安全科学引用本文复制引用
程光,张高琦,尚庆华..基于约束集的半监督未知协议识别方法[J].东南大学学报（自然科学版）,2026,56(3):461-468,8.基金项目
国家自然科学基金联合基金资助项目(U22B2025) （U22B2025）
国家自然科学基金面上资助项目(62172093) （62172093）
未知协议流量分析与识别技术研究资助项目. （）
