首页|融合Inception与SE-Attention的加密流量移动业务识别

融合Inception与SE-Attention的加密流量移动业务识别

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移动设备通常接入无线局域网,并依赖WiFi加密协议对网络中数据链路层流量进行加密,以维护通信安全.然而,现有加密流量识别方法主要针对网络层及以上的流量载荷进行分析,无法有效识别链路层加密流量的移动业务类别.针对该问题,提出了 一种在WiFi加密场景下基于链路层流量的移动业务识别方法.通过被动嗅探WiFi数据帧,提取链路层中可用的流量侧信道特征,将流量数据转换为二维直方图矩阵.融合Inception网络和SE-Attention机制,提出识别模型 SE-Incep-tion,旨在更好地捕捉到流量数据帧分布特征中的细节和全局信息,突出对重要特征的关注,以提高识别准确率.文中采用真实数据集进行实验验证,结果表明该方法在WiFi加密场景下可有效识别链路层加密流量的移动业务类别,平均准确率可达98.29%,相比于已有的识别方法具有更优的性能.
Identification of Mobile Service Type of Encrypted Traffic Based on Fusion of Inception and SE-Attention
Mobile devices usually access WLAN and rely on WiFi encryption protocol to encrypt data link layer traffic in the net-work to maintain communication security.However,existing encrypted traffic identification methods mainly analyze traffic loads at the network layer and above,and cannot effectively identify the mobile service category of link layer encrypted traffic.To ad-dress this problem,a mobile service identification method based on link layer traffic in WiFi encryption scenarios is proposed.By passively sniffing WiFi data frames and extracting the traffic-side channel features available in the link layer,the traffic data is converted into a 2D histogram matrix.The recognition model,SE-Inception,is proposed by integrating the Inception network and SE-Attention mechanism,aiming to better capture the details and global information in the distribution features of traffic data frames,and highlighting the attention to important features to improve the recognition accuracy.In this paper,real datasets are used for experimental validation,and the results show that the method can effectively recognize the mobile service category of link-layer encrypted traffic in WiFi encryption scenarios,with an average accuracy of up to 98.29%,which is a better performance compared with the existing recognition methods.

WLANLink-layer encrypted trafficTraffic identificationInceptionSE-attention

王依菁、王清贤、丁大钊、闫廷聚、曹琰

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郑州大学网络空间安全学院 郑州 450002

嵩山实验室 郑州 450000

无线局域网 链路层加密流量 流量识别 Inception SE注意力机制

国家自然科学基金河南省科技攻关项目河南省科技攻关项目嵩山实验室资助项目嵩山实验室预研项目

61871404232102210045232102210124232102210124YYYY032022005

2024

计算机科学
重庆西南信息有限公司(原科技部西南信息中心)

计算机科学

CSTPCD北大核心
影响因子:0.944
ISSN:1002-137X
年,卷(期):2024.51(10)