信息安全研究2025，Vol.11Issue(5)：439-446,8.DOI:10.12379/j.issn.2096-1057.2025.05.06
主动Tor网站指纹识别
Active Tor Website Fingerprint Recognition
摘要
Abstract
The anonymous communication system Tor is often exploited by criminals,disrupting the network environment and social stability.Website fingerprinting can effectively monitor Tor activities.However,user behavior and website content on Tor change over time,leading to the problem of concept drift,which degrades model performance.Additionally,existing models suffer from large parameter sizes and low efficiency.To address these issues,a Tor website fingerprinting model based on active learning,named Tor AL,is proposed.This method utilizes the image classification model ShuffleNetV2 for feature extraction and classification,and improves its downsampling module with Haar wavelet transform to losslessly reduce image resolution.The model's recognition accuracy surpasses that of existing models.Moreover,by combining active learning,the model is trained with a small amount of highly contributive data,effectively addressing the concept drift problem.关键词
洋葱路由/网站指纹识别/暗网/卷积神经网络/主动学习Key words
Tor(the onion router)/website fingerprint recognition/darknet/convolutional neural network/active learning分类
计算机与自动化引用本文复制引用
朱懿,蔡满春,姚利峰,陈咏豪,张溢文..主动Tor网站指纹识别[J].信息安全研究,2025,11(5):439-446,8.基金项目
中国人民公安大学2022年基本科研业务费课题(2022JKF02009) （2022JKF02009）
中国人民公安大学网络空间安全执法技术双一流创新研究专项(2023SYL07) （2023SYL07）
高等学校学科创新引智基地资助项目(B20087) （B20087）
