基于ARF的Tor网站指纹识别技术

不法分子通过Tor等匿名通信系统构建暗网隐匿其不法行为,给网络监管带来了严峻挑战.网站指纹识别技术能根据加密流量来推测用户访问的站点,是一种有效的监管手段.已有的网站指纹识别技术采用的多为基于批处理的静态模型,无法有效解决概念漂移问题.针对Tor网站指纹,文章提出一种基于自适应随机森林(ARF)算法的动态网站指纹识别模...

ARF-based Tor Website Fingerprint Recognition Technology

Criminals use Tor and other anonymous communication systems to construct dark Webs to conceal their illegal activities,which brings severe challenges to network supervision.Website fingerprint recognition technology can infer the sites that users visit based on encrypted traffic,which is an effective monitoring method.Existing Website fingerprint recognition technologies mostly use batch-based static models,which cannot effectively solve the problem of concept drift.Aiming at Tor Website fingerprints,a dynamic Website fingerprint recognition model based on adaptive random forest algorithm is proposed.The model uses an adaptive random forest algorithm as the classifier,supports two input of manual features and automatic features,and can dynamically update the classifier model according to the feature stream to realize online classification and recognition of Website fingerprints.The experimental results show that the dynamic Website fingerprint recognition model based on ARF is better than the existing multiple Website fingerprint recognition methods,and can effectively solve the problem of concept drift in existing models.