As the cyber security has attracted great attention in recent years,and with all kinds of tools’(such as Network Agent,VPN and so on)help,traditional methods of tracking users like log analysis and cookie have been n...As the cyber security has attracted great attention in recent years,and with all kinds of tools’(such as Network Agent,VPN and so on)help,traditional methods of tracking users like log analysis and cookie have been not that effective.Especially for some privacy sensitive users who changed their browser configuration frequently to hide themselves.The Browser Fingerprinting technology proposed by Electronic Frontier Foundation(EFF)gives a new approach of tracking users,and then our team designed an enhanced fingerprint dealing solution based on browser fingerprinting technology.Our enhanced solution plays well in recognizing the similar fingerprints,but it is not that efficient.Nowadays we improve the algorithm and propose a high-performance,efficient Browser Fingerprint Recognition Model.Our new model reforms the fingerprint items set by EFF and propose a Fingerprint Tracking Algorithm(FTA)to deal with collected data.It can associate users with some browser configuration changes in different periods of time quickly and precisely.Through testing with the experimental website built on the public network,we prove the high-performance and efficiency of our algorithm with a 20%time-consuming decrease than ever.展开更多
当前Web追踪领域主要使用浏览器指纹对用户进行追踪。针对浏览器指纹追踪技术存在指纹随时间动态变化、不易长期追踪等问题,提出一种关注节点和边缘特征的改进图采样聚合算法(An Improved Graph SAmple and AGgregatE with Both Node an...当前Web追踪领域主要使用浏览器指纹对用户进行追踪。针对浏览器指纹追踪技术存在指纹随时间动态变化、不易长期追踪等问题,提出一种关注节点和边缘特征的改进图采样聚合算法(An Improved Graph SAmple and AGgregatE with Both Node and Edge Features,NE-GraphSAGE)用于浏览器指纹追踪。首先以浏览器指纹为节点、指纹之间特征相似度为边构建图数据。其次对图神经网络中的GraphSAGE算法进行改进使其不仅能关注节点特征,而且能捕获边缘信息并对边缘分类,从而识别指纹。最后将NE-GraphSAGE算法与Eckersley算法、FPStalker算法和LSTM算法进行对比,验证NE-GraphSAGE算法的识别效果。实验结果表明,NE-GraphSAGE算法在准确率和追踪时长上均有不同程度的提升,最大追踪时长可达80天,相比其他3种算法性能更优,验证了NE-GraphSAGE算法对浏览器指纹长期追踪的能力。展开更多
计算机网络实验是计算机课程教学的必要环节,文章介绍了一种新型在线计算机网络仿真实验系统。该系统具有开源、免安装和易使用的特点,由基于超文本标记语言5(Hyper Text Markup Language 5,HTML5)、Javascript和层叠样式表(Cascading S...计算机网络实验是计算机课程教学的必要环节,文章介绍了一种新型在线计算机网络仿真实验系统。该系统具有开源、免安装和易使用的特点,由基于超文本标记语言5(Hyper Text Markup Language 5,HTML5)、Javascript和层叠样式表(Cascading Style Sheets,CSS)的网页Widget技术实现。用户可以在安装有浏览器的任意设备和操作系统上拖动计算机网络设备Widget组件搭建网络拓扑图,并按照从数据链路层到应用层的相关协议实时仿真。为方便教师远程考查和重现学生实验情况,本系统利用基于浏览器指纹特征的Fingerprint技术识别用户,减少了会话层对内存的消耗,使系统对计算机硬件的要求较低,具有较高的可移植性。展开更多
基金supported by the Beijing Municipal Natural Science Foundation(No.4172006)Humanity and Social Science Youth foundation of Ministry of Education of China under Grant No. 13YJCZH065+2 种基金General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No. km201410005012Open Research Fund of Beijing Key Laboratory of Trusted ComputingOpen Research Fund of Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education..
文摘As the cyber security has attracted great attention in recent years,and with all kinds of tools’(such as Network Agent,VPN and so on)help,traditional methods of tracking users like log analysis and cookie have been not that effective.Especially for some privacy sensitive users who changed their browser configuration frequently to hide themselves.The Browser Fingerprinting technology proposed by Electronic Frontier Foundation(EFF)gives a new approach of tracking users,and then our team designed an enhanced fingerprint dealing solution based on browser fingerprinting technology.Our enhanced solution plays well in recognizing the similar fingerprints,but it is not that efficient.Nowadays we improve the algorithm and propose a high-performance,efficient Browser Fingerprint Recognition Model.Our new model reforms the fingerprint items set by EFF and propose a Fingerprint Tracking Algorithm(FTA)to deal with collected data.It can associate users with some browser configuration changes in different periods of time quickly and precisely.Through testing with the experimental website built on the public network,we prove the high-performance and efficiency of our algorithm with a 20%time-consuming decrease than ever.
文摘当前Web追踪领域主要使用浏览器指纹对用户进行追踪。针对浏览器指纹追踪技术存在指纹随时间动态变化、不易长期追踪等问题,提出一种关注节点和边缘特征的改进图采样聚合算法(An Improved Graph SAmple and AGgregatE with Both Node and Edge Features,NE-GraphSAGE)用于浏览器指纹追踪。首先以浏览器指纹为节点、指纹之间特征相似度为边构建图数据。其次对图神经网络中的GraphSAGE算法进行改进使其不仅能关注节点特征,而且能捕获边缘信息并对边缘分类,从而识别指纹。最后将NE-GraphSAGE算法与Eckersley算法、FPStalker算法和LSTM算法进行对比,验证NE-GraphSAGE算法的识别效果。实验结果表明,NE-GraphSAGE算法在准确率和追踪时长上均有不同程度的提升,最大追踪时长可达80天,相比其他3种算法性能更优,验证了NE-GraphSAGE算法对浏览器指纹长期追踪的能力。
文摘计算机网络实验是计算机课程教学的必要环节,文章介绍了一种新型在线计算机网络仿真实验系统。该系统具有开源、免安装和易使用的特点,由基于超文本标记语言5(Hyper Text Markup Language 5,HTML5)、Javascript和层叠样式表(Cascading Style Sheets,CSS)的网页Widget技术实现。用户可以在安装有浏览器的任意设备和操作系统上拖动计算机网络设备Widget组件搭建网络拓扑图,并按照从数据链路层到应用层的相关协议实时仿真。为方便教师远程考查和重现学生实验情况,本系统利用基于浏览器指纹特征的Fingerprint技术识别用户,减少了会话层对内存的消耗,使系统对计算机硬件的要求较低,具有较高的可移植性。
