Tracking Your Browser with High-Performance Browser Fingerprint Recognition Model  

作　　者：Wei Jiang Xiaoxi Wang Xinfang Song Qixu Liu Xiaofeng Liu 

机构地区：[1]Chinese Academy of Cyberspace Studies,Beijing 100010,China [2]College of Computer Science,Beijing University of Technology,Beijing100124,China [3]Beijing Information Technology College,Beijing100015,China [4]Institute of Information Engineering,Chinese Academy of Sciences,Beijing100093,China [5]University of Chinese Academy of Sciences,Beijing100049,China

出　　处：《China Communications》2020年第3期168-175,共8页中国通信（英文版）

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;General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No. km201410005012;Open Research Fund of Beijing Key Laboratory of Trusted Computing;Open Research Fund of Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education..

摘　　要：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.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.

关 键 词：BROWSER FINGERPRINT AHP FINGERPRINT TRACKING algorithm 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术] TP393.08[自动化与计算机技术—计算机科学与技术]