%0 Conference Proceedings
%T Web User Profiling Based on Browsing Behavior Analysis
%+ The University of Hong Kong (HKU)
%+ Chinese Academy of Sciences [Beijing] (CAS)
%A Fan, Xiao-Xi
%A Chow, Kam-Pui
%A Xu, Fei
%Z Part 1: Internet Crime Investigations
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 10th IFIP International Conference on Digital Forensics (DF)
%C Vienna, Austria
%Y Gilbert Peterson
%Y Sujeet Shenoi
%I Springer
%3 Advances in Digital Forensics X
%V AICT-433
%P 57-71
%8 2014-01-08
%D 2014
%R 10.1007/978-3-662-44952-3_5
%K Web user profiling
%K browsing behavior
%K term frequency
%Z Computer Science [cs]Conference papers
%X Determining the source of criminal activity requires a reliable means to estimate a criminal’s identity. One way to do this is to use web browsing history to build a profile of an anonymous user. Since an individual’s web use is unique, matching the web use profile to known samples provides a means to identify an unknown user. This paper describes a model for web user profiling and identification. Two aspects of browsing behavior are examined to construct a user profile, the user’s page view number and page view time for each domain. Four weighting models, based on the term frequency and term frequency – inverse document frequency weighting schemes, are proposed and compared. Experiments involving 51 personal computers demonstrate that the profiling model is very effective at identifying web users.
%G English
%Z TC 11
%Z WG 11.9
%2 https://inria.hal.science/hal-01393760/document
%2 https://inria.hal.science/hal-01393760/file/978-3-662-44952-3_5_Chapter.pdf
%L hal-01393760
%U https://inria.hal.science/hal-01393760
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-DF
%~ IFIP-WG11-9
%~ IFIP-AICT-433