Title
Extracting user web browsing patterns from non-content network traces: The online advertising case study
Abstract
Online advertising is a rapidly growing industry currently dominated by the search engine 'giant'Google. In an attempt to tap into this huge market, Internet Service Providers (ISPs) started deploying deep packet inspection techniques to track and collect user browsing behavior. However, these providers have the fear that such techniques violate wiretap laws that explicitly prevent intercepting the contents of communication without gaining consent from consumers. In this paper, we explore how it is possible for ISPs to extract user browsing patterns without inspecting contents of communication. Our contributions are threefold. First, we develop a methodology and implement a system that is capable of extracting web browsing features from stored non-content based network traces, which could be legally shared. When such browsing features are correlated with information collected by independently crawling the Web, it becomes possible to recover the actual web pages accessed by clients. Second, we evaluate our system on the Internet and check that it can successfully recover user browsing patterns with high accuracy.
Year
DOI
Venue
2012
10.1016/j.comnet.2011.10.012
Computer Networks
Keywords
DocType
Volume
Online advertising,Web navigation,Web fingerprinting
Journal
56
Issue
ISSN
Citations 
2
1389-1286
1
PageRank 
References 
Authors
0.35
16
4
Name
Order
Citations
PageRank
Gabriel Maciá-Fernández161633.77
Yong Wang2208.62
Rafael A. Rodríguez-Gómez3563.15
Aleksandar Kuzmanovic496071.99