Title
Classification of web robots: An empirical study based on over one billion requests
Abstract
Many studies on detection and classification of web robots have focused their attention mostly on text crawlers, and empirical experiments used relatively small data collected at universities. In this paper, we analyzed more than one billion requests to www.microsoft.com in 24h. Web logs were made anonymous to eliminate potential privacy concerns while preserving essential characteristics (e.g., frequency, queries, etc). We have developed an effective characterization metrics, based on workload characteristics and resource types, in detecting and classifying various web robots including text crawlers, link checkers, and icon crawlers. As expected, web robot behavior was clearly different from that of typical interactive users, and different types of web robots also exhibited different characteristics. However, comparison of the similar type of web robots, text crawlers in particular, revealed different characteristics, thereby enabling characterization with reasonably high confidence level. We divided various feature metrics into five groups, and effectiveness of each group in classification is shown in polar diagram in the decreasing order of effectiveness in the clockwise direction. One can use the findings to classify likely identify of unknown web robots, and organizations can develop appropriate measures to deal with them. Our analysis is based on recent web log data collected at one of the best known site which offers truly global service.
Year
DOI
Venue
2009
10.1016/j.cose.2009.05.004
Computers and Security
Keywords
Field
DocType
web robot classification,web robot detection,web usage mining,web robot characterization,web security,confidence level,data collection,empirical study
Web design,Web mining,Computer science,Computer security,Web standards,Robots exclusion standard,Data Web,Web modeling,Web navigation,Web service
Journal
Volume
Issue
ISSN
28
8
Computers & Security
Citations 
PageRank 
References 
16
0.84
5
Authors
4
Name
Order
Citations
PageRank
Junsup Lee1181.62
Sungdeok Cha222019.73
Dongkun Lee3160.84
Hyungkyu Lee4295.60