Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency

Web spam is an escalating problem that wastes valuable resources, misleads people and can manipulate search engines in achieving undeserved search rankings to promote spam content. Spammers have extensively used Web robots to distribute spam content within Web 2.0 platforms. We referred to these web...

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Bibliographic Details
Main Authors: Hayati, Pedram, Chai, Kevin, Potdar, Vidyasagar, Talevski, Alex
Other Authors: David Taniar
Format: Book Chapter
Published: Springer 2010
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/47466
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author Hayati, Pedram
Chai, Kevin
Potdar, Vidyasagar
Talevski, Alex
author2 David Taniar
author_facet David Taniar
Hayati, Pedram
Chai, Kevin
Potdar, Vidyasagar
Talevski, Alex
author_sort Hayati, Pedram
building Curtin Institutional Repository
collection Online Access
description Web spam is an escalating problem that wastes valuable resources, misleads people and can manipulate search engines in achieving undeserved search rankings to promote spam content. Spammers have extensively used Web robots to distribute spam content within Web 2.0 platforms. We referred to these web robots as spambots that are capable of performing human tasks such as registering user accounts as well as browsing and posting content. Conventional content-based and link-based techniques are not effective in detecting and preventing web spambots as their focus is on spam content identification rather than spambot detection. We extend our previous research by proposing two action-based features sets known as action time and action frequency for spambot detection. We evaluate our new framework against a real dataset containing spambots and human users and achieve an average classification accuracy of 94.70%.
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institution Curtin University Malaysia
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publishDate 2010
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spelling curtin-20.500.11937-474662023-01-18T08:46:45Z Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency Hayati, Pedram Chai, Kevin Potdar, Vidyasagar Talevski, Alex David Taniar Osvaldo Gervasi Beniamino Murgante Eric Pardede Bernady O Apduhan spam 2.0 user behaviour Web 2.0 spam Web spambot detection Web spam is an escalating problem that wastes valuable resources, misleads people and can manipulate search engines in achieving undeserved search rankings to promote spam content. Spammers have extensively used Web robots to distribute spam content within Web 2.0 platforms. We referred to these web robots as spambots that are capable of performing human tasks such as registering user accounts as well as browsing and posting content. Conventional content-based and link-based techniques are not effective in detecting and preventing web spambots as their focus is on spam content identification rather than spambot detection. We extend our previous research by proposing two action-based features sets known as action time and action frequency for spambot detection. We evaluate our new framework against a real dataset containing spambots and human users and achieve an average classification accuracy of 94.70%. 2010 Book Chapter http://hdl.handle.net/20.500.11937/47466 Springer restricted
spellingShingle spam 2.0
user behaviour
Web 2.0 spam
Web spambot detection
Hayati, Pedram
Chai, Kevin
Potdar, Vidyasagar
Talevski, Alex
Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title_full Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title_fullStr Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title_full_unstemmed Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title_short Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency
title_sort behaviour-based web spambot detection by utilising action time and action frequency
topic spam 2.0
user behaviour
Web 2.0 spam
Web spambot detection
url http://hdl.handle.net/20.500.11937/47466