NDLI: Web Spambot Detection Based on Web Navigation Behaviour

Content Provider	IEEE Xplore Digital Library
Author	Hayati, P. Potdar, V. Chai, K. Talevski, A.
Copyright Year	2010
Abstract	Web robots have been widely used for various beneficial and malicious activities. Web spambots are a type of web robot that spreads spam content throughout the web by typically targeting Web 2.0 applications. They are intelligently designed to replicate human behaviour in order to bypass system checks. Spam content not only wastes valuable resources but can also mislead users to unsolicited websites and award undeserved search engine rankings to spammers’ campaign websites. While most of the research in anti-spam filtering focuses on the identification of spam content on the web, only a few have investigated the origin of spam content, hence identification and detection of web spambots still remains an open area of research. In this paper, we describe an automated supervised machine learning solution which utilises web navigation behaviour to detect web spambots. We propose a new feature set (referred to as an action set) as a representation of user behaviour to differentiate web spambots from human users. Our experimental results show that our solution achieves a 96.24% accuracy in classifying web spambots.
Starting Page	797
Ending Page	803
File Size	442183
Page Count	7
File Format	PDF
ISBN	9781424466955
ISSN	1550445X
e-ISBN	9781424466962
DOI	10.1109/AINA.2010.92
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-20
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Navigation Unsolicited electronic mail Intelligent robots Humans Support vector machines Support vector machine classification Ecosystems Intelligent networks Search engines Information filtering user behaviour Web spambot detection Web 2.0 spam spam 2.0
Content Type	Text
Resource Type	Article

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