Web Spambot Detection Based on Web Navigation Behaviour
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 chec...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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IEEE Computer Society
2010
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/11577 |
| _version_ | 1848747843287777280 |
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| author | Hayati, Pedram Potdar, Vidyasagar Chai, Kevin Talevski, Alex |
| author2 | Wenny Rahayu |
| author_facet | Wenny Rahayu Hayati, Pedram Potdar, Vidyasagar Chai, Kevin Talevski, Alex |
| author_sort | Hayati, Pedram |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T06:55:35Z |
| format | Conference Paper |
| id | curtin-20.500.11937-11577 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:55:35Z |
| publishDate | 2010 |
| publisher | IEEE Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-115772022-12-09T07:12:37Z Web Spambot Detection Based on Web Navigation Behaviour Hayati, Pedram Potdar, Vidyasagar Chai, Kevin Talevski, Alex Wenny Rahayu Fatos Xhafa Mieso Denko spam 2.0 user behaviour Web 2.0 spam Web spambot detection 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. 2010 Conference Paper http://hdl.handle.net/20.500.11937/11577 10.1109/AINA.2010.92 IEEE Computer Society fulltext |
| spellingShingle | spam 2.0 user behaviour Web 2.0 spam Web spambot detection Hayati, Pedram Potdar, Vidyasagar Chai, Kevin Talevski, Alex Web Spambot Detection Based on Web Navigation Behaviour |
| title | Web Spambot Detection Based on Web Navigation Behaviour |
| title_full | Web Spambot Detection Based on Web Navigation Behaviour |
| title_fullStr | Web Spambot Detection Based on Web Navigation Behaviour |
| title_full_unstemmed | Web Spambot Detection Based on Web Navigation Behaviour |
| title_short | Web Spambot Detection Based on Web Navigation Behaviour |
| title_sort | web spambot detection based on web navigation behaviour |
| topic | spam 2.0 user behaviour Web 2.0 spam Web spambot detection |
| url | http://hdl.handle.net/20.500.11937/11577 |