Discovery of Web Robot Sessions Based on their Navigational Patterns
Data Mining and Knowledge Discovery
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
HoneySpam: honeypots fighting spam at the source
SRUTI'05 Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop
Securing web service by automatic robot detection
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
WCRE '08 Proceedings of the 2008 15th Working Conference on Reverse Engineering
Recognizing objects in adversarial clutter: breaking a visual captcha
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Storage cost of spam 2.0 in a web discussion forum
Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference
Behaviour-Based web spambot detection by utilising action time and action frequency
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
Factors involved in estimating cost of email spam
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
Proceedings of the CUBE International Information Technology Conference
How much money do spammers make from your website?
Proceedings of the CUBE International Information Technology Conference
Detection of fixed length web spambot using REAL (read aligner)
Proceedings of the CUBE International Information Technology Conference
The changing nature of Spam 2.0
Proceedings of the CUBE International Information Technology Conference
Improving network security and design using honeypots
Proceedings of the CUBE International Information Technology Conference
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Internet bots have been widely used for various beneficial and malicious activities on the web. In this paper we provide new insights into a new kind of bot termed as web spambot which is primarily used for spreading spam content on the web. To gain insights into web spambots, we developed a tool (HoneySpam 2.0) to track their behaviour. This paper presents two main contributions, firstly it describes the design of HoneySpam 2.0 and secondly we outline the experimental results that characterise web spambot behaviour. By profiling web spambots, we provide the foundation for identifying such bots and preventing and filtering web spam content.