HoneySpam 2.0: Profiling Web Spambot Behaviour
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
Key Parameters in Identifying Cost of Spam 2.0
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
Web Spambot Detection Based on Web Navigation Behaviour
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
Clustering-based web page prediction
International Journal of Knowledge and Web Intelligence
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
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Spam 2.0 (or Web 2.0 Spam) is referred to as spam content that is hosted on Web 2.0 applications (blogs, forums, social networks etc.). Such spam differs from traditional spam as this is targeted at Web 2.0 applications and spreads through legitimate websites. The main problems with Spam 2.0 is spam websites get undeserved high ranking in search engines, damage the reputation of legitimate websites, wastes' valuable computing resources and deceives users resulting in proliferation of scam, fraud and other security attacks. Protecting the Internet against Spam 2.0 attacks is increasingly becoming important due to the potential threats it poses to the innocent web users. The paper contributes in this direction by attempting to understand the root cause of the problem, by investigating the changing nature of Spam 2.0. To understand this we setup an online discussion forum as a Honeypot to capture spam content. The collected data is analysed to identify trends within the spam corpus, which includes repetitiveness in the use of email addresses, patterns within email addresses, repetitiveness of forum posts, domains used for spamming, keywords and categories, origin of spam traffic. In the future we aim to use these trends in developing a preventive or early detection system that could predict future spam activities and would allow us to take pre-emptive actions to address them.