Open Access
Rule-Based On-the-fly Web Spambot Detection Using Action Strings
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TLDR
In this article, a rule-based web usage behavior action string that can be analyzed using Trie data structures to detect web spambots is proposed to eliminate spam in web 2.0 applications.Abstract:
spambots are a new type of internet robot that spread spam content through Web 2.0 applications like online discussion boards, blogs, wikis, social networking platforms etc. These robots are intelligently designed to act like humans in order to fool safeguards and other users. Such spam content not only wastes valuable resources and time but also may mislead users with unsolicited content. Spam content typically intends to misinform users (scams), generate traffic, make sales (marketing/advertising), and occasionally compromise parties, people or systems by spreading spyware or malwares. Current countermeasures do not effectively identify and prevent web spambots. Proactive measures to deter spambots from entering a site are limited to question / response scenarios. The remaining efforts then focus on spam content identification as a passive activity. Spammers have evolved their techniques to bypass existing anti-spam filters. In this paper, we describe a rule-based web usage behaviour action string that can be analysed using Trie data structures to detect web spambots. Our experimental results show the proposed system is successful for on-the-fly classification of web spambots hence eliminating spam in web 2.0 applications.read more
Citations
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Journal ArticleDOI
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Overview of Web Spammer Detection
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Dissertation
Personal Email Spam Filtering with Minimal User Interaction
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References
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Proceedings ArticleDOI
Identifying web spam with user behavior analysis
TL;DR: A novel spam detection framework is proposed that can detect unknown spam types and newly-appeared spam with the help of user behavior analysis and preliminary experiments show the effectiveness of the proposed features and detection framework.
Proceedings Article
Is Britney Spears Spam
Aaron Zinman,Judith Donath +1 more
TL;DR: The aim is to redefine spam and the role of the spam filter in the context of Social Networking Services (SNS) and develop a research prototype that categorizes senders into broader categories than spam/not spam using features unique to SNS.
Proceedings ArticleDOI
Toward spam 2.0: An evaluation of Web 2.0 anti-spam methods
Pedram Hayati,Vidyasagar Potdar +1 more
TL;DR: Analysis of current anti-spam methods in Web 2.0 for spam detection and prevention against the proposed evaluation framework shows that the need for more robust methods which are prevention based, unsupervised and do not increase user and system interaction complexity is highly demanded.
Book ChapterDOI
HoneySpam 2.0: Profiling Web Spambot Behaviour
TL;DR: By profiling web spambots, this paper provides the foundation for identifying such bots and preventing and filtering web spam content and describes the design of HoneySpam 2.0.
Book ChapterDOI
Web Spam Identification with User Browsing Graph
TL;DR: A user browsing graph is constructed based on users' Web access log and link analysis algorithms on this graph are adopted to identify Web spam pages and shows that algorithms performed on the constructed graph outperforms those on the original graph.