Discovery of Web Robot Sessions Based on their Navigational Patterns
Data Mining and Knowledge Discovery
Securing web service by automatic robot detection
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Spamalytics: an empirical analysis of spam marketing conversion
Proceedings of the 15th ACM conference on Computer and communications security
Unsupervised Spam Detection by Document Complexity Estimation
DS '08 Proceedings of the 11th International Conference on Discovery Science
HoneySpam 2.0: Profiling Web Spambot Behaviour
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
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
Detecting and characterizing social spam campaigns
Proceedings of the 17th ACM conference on Computer and communications security
Detecting spam bots in online social networking sites: a machine learning approach
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
The nuts and bolts of a forum spam automator
LEET'11 Proceedings of the 4th USENIX conference on Large-scale exploits and emergent threats
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
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Despite years of researcher's contribution in the domain of spam filtering, the question as to how much money spammers can make has largely remained unanswered. The value of spam-marketing on the web can be determined by discovering the cost of distributing spam in Web 2.0 platforms, and the success ratio of turning a spamming campaign into a profitable activity. Currently, there is limited knowledge on the nature of spam distribution in web applications, and public methods for estimating the turnover rate for spammers, in the existing literature. Therefore, we adopted a methodological approach to address these issues and measure the value of spam-marketing on the web. Using current spam tactics, we targeted 66,226 websites both in English and non-English languages. We launched a spam campaign and set up a website to replicate spam practices. We posted spam content to 7,772 websites that resulted in 2059 unique visits to our website, and 3 purchase transactions, in a period of a month. The total conversion visit rate for this experiment was 26.49% and purchase rate was 0.14%.