How much money do spammers make from your website?

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%.

[1]  Nazanin Firoozeh,et al.  Definition of spam 2.0: New spamming boom , 2010, 4th IEEE International Conference on Digital Ecosystems and Technologies.

[2]  John Langford,et al.  CAPTCHA: Using Hard AI Problems for Security , 2003, EUROCRYPT.

[3]  Calton Pu,et al.  Study of Trend-Stuffing on Twitter through Text Classification , 2010 .

[4]  Alex Talevski,et al.  HoneySpam 2.0: Profiling Web Spambot Behaviour , 2009, PRIMA.

[5]  Steven Myers,et al.  The Nuts and Bolts of a Forum Spam Automator , 2011, LEET.

[6]  Vidyasagar Potdar,et al.  Toward spam 2.0: An evaluation of Web 2.0 anti-spam methods , 2009, 2009 7th IEEE International Conference on Industrial Informatics.

[7]  Vipin Kumar,et al.  Discovery of Web Robot Sessions Based on their Navigational Patterns , 2004, Data Mining and Knowledge Discovery.

[8]  Timothy W. Finin,et al.  Towards Spam Detection at Ping Servers , 2007, ICWSM.

[9]  Hiroki Arimura,et al.  Unsupervised spam detection by document complexity estimation , 2008 .

[10]  Chris Kanich,et al.  Spamalytics: an empirical analysis of spam marketing conversion , 2008, CCS.

[11]  Alex Talevski,et al.  Behaviour-Based Web Spambot Detection by Utilising Action Time and Action Frequency , 2010, ICCSA.

[12]  Kang-Won Lee,et al.  Securing Web Service by Automatic Robot Detection , 2006, USENIX Annual Technical Conference, General Track.

[13]  Farida Ridzuan,et al.  Storage cost of spam 2.0 in a web discussion forum , 2011, CEAS '11.

[14]  Virgílio A. F. Almeida,et al.  Detecting Spammers on Twitter , 2010 .

[15]  Farida Ridzuan,et al.  Key Parameters in Identifying Cost of Spam 2.0 , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[16]  Paul Judge,et al.  Understanding and Reversing the Profit Model of Spam , 2005, WEIS.

[17]  Jun Hu,et al.  Detecting and characterizing social spam campaigns , 2010, CCS '10.

[18]  Alex Hai Wang,et al.  Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach , 2010, DBSec.