Show Me the Money: Characterizing Spam-advertised Revenue

Authors: 

Chris Kanich, University of California, San Diego; Nicholas Weaver, International Computer Science Institute; Damon McCoy and Tristan Halvorson, University of California, San Diego; Christian Kreibich, International Computer Science Institute; Kirill Levchenko, University of California, San Diego; Vern Paxson, International Computer Science Institute and University of California, Berkeley; Geoffrey M. Voelker and Stefan Savage, University of California, San Diego

Abstract: 

Modern spam is ultimately driven by product sales: goods purchased by customers online. However, while this model is easy to state in the abstract, our understanding of the concrete business environment—how many orders, of what kind, from which customers, for how much—is poor at best. This situation is unsurprising since such sellers typically operate under questionable legal footing, with “ground truth” data rarely available to the public. However, absent quantifiable empirical data, “guesstimates” operate unchecked and can distort both policy making and our choice of appropriate interventions. In this paper, we describe two inference techniques for peering inside the business operations of spam-advertised enterprises: purchase pair and basket inference. Using these, we provide informed estimates on order volumes, product sales distribution, customer makeup and total revenues for a range of spam-advertised programs.

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BibTeX
@inproceedings {266525,
author = {Chris Kanich and Nicholas Weaver and Damon McCoy and Tristan Halvorson and Christian Kreibich and Kirill Levchenko and Vern Paxson and Geoffrey M. Voelker and Stefan Savage},
title = {Show Me the Money: Characterizing Spam-advertised Revenue},
booktitle = {20th USENIX Security Symposium (USENIX Security 11)},
year = {2011},
address = {San Francisco, CA},
url = {https://www.usenix.org/conference/usenix-security-11/show-me-money-characterizing-spam-advertised-revenue},
publisher = {USENIX Association},
month = aug
}

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