Spamalytics: An Empirical Analysis of Spam Marketing Conversion

Spamalytics: An Empirical Analysis of Spam Marketing Conversion (2008)

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by Chris Kanich , Christian Kreibich , Kirill Levchenko , Brandon Enright , Geoffrey M. Voelker , Vern Paxson , Stefan Savage

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Datum	Value	Source
TITLE	Spamalytics: An Empirical Analysis of Spam Marketing Conversion	user correction
AUTHOR NAME	Chris Kanich	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
AUTHOR NAME	Christian Kreibich	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
AUTHOR NAME	Kirill Levchenko	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
AUTHOR NAME	Brandon Enright	user correction
AUTHOR NAME	Geoffrey M. Voelker	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
AUTHOR NAME	Vern Paxson	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
AUTHOR NAME	Stefan Savage	user correction
AUTHOR AFFIL	International Computer Science Institute; Dept. of Computer Science and Engineering; Berkeley, USA University of California, San Diego	user correction
AUTHOR ADDR	USA	user correction
ABSTRACT	The “conversion rate” of spam — the probability that an unsolicited e-mail will ultimately elicit a “sale ” — underlies the entire spam value proposition. However, our understanding of this critical behavior is quite limited, and the literature lacks any quantitative study concerning its true value. In this paper we present a methodology for measuring the conversion rate of spam. Using a parasitic infiltration of an existing botnet’s infrastructure, we analyze two spam campaigns: one designed to propagate a malware Trojan, the other marketing on-line pharmaceuticals. For nearly a half billion spam e-mails we identify the number that are successfully delivered, the number that pass through popular anti-spam filters, the number that elicit user visits to the advertised sites, and the number of “sales” and “infections” produced.	user correction
YEAR	2008	user correction
CITATIONS	22 found	ParsCit 1.0