The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Spamalytics: an empirical analysis of spam marketing conversion
Abstract
The 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.
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Cites
Kademlia: A Peer-to-Peer Information System Based on the XOR Metric
Maymounkov, P., & Mazières, D. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-45748-8_5 · Cited by 3,004
Revealing botnet membership using DNSBL counter-intelligence
Ramachandran, A., Feamster, N., & Dagon, D. (2006) · Cited by 204
Spamscatter: characterizing internet scam hosting infrastructure
Anderson, D. S., Fleizach, C., Savage, S., & Voelker, G. M. (2007) · eScholarship (California Digital Library) · Cited by 179
Self-citationSpam Works: Evidence from Stock Touts and Corresponding Market ActivityPreprint
Frieder, L., & Zittrain, J. L. (2006) · SSRN Electronic Journal · doi:10.2139/ssrn.920553 · Cited by 107
Wang, Y., Ma, M., Niu, Y., & Chen, H. (2007) · International World Wide Web Conference (WWW) · doi:10.1145/1242572.1242612 · Cited by 89
On the effects of stock spam e-mails
Hanke, M., & Hauser, F. (2007) · Journal of Financial Markets · doi:10.1016/j.finmar.2007.10.001 · Cited by 77
Goodman, J., & Rounthwaite, R. (2004) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/988772.988779 · Cited by 68
Cited by
A survey of emerging threats in cybersecurity
Jang-Jaccard, J., & Nepal, S. (2014) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2014.02.005 · Cited by 892
A survey on automated dynamic malware-analysis techniques and tools
Egele, M., Scholte, T., Kirda, E., & Kruegel, C. (2012) · ACM Computing Surveys · doi:10.1145/2089125.2089126 · Cited by 871
A Survey on Malware Detection Using Data Mining Techniques
Ye, Y., Li, T., Adjeroh, D., & Iyengar, S. S. (2018) · ACM Computing Surveys · doi:10.1145/3073559 · Cited by 623
Your botnet is my botnet: analysis of a botnet takeover
Stone-Gross, B., Cova, M., Cavallaro, L., Gilbert, B., Szydlowski, M., Kemmerer, R., Kruegel, C., & Vigna, G. (2009) · Proceedings of the 16th ACM conference on Computer and communications security · doi:10.1145/1653662.1653738 · Cited by 577
@spam: the underground on 140 characters or less
Grier, C., Thomas, K., Paxson, V., & Zhang, M. (2010) · Proceedings of the 17th ACM conference on Computer and communications security · doi:10.1145/1866307.1866311 · Cited by 558
Self-citation
Metadata
- Authors
- Kanich, C., Kreibich, C., Levchenko, K., Enright, B., Voelker, G. M., Paxson, V., & Savage, S.
- Venue
- Proceedings of the 15th ACM conference on Computer and communications security
- Publisher
- ACM
- Published
- 2008-10-27
- Pages
- 3-14
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W2091692346
- Cited by
- 323
- References
- 7
- FWCI
- 28.85
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Kanich, C., Kreibich, C., Levchenko, K., Enright, B., Voelker, G. M., Paxson, V., & Savage, S. (2008). Spamalytics: an empirical analysis of spam marketing conversion. Proceedings of the 15th ACM conference on Computer and communications security. https://doi.org/10.1145/1455770.1455774
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
