Spamalytics: an empirical analysis of spam marketing conversion

By Chris Kanich, Christian Peter Kreibich, Kirill Levchenko, Brandon Enright, Geoffrey M. Voelker, Vern Paxson, Stefan Savage. CACM, 2009

334 citations recorded by the source corpus.

Subfields: Information Systems, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/273433026cb7c9309f73b8a6115505c64d63f579

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In Information Systems

In Statistical and Nonlinear Physics

Citations in the corpus

The Plight of the Targeted Attacker in a World of Scale (2010, methodology): “Using the numbers from the spam campaign documented by Kanich et al. [28]: 100 .”
Handcrafted Fraud and Extortion: Manual Account Hijacking in the Wild (2014, methodology): “This explanation is supported by previous work [14] that observed that the spam delivery rate was 10 times higher for webmail protected by commodity spam filtering than by large mail provider such as Gmail, Yahoo, and Hotmail.”
Your botnet is my botnet: analysis of a botnet takeover (2009, background): “Given the importance of the problem, signiﬁcant research effort has been invested to gain a better understanding of the botnet phenomenon [8, 29], to study the modus operandi of cyber crim-inals [19, 22], and to develop effective mitigation techniques [10, 11].”
A Survey on Malware Detection Using Data Mining Techniques (2017, methodology): “Botnets are widely used in launching Distributed Denial of Service (DDoS) attacks [Kanich et al. 2008], sending spam emails, and hosting phishing fraud.”
Understanding fraudulent activities in online ad exchanges (2011, background): “Recent work has examined botnets and researchers have infiltrated or seized control of parts of the botnet infrastructure to gain more insight into their inner-workings [15, 22, 24, 25].”
Differential privacy for collaborative security (2010, background): “Internet network operators need to .ght global phenomena such asbotnets,butthey arehamperedbythefactthat operators can observe only the traf.c in their local domains.”
Click Trajectories: End-to-End Analysis of the Spam Value Chain (2011, methodology): “Our own previous work on spam conversion also used empirical means to infer parts of the return-on-investment picture in the spam business model [21].”
A Learning-Based Approach to Reactive Security (2009, background): “For example, attackers compromise machines and form botnets because they make money from spam [8] or rent the botnet to others [9].”
Measuring the Cost of Cybercrime (2012, neutral): “In one 2008 study, researchers manipulated the command and control channel of the Storm botnet to drive estimates of the underlying consumer conversion rate [29].”
No Encore for Encore? Ethical questions for web-based censorship measurement (2015, background): “A well-known one is Spamalytics, a study where researchers took over control of a botnet—a network of machines infected with malware and controlled by a single operator—to modify and study the spam campaigns that originated from the infected machines [5].”
BotGrep: Finding P2P Bots with Structured Graph Analysis (2010, methodology): “To evaluate the effect of sampling, we replayed packet-level traces collected by the authors of [42] from Storm botnet nodes, and simulated NetFlow to determine the fraction of botnet links that would be detected.”
Aiding the Detection of Fake Accounts in Large Scale Social Online Services (2012, methodology): “The flow-based scheme GateKeeper [53] improves over SumUp [52].”