The Anatomy of Clickbot.A

By Neil Daswani, Michael Stoppelman. 2007

198 citations recorded by the source corpus.

How researchers see this paper

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Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking (2017, background): “, number of ad impressions, click-through rate or CTR, bounce rate) as well as effective mechanisms to overcome fraudulent activities such as click spam [7, 22].”
Adversarial Web Search (2011, background): “Another option is the use of large botnets, which, through their size, can conceal the behavior by spreading it out over thousands of infected machines [61].”
A survey of mobile malware in the wild (2011, methodology): “non-malicious networks by using desktop malware to load and click on advertisements [43, 22].”
Understanding fraudulent activities in online ad exchanges (2011, background): “Studies also have shown how malware can exploit ad networks [7, 10].”
BotMiner: Clustering Analysis of Network Traffic for Protocol- and Structure-Independent Botnet Detection (2008, methodology): “, HTTP [8, 14, 24, 39]), and the structure moved from centralized to distributed (e.”