Click fraud prevention in pay-per-click model: Learning through multi-model evidence fusion

Kantardzic, Mehmed; Walgampaya, Chamila; Emara, Wael

doi:10.1109/icmwi.2010.5647854

Cited by 6 publications

(3 citation statements)

References 19 publications

(17 reference statements)

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“…What is left in the server side is separately analyzed, which is the scope of this paper, for potential bot networks. We have discussed the functionality of our system in detail in [10], [9], and [11].…”

Section: A Data Collection Pre-processing and Session Identificationmentioning

confidence: 99%

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Cracking the Smart ClickBot

Walgampaya

Kantardzic

2011

2011 13th IEEE International Symposium on Web Systems Evolution (WSE)

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Nowadays, almost every task involving Web traversing and information retrieval recurs to Web robots. Web robots are software programs that automatically traverse the Web's hypertext structure. They proliferate rapidly aside with the growth of the Web and are extremely valuable and important means not only for the large search engines, but also for many specialized services such as investment portals, competitive intelligence tools, etc. While many web robots serve useful purposes, recently, there have been cases linked to fraudulent activities committed by these Web robots. Click fraud, which is the act of generating illegitimate clicks, is one of them. This paper details the architecture and functionality of the Smart ClickBot, a sophisticated software bot that is designed to commit click fraud. It was first detected and reported by NetMosaics Inc. in March, 2010, a real time click fraud detection and prevention solution provider. We discuss the machine learning algorithms used, to identify all clicks exhibiting Smart ClickBot like patterns. We constructed a Bayesian classifier that automatically classifies server log data as being Smart ClickBot or not. We also introduce a Benchmark data set for Smart ClickBot. We disclose the results of our investigation of this bot to educate the security research community and provide information regarding the novelties of the attack.

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Section: A Data Collection Pre-processing and Session Identificationmentioning

confidence: 99%

“…It was first detected and reported by the NetMosaics click fraud detection system in 2010 [10], [9], [11]. Smart ClickBot is a for-sale click bot and it can be purchased [20].…”

Section: An Overview Of the Smart Clickbotmentioning

confidence: 99%

Cracking the Smart ClickBot

Walgampaya

Kantardzic

2011

2011 13th IEEE International Symposium on Web Systems Evolution (WSE)

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“…It was first detected and reported by the Netl\Iosaics click fraud detection system in 2010 [Kantardzic et al, 2008, Kantardzic et al, 2010a. Smart ClickBot is a for-sale click bot and it can be purchased [Walgampaya and Kantardzic, 2010j.…”

Section: An Overview Of the Smart Clickbotmentioning

confidence: 99%