Dissecting One Click FraudsAuthors: Nicolas Christin, Sally S. Yanagihara, Keisuke KamatakiProceedings of the ACM CCS 2010Reporter: Jing ChiuAdvisor: Yuh-Jye LeeEmail: D9815013@mail.ntust.edu.tw

112/04/21 1Data Mining & Machine Learning Lab

Outlines• Introduction

▫ One Click Fraud• Data Collection

▫ Channel BBS▫ Koguma-neko Teikoku▫ Wan-Cli Zukan

• Data Analysis▫ Infrastructural loopholes▫ Grouping miscreants▫ Evidence of other illicit activities

• Economic Incentives▫ Cost-benefit analysis▫ Fraud profitability▫ Legal aspects▫ Field measurements

• Conclusions112/04/21 2Data Mining & Machine Learning Lab

•One Click Frauds

Introduction

112/04/21 Data Mining & Machine Learning Lab 3

•2 Channel BBS▫The largest bulletin board in Japan▫March 6, 2006 ~ October 26, 2009

•Koguma-neko Teikoku▫Privately owned website▫August 24, 2006 ~ August 14, 2009

•Wan-Cli Zukan▫Privately owned website▫September 6,2006 ~ October 26, 2009

Data Collection

112/04/21 Data Mining & Machine Learning Lab 4

•Data parsing•Extracted attributes•Store to MySQL database

Data Collection (cont.)

112/04/21 Data Mining & Machine Learning Lab 5

Data Collection (cont.)

112/04/21 Data Mining & Machine Learning Lab 6

• Infrastructural loopholes▫Phone numbers▫Bank▫DNS registrars▫DNS resellers

• Grouping miscreants▫Use undirected graph to represent the dataset▫Fraud distribution

• Evidence of other illicit activities▫Eight blacklisting services and Google Safe

Browsing

Data Analysis

112/04/21 Data Mining & Machine Learning Lab 7

•Cost-benefit analysis•Fraud profitability•Legal aspects•Field measurements

Economic Incentives

112/04/21 Data Mining & Machine Learning Lab 8

•Collect and analyze a corpus of over 2,000 reported One Click Fraud incidents

•Describe a number of potential vulnerabilities which be used for scam

•Shows an important reason for why scam flourish

Conclusions

112/04/21 Data Mining & Machine Learning Lab 9

•Questions?

Thanks for your attention

112/04/21 Data Mining & Machine Learning Lab 10

•Top 10 popular registrars vs. Top 11 in One Click Frauds

DNS Registrars

112/04/21 Data Mining & Machine Learning Lab 11

DNS Resellers

112/04/21 Data Mining & Machine Learning Lab 12

112/04/21 Data Mining & Machine Learning Lab 13

Fraud Distribution

112/04/21 Data Mining & Machine Learning Lab 14

Evidence of other illicit activities

112/04/21 Data Mining & Machine Learning Lab 15

Ten most common amounts of money requested

112/04/21 Data Mining & Machine Learning Lab 16

Press reports of One Click Fraud arrests

112/04/21 Data Mining & Machine Learning Lab 17