Centro de Documentação da PJ
Monografia
 CD276 |
Fraud detection within mobile money [Documento electrónico] : a mathematical statistics approach / Frida Kappelin, Jimmie Rudvall.- Karlskrona, Sweden : [s.n.], 2015.- 1 CD-ROM ; 12 cm
Tese de Mestrado em "Computer Science" apresentada ao "Department of Computer Science & Engineering" do "Blekinge Institute of Technology", tendo como orientadores Dejan Baca, Stefan Axelsson. Ficheiro de 767 KB em formato PDF (54 p.).
FRAUDE BANCÁRIA, CRIME INFORMÁTICO, TELEFONE MÓVEL, ESTATÍSTICA, METODOLOGIAS, TESE, SUÉCIA
1 Introduction. 1.1 Background. 1.2 Research question. 2 Related Work. 2.1 Benford’s law. 2.2 Rules and limits. 2.3 Big Data. 3 Method. 3.1 Case study. 3.1.1 Case study of Priest attack (Phishing-attack). 3.1.2 Case study of Scooter attack (Grab and run-attack). 3.1.3 Other interesting operation types. 3.2 Statistical methods. 3.2.1 Benford’s law. 3.2.2 Application of Benford’s law. 3.2.3 Quantiles. 3.2.4 Application of quantiles. 3.3 Rules. 3.3.1 Definition of rules. 3.4 Limits. 3.5 Big data. 3.5.1 Data visualization. 3.6 Fraud Detector. 3.7 Performance measurements. 3.7.1 Receiving Operating Characteristics curve. 3.7.2 Other measurements. 4 Results. 4.1 Results of case study. 4.1.1 Phishing attack - general characteristics. 4.1.2 Grab and run attack - general characteristics. 4.1.3 Characteristics in the studied Mobile Money system. 4.1.4 Operation types. 4.2 Results of rules. 4.3 Data visualization. 4.4 Results of limits. 4.5 Fraud injection in a data set. 4.6 Result of fraud detector and performance. 4.6.1 Accuracy and precision. 4.6.2 Receiving Operating Characteristics curves. 5 Analysis. 6 Conclusions and Future Work. References. 7 Appendix. 7.1 Appendix A, Benford’s law. 7.1.1 Requirements. 7.1.2 Conformity. 7.1.3 Z-statistics. 7.1.4 Basic digit test. 7.2 Appendix B, R-code. 7.3 Appendix C, Visualization results.