Detecting Telecommunication Fraud with Visual Analytics: A Review

[1]  Silvia Miksch,et al.  Visual Analytics for fraud detection and monitoring , 2015, 2015 IEEE Conference on Visual Analytics Science and Technology (VAST).

[2]  V. Subramaniyaswamy,et al.  Data mining approach for subscription-fraud detection in telecommunication sector , 2014 .

[3]  Alex Endert,et al.  The State of the Art in Integrating Machine Learning into Visual Analytics , 2017, Comput. Graph. Forum.

[4]  Ronald J. Brachman,et al.  Brief Application Description; Visual Data Mining: Recognizing Telephone Calling Fraud , 2004, Data Mining and Knowledge Discovery.

[5]  Richard May,et al.  Foundations and Frontiers in Visual Analytics , 2009, Inf. Vis..

[6]  AignerWolfgang,et al.  Special Section on Visual Analytics , 2014 .

[7]  William N. Dilla,et al.  Data visualization for fraud detection: Practice implications and a call for future research , 2015, Int. J. Account. Inf. Syst..

[8]  Tom Fawcett,et al.  Adaptive Fraud Detection , 1997, Data Mining and Knowledge Discovery.

[9]  Silvia Miksch,et al.  A matter of time: Applying a data-users-tasks design triangle to visual analytics of time-oriented data , 2014, Comput. Graph..

[10]  Deepa Mangala,et al.  Corporate Fraud Prevention and Detection: Revisiting the Literature , 2015 .

[11]  Allan R. Wilks,et al.  Fraud Detection in Telecommunications: History and Lessons Learned , 2010, Technometrics.

[12]  Iyabo Awoyelu,et al.  Fraud Detection in Telecommunications Industry: Bridging the Gap with Random Rough Subspace Based Neural Network Ensemble Method , 2015 .

[13]  Prabin Kumar Panigrahi,et al.  A Review of Financial Accounting Fraud Detection based on Data Mining Techniques , 2012, ArXiv.

[14]  Bojana Dalbelo Basic,et al.  Visualization of Text Streams: A Survey , 2010, KES.

[15]  Mohammad Mehdi Sepehri,et al.  A data mining framework for detecting subscription fraud in telecommunication , 2011, Eng. Appl. Artif. Intell..

[16]  Silvia Miksch,et al.  Visual analytics for event detection: Focusing on fraud , 2018, Vis. Informatics.

[17]  Simon Pietro Romano,et al.  Kerberos: A real-time fraud detection system for IMS-enabled VoIP networks , 2017, J. Netw. Comput. Appl..

[18]  Yong Hu,et al.  The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature , 2011, Decis. Support Syst..

[19]  Mohammad Abdollahi Azgomi,et al.  A Taxonomy of Frauds and Fraud Detection Techniques , 2009, ICISTM.

[20]  Claudio A. Perez,et al.  Subscription fraud prevention in telecommunications using fuzzy rules and neural networks , 2006, Expert Syst. Appl..

[21]  Dominik Olszewski,et al.  A probabilistic approach to fraud detection in telecommunications , 2012, Knowl. Based Syst..

[22]  David J. Hand,et al.  Statistical fraud detection: A review , 2002 .

[23]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[24]  David S. Ebert,et al.  A Survey on Visual Analysis Approaches for Financial Data , 2016, Comput. Graph. Forum.