@inproceedings{47bd8d08827044c99d1c5282ec8dc9e8,
title = "Fraud Analysis Approaches in the Age of Big Data-A Review of State of the Art",
abstract = "Fraud is a criminal practice for illegitimate gain of wealth or tampering information. Fraudulent activities are of critical concern because of their severe impact on organizations, communities as well as individuals. Over the last few years, various techniques from different areas such as data mining, machine learning, and statistics have been proposed to deal with fraudulent activities. Unfortunately, the conventional approaches display several limitations, which were addressed largely by advanced solutions proposed in the advent of Big Data. In this paper, we present fraud analysis approaches in the context of Big Data. Then, we study the approaches rigorously and identify their limits by exploiting Big Data analytics.",
keywords = "Big Data, Data Mining, Fraud Analysis, Machine Learning, Statistical Modeling",
author = "Sara Makki and Rafiqul Haque and Yehia Taher and Zainab Assaghir and Gregory Ditzler and Hacid, {Mohand Said} and Hassan Zeineddine",
year = "2017",
month = oct,
day = "9",
doi = "10.1109/FAS-W.2017.154",
language = "English (US)",
series = "Proceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "243--250",
booktitle = "Proceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017",
note = "2nd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 ; Conference date: 18-09-2017 Through 22-09-2017",
}