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Based big data analysis of fraud detection for online transaction orders

  • Qinghong Yang*
  • , Xiangquan Hu
  • , Zhichao Cheng
  • , Kang Miao
  • , Xiaohong Zheng
  • *Corresponding author for this work
  • Beihang University
  • E-commerce China Dangdang Inc

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fraud control is important for the online marketplace. This study addresses the problem of detecting attempts to deceive orders in Internet transactions. Our goal is to generate an algorithmmodel to detect and prevent the fraudulent orders. First, after analyzing the real historical data of customers’ orders from Dangdang Website (http://www.dangdang.com. E-commerce China Dangdang Inc (Dangdang) is a leading e-commerce company in China. Dangdang officially listed on the New York Stock Exchange on December 8th, 2010, and is the first Chinese B2C e-commerce company which is completely based on online business to list on New York Stock.), we described characteristics related to transactions that may indicate frauds orders.We presented fraudulent orders characteristic matrix through comparing the normal and abnormal orders. Secondly, we apply Logic Regression model to identify frauds based on the characteristic matrix. We used real data from Dang company to train and evaluate our methods. Finally we evaluated the validity of solutions though analyzing feedback data.

Original languageEnglish
Title of host publicationCloud Computing - 5th International Conference, CloudComp 2014, Revised Selected Papers
EditorsRoy Xiaorong Lai, Victor C.M. Leung, Min Chen, Jiafu Wan
PublisherSpringer Verlag
Pages98-106
Number of pages9
ISBN (Electronic)9783319160498
DOIs
StatePublished - 2015
Event5th International Conference on Cloud Computing, CloudComp 2014 - Guilin, China
Duration: 19 Oct 201421 Oct 2014

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume142
ISSN (Print)1867-8211

Conference

Conference5th International Conference on Cloud Computing, CloudComp 2014
Country/TerritoryChina
CityGuilin
Period19/10/1421/10/14

Keywords

  • Big data
  • Fraud detection
  • Fraud order
  • Fraud prevention
  • Internet translation
  • Logistic regression

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