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Halting The Envious Activities using HADOOP

Author(s):

Vivek Kumar , Trinity Academy of Engineering; Gaurav Saste, Trinity Academy of Engineering; Mangesh Babar, Trinity Academy of Engineering; Meenakshi Sawant, Trinity Academy of Engineering

Keywords:

Map Reduce, HDFS, Click Stream Data, Web Log Analytics, Fraud Users

Abstract

Today large Number of peoples is interacting with the online application system that can perform fraud activities or real activities. So it’s not efficient for identifying which users are real among them. It’s one of the major and most popular aspect is online purchasing. People nowadays don’t hesitate to make money transactions online, for which new security measures are to be credited. But there is always a counter measure to threat the security of the system, such as fraudulent activities. For this use of click stream analysis proves beneficial. Click stream analysis works on the clicking pattern of users. Logs of user activities are stored using Hadoop, effective for processing and analyzing big data, which uses its Map Reduce feature for categorizing data on the key values provided. This helps in identifying normal and abnormal user behaviors which in turn helps in preventing the malicious activities which are carried out on online applications. This technique can be used to avoid the losses incurring from them and enhance the security from business perspective.

Other Details

Paper ID: IJSRDV4I40174
Published in: Volume : 4, Issue : 4
Publication Date: 01/07/2016
Page(s): 102-106

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