scholarly journals Click Fraud Detection on the Advertiser Side

2014 ◽  
pp. 419-438 ◽  
Author(s):  
Haitao Xu ◽  
Daiping Liu ◽  
Aaron Koehl ◽  
Haining Wang ◽  
Angelos Stavrou
Keyword(s):  
Fraud Detection ◽  
Click Fraud

User click fraud detection method based on Top-Rank-k frequent pattern mining

2019 ◽  
Vol 33 (15) ◽  
pp. 1950150 ◽  
Author(s):  
Lijiao Pan ◽  
Shibiao Mu ◽  
Yingyan Wang
Keyword(s):  
Pattern Mining ◽  
Detection Method ◽  
Online Advertising ◽  
Fraud Detection ◽  
Frequent Pattern Mining ◽  
Detection Algorithm ◽  
Frequent Pattern ◽  
Good Efficiency ◽  
Click Fraud ◽  
Evaluation Score

A user click fraud detection method based on Top-Rank-k frequent pattern mining algorithm is presented to solve the click fraud problem appearing in current online advertising. Firstly, this method combines the click frequency of event samples, calculates the real evaluation score of click stream, and the click stream density function and evaluation score expression under multi-dimensional variables, and further obtains the time complexity of the next user’s click fraud process. Secondly, according to the Top-Rank-k frequent pattern, the process of click fraud detection algorithm is designed, and the click fraud user is analyzed and obtained. The results show that this method has good efficiency and correctness, and is superior to other similar algorithms.

scholarly journals Crowdsourcing for click fraud detection

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Riwa Mouawi ◽  
Imad H. Elhajj ◽  
Ali Chehab ◽  
Ayman Kayssi
Keyword(s):  
Fraud Detection ◽  
Click Fraud

Improving Click Fraud Detection by Real Time Data Fusion

2008 ◽  
Author(s):  
Mehmed Kantardzic ◽  
Chamila Walgampaya ◽  
Brent Wenerstrom ◽  
Oleksandr Lozitskiy ◽  
Sean Higgins ◽  
...  
Keyword(s):  
Data Fusion ◽  
Real Time ◽  
Fraud Detection ◽  
Time Data ◽  
Click Fraud ◽  
Real Time Data

scholarly journals Click Fraud Detection and Prevention System for Ad Networks

2019 ◽  
Vol 5 (1) ◽  
pp. 27 ◽  
Author(s):  
Paulo S. Almeida ◽  
João J. C. Gondim
Keyword(s):  
Fraud Detection ◽  
Context Information ◽  
Technical Data ◽  
Click Fraud ◽  
Prevention System

Click fraud detection consists of identifying the intention behind received clicks, given only technical data and context information. Reviewing concepts involved in click fraud practices and related work, a system that detects and prevents this type of fraud is proposed and implemented. The system is based and implemented on an ad network, one of the 3 main agents in the online ad environment, and for its validation, 3 servers were used, representing the publisher, the ad network with the system implemented and the announcer, and a bot that attempts to commit a click fraud.

The web ad-click fraud detection approach for supporting to the online advertising system

2022 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Pankaj Kumar Keserwani ◽  
Mahesh Chandra Govil ◽  
Emmanuel Shubhakar Pilli
Keyword(s):  
Online Advertising ◽  
Fraud Detection ◽  
Click Fraud ◽  
Detection Approach ◽  
The Web

An EM algorithm for click fraud detection

2016 ◽  
Vol 9 (3) ◽  
pp. 389-394 ◽  
Author(s):  
Xuening Zhu ◽  
Da Huang ◽  
Rui Pan ◽  
Hansheng Wang
Keyword(s):  
Em Algorithm ◽  
Fraud Detection ◽  
Click Fraud

scholarly journals A hybrid and effective learning approach for Click Fraud detection

2021 ◽  
Vol 3 ◽  
pp. 100016
Author(s):  
Thejas G.S. ◽  
Surya Dheeshjith ◽  
S.S. Iyengar ◽  
N.R. Sunitha ◽  
Prajwal Badrinath
Keyword(s):  
Fraud Detection ◽  
Learning Approach ◽  
Click Fraud ◽  
Effective Learning
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