Click Fraud Detection and Prevention System for Ad Networks

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.

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Data Sampling Strategies for Click Fraud Detection Using Imbalanced User Click Data of Online Advertising: An Empirical Review

IETE Technical Review ◽

10.1080/02564602.2021.1915892 ◽

2021 ◽

pp. 1-10

Author(s):

Deepti Sisodia ◽

Dilip Singh Sisodia

Keyword(s):

Online Advertising ◽

Fraud Detection ◽

Sampling Strategies ◽

Data Sampling ◽

Click Fraud

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Quad division prototype selection-based k-nearest neighbor classifier for click fraud detection from highly skewed user click dataset

Engineering Science and Technology an International Journal ◽

10.1016/j.jestch.2021.05.015 ◽

2021 ◽

Author(s):

Deepti Sisodia ◽

Dilip Singh Sisodia

Keyword(s):

Nearest Neighbor ◽

Fraud Detection ◽

Prototype Selection ◽

K Nearest Neighbor ◽

Click Fraud ◽

Nearest Neighbor Classifier ◽

Neighbor Classifier

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Click Fraud Detection of Online Advertising-LSH Based Tensor Recovery Mechanism

IEEE Transactions on Intelligent Transportation Systems ◽

10.1109/tits.2021.3107373 ◽

2021 ◽

pp. 1-8

Author(s):

Fumin Zhu ◽

Chen Zhang ◽

Zunxin Zheng ◽

Sattam Al Otaibi

Keyword(s):

Online Advertising ◽

Fraud Detection ◽

Click Fraud ◽

Recovery Mechanism ◽

Tensor Recovery

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

International Journal of Modern Physics B ◽

10.1142/s0217979219501509 ◽

2019 ◽

Vol 33 (15) ◽

pp. 1950150 ◽

Cited By ~ 1

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.

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