Data Sampling Strategies for Click Fraud Detection Using Imbalanced User Click Data of Online Advertising: An Empirical Review-Reference-Cited by-同舟云学术

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

Published:2021-04-26 Issue: Volume: Page:1-10
ISSN:0256-4602
Container-title:IETE Technical Review
language:en
Short-container-title:IETE Technical Review

Author:

Sisodia Deepti¹,Sisodia Dilip Singh¹

Affiliation:

1. Department of Computer Science and Engineering, National Institute of Technology, Raipur, India

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/02564602.2021.1915892

Reference69 articles.

1. S. Nagaraja, and R. Shah, “Clicktok: Click fraud detection using traffic analysis,” in Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks, Miami Florida, vol. 2, 2019, pp. 105–116.

2. An ensemble learning based approach for impression fraud detection in mobile advertising

3. K. Springborn, and P. Barford, “Impression fraud in on-line advertising via pay-per-view networks,” in 22nd USENIX Security Symposium, 2013, pp. 211–226. Available: https://www.usenix.org/system/files/conference/usenixsecurity13/sec13-paper_springborn.pdf.

4. Z. Li, K. Zhang, Y. Xie, F. Yu, and X. Wang, “Knowing your enemy: Understanding and detecting malicious web advertising,” in Proceedings of the 2012 ACM Conference on Computer and Communications Security, 2012, pp. 674–686, doi:10.1145/2382196.2382267.

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