Online advertising security: Issues, taxonomy, and future directions

Z Pooranian, M Conti, H Haddadi… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Online advertising has become the backbone of the Internet economy by revolutionizing
business marketing. It provides a simple and efficient way for advertisers to display their …

[HTML][HTML] A hybrid and effective learning approach for click fraud detection

GS Thejas, S Dheeshjith, SS Iyengar… - Machine Learning with …, 2021 - Elsevier
Click Fraud is a fraudulent act of clicking on pay-per-click advertisements to increase the
site's revenue or to drain revenue from the advertiser. This illegal act has been putting …

Deep learning-based model to fight against ad click fraud

GS Thejas, KG Boroojeni, K Chandna, I Bhatia… - Proceedings of the …, 2019 - dl.acm.org
Click fraud is a fast-growing cyber-criminal activity with the aim of deceptively clicking on the
advertisements to make the profit to the publisher or cause loss to the advertiser. Due to the …

GFD: A weighted heterogeneous graph embedding based approach for fraud detection in mobile advertising

J Hu, T Li, Y Zhuang, S Huang… - Security and …, 2020 - Wiley Online Library
Online mobile advertising plays a vital role in the mobile app ecosystem. The mobile
advertising frauds caused by fraudulent clicks or other actions on advertisements are …

Click Fraud Detection of Online Advertising Using Machine Learning Algorithms

B Kirkwood, M Vanamala… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
With online advertising quickly growing, click fraud has become a major concern for
advertisers. Publishers are paid by the advertisers for each click of their ad on the …

Smart mobile bot detection through behavioral analysis

I Aberathne, C Walgampaya - Advances in Data and Information Sciences …, 2018 - Springer
Mobile advertising became a huge financial pillar due to drastic increase in smartphones
and tablets usage in recent years. This huge-revenue ecosystem is severely thwarted by ad …

Multimodal and contrastive learning for click fraud detection

W Li, Q Zhong, Q Zhao, H Zhang, X Meng - ar** marvels on the web, and it is characterized as a strategy for
abusing psychological predispositions to pull in online viewership, that is, to draw in" clicks." …