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Combating Evolving Threats: A Systematic Review of Online Ad Fraud Detection
Abstract
This systematic review investigates online ad fraud detection and brand safety research from 2011 to 2024. The analysis reveals a continuous battle against click fraud and its evolving forms. Machine learning has become a cornerstone of detection efforts, offering superior capabilities compared to traditional methods. The rise of mobile advertising necessitated the development of specialized solutions to address distinct user behavior and data patterns on this platform. However, research highlights an expanding threat landscape beyond click fraud, encompassing impression fraud and placement fraud. Brand safety concerns have also gained prominence, emphasizing the importance of protecting brand reputation. The review underscores the need for collaboration between researchers and industry professionals to achieve a more secure and trustworthy online advertising ecosystem.
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