AI-based Strategies in Combating Ad Fraud in Digital Advertising: Implementations, and Expected Outcomes

Abstract

The digital advertising industry faces significant challenges due to ad fraud, which encompasses various deceptive practices such as click fraud, domain spoofing, ad injection, pixel stuffing, forced redirect ads, and SDK spoofing. These fraudulent activities lead to financial losses for advertisers and undermine the effectiveness of their campaigns. This research aims to investigate the application of artificial intelligence (AI) techniques to combat ad fraud and discuss five AI-based strategies, their implementations, and potential outcomes. The proposed strategies include: 1) anomaly detection and behavioral analysis, 2) domain verification and network analysis, 3) real-time monitoring and ad content analysis, 4) SDK analysis and app attribution modeling, and 5) collaborative filtering and industry collaboration. Each strategy uses AI algorithms and machine learning models to identify and mitigate fraudulent activities in different aspects of the digital advertising ecosystem. The implementation of these strategies involves training AI models to detect anomalies in ad traffic patterns, analyze user behavior, verify domain authenticity, monitor ad content, and accurately attribute app installs. Anomaly detection and behavioral analysis utilize machine learning to identify suspicious patterns and deviations from normal user engagement. AI-powered techniques are used in domain verification and network analysis to detect disparities that indicate domain spoofing. Real-time monitoring and ad content analysis use AI to scan for malicious ad placements and fraudulent content. SDK analysis and app attribution modeling leverage AI to identify abnormal SDK interactions and discrepancies in install reporting. In collaborative filtering and industry collaboration, stakeholders share data and ideas to improve collective fraud detection skills. The expected outcomes of implementing these AI-based strategies include proactively identifying and mitigating fraudulent activities, avoiding payments for low-quality traffic, ensuring ad placement on legitimate websites, preventing malware infections or privacy breaches, optimizing app marketing campaigns, and strengthening defenses against evolving ad fraud tactics.