Real-Time Ad Fraud Blacklisting System
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Solution Overview
Problem
Advertisers face significant losses due to fraudulent techniques employed by online publishers and advertising networks, which generate fake clicks and application installs using bots, leading to misuse of marketing budgets and a need for effective fraud detection systems.
Innovation Solution
A computer system utilizing advertisement fraud data to create real-time blacklists and whitelists of entities based on various parameters, including device ID, IP address, and confidence scores, with a feedback loop for optimizing the blacklist to prevent invalid blacklisting and ensure accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time blacklisting of fraudulent entities is implemented, then advertising revenue protection is improved, but system complexity increases
Solution Approach 1:
The patent introduces a blacklist system as an intermediary component between the fraud detection system and the advertisement serving system. This blacklist acts as a mediator that stores fraudulent entity identifiers and enables quick reference during ad serving, thereby protecting advertising revenue without requiring complex real-time analysis at the point of ad delivery.
Solution Approach 2:
The system performs preliminary fraud detection and blacklisting actions before fraudulent entities can cause significant damage. By collecting fraud data, generating blacklists, and distributing them proactively to advertisement servers, the system prevents fraud rather than merely responding to it, improving revenue protection while maintaining manageable system complexity.
2Measurement precision
If multiple parameters are used for blacklisting, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the fraud detection process into distinct components: fraud data collection, fraud analysis, blacklist generation, and parameter-based filtering. Each component handles specific parameters (device ID, IP address, publisher ID, etc.) independently, allowing for precise multi-parameter blacklisting while maintaining manageable system complexity through modular architecture.
3Productivity
If real-time fraud data collection is implemented, then productivity is improved, but loss of time increases
Solution Approach 1:
The system implements real-time fraud data collection by skipping traditional batch processing delays. Fraud data is collected, analyzed, and blacklisted continuously without interruption, allowing the system to rapidly respond to fraudulent activities while minimizing time loss through streamlined processing pipelines that eliminate unnecessary intermediate steps.
Data Source
AI summary
The present disclosure provides a system for utilization of an advertisement fraud data to blacklist or whitelist one or more entities. The system includes a first step of collecting the advertisement fraud data associated with online advertisement and commerce fraud. The system includes another step of creating a blacklist of one or more entities from the collected advertisement fraud data. The system includes another step of blocking the one or more entities present in the created blacklist in real-time. The system includes another step of generating a whitelist of one or more entities from the created blacklist of the one or more entities. The system includes yet another step of optimizing the blacklist of the one or more entities in real-time.