Network Interaction Correlation via Third-Party Edge Appliance
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Solution Overview
Problem
Illegitimate network interactions, such as those generated by botnets, lead to inappropriate payments in advertising revenue models, as existing systems fail to effectively distinguish between legitimate and fraudulent interactions.
Innovation Solution
An edge appliance monitors network traffic to analyze interactions by deriving information from TCP/IP and OSI layers 3-7, using models to assess legitimacy and report on fraudulence, with the ability to correlate interactions across multiple points in the network, and communicate with third-party systems for scalability and independence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network interactions are monitored and analyzed to distinguish legitimate from illegitimate interactions, then payment accuracy is improved, but system complexity increases
Solution Approach 1:
The monitoring system is segmented into multiple independent components: network traffic capture modules, interaction analysis modules, legitimacy determination modules, and payment processing modules. Each component performs a specific function, allowing the complex overall system to be built from manageable, independent parts that can be developed and maintained separately while achieving high measurement precision in interaction legitimacy detection.
2Measurement precision
If detailed network traffic analysis is performed to assess interaction legitimacy, then fraud detection accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing legitimacy criteria, pre-configuring analysis rules, and pre-positioning monitoring components before actual network traffic analysis begins. This allows the system to quickly evaluate interactions against predetermined standards without requiring complex real-time decision-making, thereby maintaining high fraud detection accuracy while minimizing processing time delays.
3Reliability
If network monitoring is implemented to reduce inappropriate payments, then payment reliability is improved, but network performance may deteriorate
Solution Approach 1:
The monitoring system is implemented as an intermediary component that sits between network traffic sources and payment processing systems. It captures and analyzes traffic copies without interfering with the actual network flow, determining legitimacy based on pre-established criteria and allowing approved transactions to pass through unchanged. This intermediary approach ensures payment reliability through thorough analysis while maintaining network performance by not creating bottlenecks in the actual data flow.
Data Source
AI summary
Correlating a network interaction is disclosed. A network interaction is detected at an advertising network. A network interaction is detected at an advertiser. The network interaction at the advertising network is correlated with the network interaction at the advertiser. The network interaction correlation is performed by a third party that is not affiliated with the advertising network or the advertiser.