Access Management for Content Delivery Networks: Measurements, Models, and Strategies

Abstract

We address the challenge of managing access to Content Delivery Networks (CDNs). In particular, we consider a scenario where users request tokens to access content, and one form of piracy consists in illegally sharing tokens. We focus on mitigating token misuse through performance analysis and statistical access pattern monitoring. Specifically, we examine how illegal token sharing impacts content delivery infrastructure and propose defining acceptable request limits to detect and block suspicious access patterns. Additionally, we introduce countermeasures against piracy, including selective quality degradation for users identified as engaging in illegal sharing, aiming to deter such behavior. Using queuing models, we quantify the impact of piracy on system performance across different scenarios. To validate our model, we perform statistical tests that compare real CDN traffic patterns with the expected request intervals in our proposed framework. These measures—defining access thresholds, quality degradation for unauthorized use, and statistical alignment checks—enhance CDN access management, preserving infrastructure integrity and the legitimate user experience while reducing operational costs.