CDN Cross-Domain User Agent Tracking via Encrypted Cookies
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Solution Overview
Problem
Current content delivery networks (CDNs) face challenges in effectively tracking and distinguishing between human and automated user agents across multiple domains, which hampers personalized content delivery and fraud mitigation.
Innovation Solution
A CDN system that generates a unique identifier for user agents, stored as an encrypted cookie, to track and classify their behavior across domains, using active and passive methods, and analyzes this data to differentiate between human and automated entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cookies are shared across content domains to track user behavior, then user profiling capability is improved, but system complexity and coordination requirements increase
Solution Approach 1:
The patent introduces a CDN service provider as an intermediary that operates a distributed tracking system across multiple content domains. The CDN inserts tracking objects into content delivered to user agents and collects behavior data centrally, eliminating the need for direct coordination between non-cooperating content domains. This mediator approach enables cross-domain user profiling while keeping individual domain implementations simple.
2Loss of information
If a distributed tracking system is implemented across multiple domains, then user behavior data collection is improved, but ease of operation and implementation difficulty worsen
Solution Approach 1:
The CDN service provider's distributed system performs multiple functions: content delivery, tracking object insertion, data collection, and user profiling. By making the CDN multi-functional, the system enables cross-domain tracking without requiring separate specialized infrastructure. Content providers can participate in the tracking ecosystem by simply using the CDN's content delivery service, reducing implementation barriers.
3Reliability
If user agents are tracked across multiple domains using unique identifiers, then fraud detection capability is improved, but device complexity and processing requirements increase
Solution Approach 1:
The tracking system uses passive techniques where user agents automatically carry tracking identifiers (such as cookies) across domains without requiring active participation or configuration. The CDN service automatically inserts tracking objects and collects behavior data without manual intervention from content providers or users. This self-service approach reduces operational complexity while maintaining fraud detection capabilities.
Data Source
AI summary
A content delivery network (CDN) service provider extends a content delivery network to gather information on atomically identifiable web clients (called “user agents”) as such computer-implemented entities interact with the CDN across different domains being managed by the CDN service provider. The data system tracks user agents, preferably via cookies, although one or more passive techniques may be used. A user agent may be a cookie-able device having a cookie store. As the user agent navigates across sites, a CDN-specific unique identifier used by the system to correlate user agents is generated. Preferably, the unique identifier is stored as an encrypted cookie. The unique identifier represents one user agent (and, thus, one cookie-able device's store). The system tracks user agent behavior on and across customer sites that are served by the CDN, and these behaviors are classified into identifiable “segments” that may be used to create a profile.