Server-Based Trust Store Discovery via TLS Certificate Feedback
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Solution Overview
Problem
Service operators face challenges in determining which root Certificate Authorities (CAs) their client base trusts, as client trust stores are unknown and vary by browser, OS, or application, making it difficult to identify trusted digital certificates and plan for certificate replacements to avoid service outages.
Innovation Solution
The system uses a non-material TLS connection to periodically present randomly-selected digital certificates to clients and monitor responses, employing machine learning techniques to infer trusted CAs by analyzing successful and failed connections, particularly using the favicon.ico URL, and maintaining a certificate manager to process and analyze client reactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional techniques are used to identify trusted root CAs, then service operators can maintain security, but they face undue business burdens and guesswork in determining which CAs clients trust
Solution Approach 1:
The system implements feedback by monitoring client responses to presented digital certificates. When a certificate is presented and the client accepts it (indicated by successful TLS handshake or absence of certificate rejection errors), this feedback information is recorded to infer that the issuing CA is trusted by the client. This automated feedback mechanism eliminates guesswork and business burdens associated with conventional manual identification methods.
Solution Approach 2:
The system allows clients to effectively self-report their trust store contents through their natural certificate validation behavior. Clients don't need to explicitly provide their trust store information; instead, their acceptance or rejection of presented certificates automatically reveals which CAs they trust, making the process self-service oriented and eliminating manual intervention.
2Reliability
If service operators manually track and manage digital certificates, then they can maintain trust, but it becomes difficult to plan for certificate replacements and avoid service outages
Solution Approach 1:
The system performs preliminary action by continuously and automatically monitoring which CAs are trusted by the client base before certificate expiration issues arise. By maintaining an up-to-date inference of trusted CAs through ongoing certificate presentation and response monitoring, service operators can proactively plan certificate replacements in advance, avoiding last-minute crises and service outages.
Solution Approach 2:
The system replaces manual mechanical tracking processes with automated electronic monitoring. Instead of operators manually tracking certificate expirations and trust relationships, the system automatically presents certificates, monitors client responses, and maintains an updated view of trusted CAs through electronic data collection and analysis, significantly reducing time and effort required.
3Adaptability or versatility
If trust stores include large numbers of CAs, then clients have more trusted certificates, but it becomes very difficult to identify which CAs should be trusted or specify which digital certificates should be trusted
Solution Approach 1:
The system extracts the specific subset of CAs that are actually trusted by the client base from the large trust store. Instead of dealing with all CAs in the trust store, the system presents certificates from various CAs and extracts information about which specific CAs clients actually trust based on their responses, simplifying the identification process to only the relevant trusted CAs.
Data Source
AI summary
An automated server-based scheme allows a hosted service such as an individual computer system, computer application, or network service, to infer root certificate authorities present in client trust stores. Presenting a random selection of one or more digital certificates to a given client seeking a favorite icon URL, in response to a Transport Layer Security (TLS) connection request from the client, allows the service operator's trained machine learning system to define a customized set of potentially-trusted root certificate authorities based on learned successes and failures of connections with the given client, as well as other parties. The hosted service operator may employ a certificate manager and/or client-specific rules for presenting the certificates.