DNS Tunneling Detection via Subdomain Entropy Analysis

The patent introduces a DNS filter as an intermediary component between the DNS client and DNS server. This filter intercepts DNS requests, analyzes them against configured policies and machine learning models, and selectively blocks malicious requests while allowing legitimate traffic to pass through. The intermediary approach maintains network functionality for legitimate DNS queries while preventing DNS tunneling attacks, resolving the contradiction between network usability and security.

The patent extracts DNS traffic analysis from traditional security measures and creates a dedicated DNS filtering system. By separating DNS monitoring functions from general-purpose antivirus and intrusion detection systems, the patent enables specialized detection capabilities including domain reputation checking, machine learning-based anomaly detection, and policy-based blocking. This extraction allows the system to detect DNS tunneling attacks that would be invisible to traditional security measures while maintaining basic security protections.

The patent applies local quality by implementing differential filtering rules for different DNS requests. Instead of uniformly blocking all DNS traffic, the system analyzes each request's characteristics (domain reputation, request patterns, entropy levels, policy compliance) and applies selective blocking. Legitimate DNS requests that pass all security checks are allowed through, while only requests matching tunneling attack patterns are blocked. This localized, granular approach maintains legitimate network access while preventing attacks.