Router Policy Enforcement for Real-Time Network Threat Isolation
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Solution Overview
Problem
Current network systems lack effective real-time protection against advanced persistent threats and day-zero attacks due to increased data network speeds and complexity from network disaggregation, with existing methods failing to provide preemptive security for distributed denial of service (DDoS), protocol anomalies, and zero-day attacks.
Innovation Solution
A system comprising a traffic collector, machine learning component, and policy component for real-time analysis of packet metadata to detect anomalies and autonomously generate mitigation policies, which are enforced across network endpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If standard protocols (netflow/sflow) with offline analysis are used, then system complexity is reduced, but real-time threat detection capability deteriorates
Solution Approach 1:
The system performs preliminary actions by continuously collecting and analyzing packet metadata in real-time before threats fully materialize. The anomaly detection system proactively identifies patterns and generates policy rules in advance, enabling preemptive mitigation rather than reactive response to attacks
Solution Approach 2:
The patent introduces an intermediary anomaly detection system that sits between standard networking protocols and policy enforcement. This intermediary layer analyzes packet metadata and generates anomaly scores, translating raw network data into actionable policy rules without requiring fundamental changes to existing networking infrastructure
2Reliability
If dedicated intrusion prevention systems are deployed, then threat detection capability is improved, but response time to zero-day attacks deteriorates
Solution Approach 1:
The system performs self-service by autonomously generating policy rules from detected anomalies without requiring human analysis or intervention. When the anomaly detection system identifies a threat pattern, it automatically creates and enforces mitigation policies, eliminating the time lag associated with human response to zero-day attacks
Solution Approach 2:
The patent implements continuous feedback loops where policy enforcement outcomes are monitored and fed back into the anomaly detection system. This feedback mechanism allows the system to learn from enforcement results and refine its detection algorithms in real-time, improving response effectiveness without additional human intervention
3Adaptability or versatility
If network disaggregation is implemented, then system adaptability is improved, but security vulnerability increases
Solution Approach 1:
The anomaly detection system provides universal protection across multiple disaggregated network components. By analyzing packet metadata from various network elements and applying unified anomaly detection algorithms, the system creates a cohesive security layer that protects the entire disaggregated network architecture from threats
4Measurement precision
If real-time packet metadata analysis is performed, then anomaly detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The system extracts only the essential packet metadata fields required for anomaly detection rather than analyzing complete packet contents. By selectively extracting relevant metadata elements and focusing analysis on key indicators, the system achieves high detection accuracy while minimizing processing complexity
Data Source
AI summary
This disclosure describes methods, devices, and systems for network policy enforcement. An example method includes, at a router device comprising memory and control circuit, enforcing one or more policy rules at the router device. The method also includes, while enforcing the one or more policy rules, receiving an updated policy rule from a policy server via a policy agent, and implement the updated policy rule by adjusting a data plane of the router device via the policy agent.