Endpoint Detection Profiling Using Synthetic Network Fingerprints
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Solution Overview
Problem
Core networks have limited visibility into end user network endpoints, leading to inaccurate or tampered profiles, which hampers real-time identification, mitigation, and optimization of network events and conditions.
Innovation Solution
A system and method for detecting and profiling endpoints by receiving packets, determining device identity and behavior patterns, and generating synthetic profiles using fingerprinting and heuristic engines to enhance endpoint visibility and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If core networks rely on endpoint-provided profiles for identification, then the network can operate with basic endpoint information, but the profiles may be inaccurate or tampered with, reducing security and reliability
Solution Approach 1:
The patent introduces an intermediary detection system positioned between the endpoint and core network that acts as a mediator. This intermediary analyzes endpoint behavior and generates synthetic profiles, preventing direct reliance on potentially tampered endpoint-provided profiles while maintaining network operation. The intermediary translates endpoint characteristics into reliable identification data for the core network.
Solution Approach 2:
The patent replaces the mechanical/trust-based system of accepting endpoint-provided profiles with an analytical system that uses behavior analysis and fingerprinting. Instead of mechanically trusting endpoint declarations, the system substitutes a detection mechanism that observes and measures actual endpoint behavior patterns to generate reliable identification.
2Loss of information
If core networks implement comprehensive endpoint detection and profiling, then visibility and security improve, but the system complexity and processing requirements increase
Solution Approach 1:
The patent extracts only the essential and most reliable characteristics for endpoint identification, rather than attempting to capture and analyze all possible endpoint attributes. The detection system focuses on extracting key behavioral patterns and fingerprinting data that provide sufficient visibility while avoiding the complexity of comprehensive analysis of every endpoint feature.
Solution Approach 2:
The patent creates synthetic profiles that are simplified representations or copies of actual endpoint characteristics. Rather than maintaining complex raw data from all endpoint interactions, the system generates condensed synthetic profiles that capture essential identification information, reducing storage and processing complexity while maintaining visibility.
3Measurement precision
If the system analyzes multiple packets from multiple sources to create accurate profiles, then profile reliability improves, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary analysis of endpoint characteristics and behavior patterns during initial interactions, establishing baseline profiles before full network operations begin. This preliminary action allows the system to have identification data ready in advance, reducing the time required for profile generation during actual network operations while maintaining measurement precision through continued refinement.
Data Source
AI summary
A system for detecting and profiling endpoints of a computer network is provided. The system includes a first computing device including at least one processor in communication with at least one memory device. The first computing device is in communication with a computer network. The at least one memory device stores a plurality of instructions, which when executed by the at least one processor cause the at least one processor to receive a plurality of packets transmitted to the computer network, determine an identity of a first end point device associated with the plurality of packets, determine a behavior pattern for the first end point device based on the plurality of packets, and generate a synthetic profile for the first end point device based on the identity and the behavior pattern.