Anonymous Sensor Trust Checks for Threat Data Verification
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Solution Overview
Problem
Cybersecurity systems face challenges in determining the trustworthiness of anonymized cyberthreat sensor data from unknown sources, as they cannot verify the data's authenticity without direct contact with the sensor owners, leading to potential false positives and compromised threat detection accuracy.
Innovation Solution
An automated mechanism to verify sensor trustworthiness through a four-phase process: sensor health check, data ballpark check, reputation comparison, and manual review, using predefined envelopes and reputation lists to assess sensor operation and data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor data is collected from anonymous third parties to expand data sources, then the quantity of sensor data increases, but the trustworthiness of the sensor data decreases due to inability to verify sensor operation
Solution Approach 1:
The patent introduces an automated verification mechanism that acts as an intermediary between anonymous sensors and the threat intelligence product. This mechanism collects sensor operating parameters, compares them against expected parameters, and determines trustworthiness automatically, enabling the system to process data from anonymous sources without direct verification of the sensor owners.
Solution Approach 2:
The system performs self-verification by automatically collecting sensor operating parameters, comparing them to expected parameters, and determining trustworthiness without requiring external verification from sensor owners. The automated mechanism serves itself by establishing confidence in anonymous sensor data through parameter comparison and reputation database checks.
2Reliability
If automated verification mechanisms are implemented to ensure data trustworthiness, then the reliability of sensor data improves, but the device complexity increases due to multiple verification phases
Solution Approach 1:
The verification process is divided into distinct phases: Phase 1 checks sensor operating parameters against expected parameters, Phase 2 examines sensor data against expected data characteristics, Phase 3 corroborates findings against reputation databases, and Phase 4 applies existing protections. This segmentation allows the complex verification process to be managed through modular, sequential steps rather than a monolithic system.
Data Source
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Figure 3A~3C
AI summary
Systems, methods and products for determining the trustworthiness of anonymous sensors, including a sensor health check (102), a data ballpark check (104), a reputation comparison (106), and optional "last resort" procedures (108). The sensor health check (102) examines sensor operating parameters to see if they fall within an envelope of expected values. If not, the sensor is unhealthy and is not trusted. The data ballpark check (104) determines whether the sensor's traffic data falls within a predefined envelope of values. If the sensor is healthy and the traffic is within expected ranges, the sensor is trusted. If the traffic data is outside expected ranges, the reputation comparison (106), determines whether IP addresses, domains or other IOCs in the traffic data are found in the reputation list which may corroborate the traffic as trustworthy because it represents malicious or not-in-the-wild traffic. "Last resort" procedures (108) may include applying safelists/blocklists, signature controls etc. to verify sensor/data trustworthiness.