Sensor Data Confidence Scoring for Secure Automated Machines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated machines, such as self-driving vehicles, are vulnerable to security breaches through compromised sensors, which can generate false input data leading to unsafe operating commands due to the lack of effective security measures for sensor data validation.
Innovation Solution
A communication system that includes a security server and a sensor security evaluation application, which assigns a security confidence score to sensor data based on vulnerability, location, and staleness factors, allowing the automated machine to differentiate and mitigate risky data, thereby ensuring safe operating commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is processed without security validation, then processing speed and system simplicity are maintained, but security reliability deteriorates due to vulnerability to compromised sensors
Solution Approach 1:
A security server is introduced as an intermediary component between sensors and the automated machine processing platform. The security server receives sensor data, determines security confidence scores based on vulnerability, location, and staleness factors, and provides validated data to the processing platform. This mediator approach enhances security reliability without significantly increasing the complexity of the core processing system.
Solution Approach 2:
The security validation function is segmented from the main processing system into a separate security server. This segmentation allows the security assessment to be performed independently, with dedicated algorithms for evaluating vulnerability factors, location factors, and staleness factors, while the main processing platform continues to operate with minimal modification.
2Reliability
If security confidence scoring is implemented for all sensor data, then security reliability is improved, but processing time increases due to additional validation steps
Solution Approach 1:
The security server implements partial validation by focusing assessment efforts on sensor data that exhibit higher risk characteristics. The system evaluates vulnerability factors, location factors, and staleness factors selectively, applying more rigorous validation to data from sensors with higher vulnerability scores or suspicious characteristics, while using streamlined validation for lower-risk data streams.
Solution Approach 2:
The security validation process dynamically adjusts assessment parameters based on the specific characteristics of each sensor data stream. The system modifies the depth and intensity of validation based on vulnerability scores, data type, and contextual factors, allowing faster processing for trusted sensors while maintaining high security standards for potentially compromised data sources.
Data Source
AI summary
Systems, methods, and software can be used to provide secure sensor data. In some aspects, a computer-implemented method includes: receiving, at a sensor security evaluation application executing on a device, sensor data from a sensor on the device; determining, by the sensor security evaluation application, a security confidence score associated with the sensor data; and transmitting, from the sensor security evaluation application, the security confidence score and the sensor data to a smart machine processor on the device.