Dual Computing Environment for Secured Automated Systems
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Solution Overview
Problem
Current automated systems, including Industrial Control Systems (ICS), are vulnerable to malware attacks that can cause irreparable damage, as seen in incidents like the Stuxnet virus, highlighting the need for a robust security solution to separate input/output operations from processing sections and ensure authentication of data and command responses.
Innovation Solution
Implementing a dual-computing environment architecture that combines a legacy computing environment for processing with a trusted computing environment for secure data transmission and authentication, allowing for the creation of a secure network where raw sensor and actuator data can be safely communicated and verified, enabling monitoring, detection, containment, blocking, and recovery from malware attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a legacy computing environment is used for processing sensor data and controlling actuators, then system functionality and compatibility are maintained, but security and reliability are compromised due to vulnerability to malware attacks
Solution Approach 1:
The computing environment is divided into two distinct segments: a legacy computing environment for maintaining system functionality and compatibility, and a trusted computing environment for ensuring security and reliability. This segmentation allows each environment to be optimized for its specific purpose while isolating vulnerabilities from critical functions.
Solution Approach 2:
A Trusted Platform Module (TPM) is introduced as an intermediary component that bridges the legacy and trusted computing environments. The TPM securely stores cryptographic keys and enables authentication between environments without requiring direct trust between the legacy system and external networks, thus mediating security concerns while maintaining system functionality.
2Measurement precision
If sensor raw data is processed through a legacy computing environment, then data processing capabilities are maintained, but data authentication and integrity are compromised
Solution Approach 1:
Data processing is segmented into two paths: one through the legacy computing environment for maintaining processing capabilities, and another through the trusted computing environment for ensuring data authentication and integrity. This allows the system to maintain both processing throughput and data authenticity simultaneously by utilizing both environments in parallel.
Solution Approach 2:
The trusted computing environment creates a secure copy of the data processing function, replicating the legacy environment's processing capabilities while adding authentication and integrity verification. This copying allows the system to maintain processing throughput while enhancing data authentication through the additional trusted environment layer.
3Reliability
If a trusted computing environment is added to protect against malware, then security is improved, but system complexity and hardware requirements increase
Solution Approach 1:
The Trusted Platform Module (TPM) is nested within the existing computing hardware architecture, allowing the trusted computing environment to be integrated without requiring a complete system replacement. This nesting approach enables malware protection capabilities to be embedded within the existing device structure, reducing overall system complexity compared to alternative solutions.
4Speed
If raw sensor output is transmitted directly to network nodes, then data transmission speed is maintained, but data security and authentication are compromised
Solution Approach 1:
The trusted computing environment acts as an intermediary between the sensor and network node, performing authentication and integrity verification of raw sensor output before transmission. This intermediary approach maintains data transmission speed by processing security functions at the data source rather than requiring separate authentication steps, while simultaneously enhancing data security through cryptographic verification.
Data Source
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AI summary
Secured automated or semi-automated systems are provided herein. In one embodiment, a sensor system includes a sensor, a legacy computing environment that is configured to communicate with the sensor and process sensor raw data output, and transmit the processed sensor output to a first network node over the network, and a trusted computing environment configured to receive raw sensor output directly from the sensor and transmit the raw sensor output to an additional network node or the first network node over the network.