TT&C Integrity Monitoring via Network Traffic Analysis
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Solution Overview
Problem
Current space mission systems lack effective monitoring of telemetry, tracking, and command (TT&C) data integrity, relying on unverified commands sent to space vehicles, which can lead to insider threats and malicious activities.
Innovation Solution
A computer-implemented method and apparatus that analyze network traffic between a front-end processor and a cryptographic unit, creating a JSON object for data packets containing vehicle commands, and transmitting it to a cyber defense or SIEM module for anomaly scoring using machine learning or rule-based intrusion detection systems, providing enhanced visualization and intrusion detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators trust the TT&C software commands without verification, then the system operation is simple and fast, but the security and integrity of commands are compromised
Solution Approach 1:
The patent introduces a network monitor as an intermediary component that sits between the FEP and cryptographic unit, capturing and analyzing command traffic without disrupting the primary command path. This mediator extracts command data, creates JSON representations, and forwards them for analysis while allowing normal command flow to continue uninterrupted.
Solution Approach 2:
The system creates copies of command data packets for analysis purposes. The network monitor captures copies of the data stream containing vehicle commands, creates JSON object representations of these packets, and forwards the copies to cyber defense tools and SIEM systems for anomaly detection, while the original commands continue to be processed normally.
2Reliability
If network traffic analysis is implemented for all data packets, then command integrity monitoring is improved, but the processing time and computational resources increase
Solution Approach 1:
The network monitor extracts only the specific portions of data packets that contain vehicle commands, rather than analyzing entire data streams. It identifies and extracts command data from the network traffic, creates focused JSON representations of these extracted commands, and forwards them for analysis, reducing the volume of data requiring detailed processing.
Solution Approach 2:
The system applies partial analysis by focusing computational resources only on packets identified as containing vehicle commands, rather than analyzing every packet in full detail. The monitor selectively processes command-related traffic while allowing non-critical traffic to pass with minimal processing.
3Object-affected harmful factors
If comprehensive monitoring and anomaly detection are implemented, then security against insider threats is improved, but the system complexity and resource requirements worsen
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: a network monitor for capturing and extracting command data, a JSON object creation component for standardizing data representation, and separate cyber defense tools for anomaly detection. This segmentation allows each component to perform its specific function efficiently and enables independent configuration and maintenance of different monitoring capabilities.
Data Source
AI summary
Space system TT&C monitoring includes analyzing network traffic comprising of data packets between a front-end processor (FEP) and a cryptographic unit. A JavaScript Object Notation (JSON) object is created when the network traffic containing a vehicle command is detected. The JSON object is transmitted, by way of a data transport mechanism, to either a cyber defense module or a security information and event management (SIEM) module for further ingestions and visualization. The JSON object is analyzed using machine learning (ML) module or a rule-based intrusion detection system (IDS) module to generate an anomaly score for the SIEM module for further ingestions and visualization.