Aircraft Data Communication Integrity Checks Using Hash-Linked Logs
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Solution Overview
Problem
Existing aircraft communication systems fail to detect the loss of messages between entities, which can lead to major or catastrophic events due to unknown message loss trends, necessitating a method for predictive maintenance and online self-assessment.
Innovation Solution
Implementing a blockchain-based system to log, compare, and verify data communication integrity by appending cryptographic hashes to messages across entities, allowing identification of message loss and degradation in aircraft components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If messages are sent at high frequency through multiple intermediate entities, then communication speed and responsiveness are improved, but message loss occurs undetected and can lead to catastrophic events
Solution Approach 1:
The system performs preliminary actions by logging messages and generating cryptographic hashes at each intermediate entity before messages are fully transmitted through the chain. This proactive approach allows for detection of message loss trends before they become catastrophic, resolving the contradiction by maintaining high communication speed while preventing undetected message loss.
Solution Approach 2:
The system implements feedback mechanisms by comparing message logs from the first entity with logs from intermediate entities and the second entity. When discrepancies are detected, the system generates alerts and initiates predictive maintenance actions, ensuring reliable message delivery while maintaining high communication speed through continuous monitoring.
2Device complexity
If traditional message handling is used without detection mechanisms, then system complexity is reduced, but message loss trends remain undetected until catastrophic events occur
Solution Approach 1:
The system introduces intermediary components (logging mechanisms, hash generation functions, and comparison modules) that act as mediators between message transmission and detection. These intermediaries enable message loss detection without requiring complete system redesign, thus resolving the contradiction by adding targeted complexity only where needed for detection.
Solution Approach 2:
The system replaces traditional mechanical message handling with cryptographic hash-based verification. Instead of complex physical detection mechanisms, the patent uses mathematical hash functions to verify message integrity and detect loss, reducing overall system complexity while improving detection capability.
3Measurement precision
If message logs are collected and compared from all entities, then message loss detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential verification elements (cryptographic hashes and message logs) from the complete message data. By comparing only these extracted elements rather than entire message contents, the system achieves high detection accuracy while minimizing processing time and computational resource requirements.
Solution Approach 2:
The system changes the verification parameter from comparing complete message contents to comparing cryptographic hashes of messages. This parameter change maintains detection accuracy while dramatically reducing processing time, as hash comparison is computationally much less intensive than full message comparison.
Data Source
AI summary
Method of verifying data communication integrity in an aircraft which has first and second data generating and sending entities. Data generated at the first entity is sent to the second entity as messages via a number of intermediate entities. The data communication is a blockchain with blocks, each being added to the blockchain by one of the entities and including a cryptographic hash representative of the prior block, thus linking the blocks. The method includes: a) logging a message subgroup and cryptographic hash at one or more of the first, second and intermediate entities; b) collecting message logs from each entity for verification; c) comparing messages sent by the first entity and messages received by the second entity; and d) if not all messages have arrived at said second entity, comparing message logs of intermediate entity(ies) with the message log of the first entity to identify where loss occurred.