Encrypted Sensor Data Transmission via Blockchain Nodes
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Solution Overview
Problem
Conventional databases and sensor systems in industrial control networks face security vulnerabilities, data corruption, and unauthorized access due to unencrypted data transmission and storage, which can lead to breaches and system manipulation.
Innovation Solution
Implementing a fully encrypted, identity-attested, distributed network architecture using blockchain technology for SCADA/PLC systems, where data is encrypted at rest and in transit, and only decrypted for processing or viewing on specific devices, with edge processors acting as mini-nodes in a decentralized blockchain network to validate data and commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored or transmitted unencrypted in conventional databases, then data access and processing are simple and fast, but security is compromised and data can be stolen or manipulated by malicious actors
Solution Approach 1:
Data is encrypted before storage or transmission using cryptographic algorithms. The encryption process transforms readable data into ciphertext that cannot be accessed or understood without the proper decryption key, preventing unauthorized access while maintaining data utility for authorized operations
Solution Approach 2:
A cryptographic intermediary layer is introduced between data and storage/transmission systems. This layer applies encryption algorithms that act as a mediator, converting data into secure ciphertext form while preserving the ability to restore original data through authorized decryption processes
2Reliability
If sensor data is transmitted without encryption, then transmission speed and processing efficiency are maintained, but data integrity is compromised and data can be spoofed or altered in transit
Solution Approach 1:
Cryptographic protection is applied to sensor data before transmission begins. Encryption algorithms process the data in advance, creating ciphertext that maintains integrity during transmission and can be verified through cryptographic authentication mechanisms
Solution Approach 2:
Traditional physical security measures for data protection are replaced with cryptographic mechanisms. Instead of relying on physical access controls or secure hardware environments, the system uses mathematical encryption algorithms to protect data integrity and authenticity during transmission
3Reliability
If conventional databases are used for sensor data storage, then data access is straightforward, but data can be corrupted or lost due to outside factors such as hacking or power outages
Solution Approach 1:
Data is divided into cryptographic blocks that are distributed across multiple nodes in a decentralized network. Each block contains a portion of the sensor data along with cryptographic hashes that link it to adjacent blocks, creating a segmented structure that prevents single-point failures and corruption
Solution Approach 2:
Multiple copies of encrypted data blocks are created and distributed across different nodes in the network. These redundant copies ensure data availability and integrity even if some nodes fail or are compromised, as the complete dataset can be reconstructed from remaining copies
4Reliability
If sensor devices store data in memory without encryption, then data access is fast and efficient, but stored data presents a target that can be accessed or manipulated by attackers
Solution Approach 1:
Data is encrypted immediately upon generation or before being written to memory storage. This preliminary encryption ensures that even if memory is compromised or accessed unauthorizedly, the data remains protected as ciphertext that cannot be interpreted without proper cryptographic keys
Data Source
AI summary
Disclosed herein are systems and methods to ensure that data collected from remote sensors sent to cloud-based storage, as well as commands sent to remote actuators from cloud-based control systems remain in a highly encrypted, redundant and resilient form at all times other than in volatile memory (e.g., while in use). Device to device automated sensing and control is also considered and addressed by this focus. Data from industrial sensors requires validation in both the “root of trust” within the sensor/actuator itself to ensure that the data is being transmitted or received from a valid device as well as ensuring that the data has not been manipulated or altered or viewed while in transit.