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Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization
- Source :
- IEEE Control Systems Letters, 7, 395-400. IEEE
- Publication Year :
- 2023
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2023.
-
Abstract
- Recent developments in communication technologies, such as 5G, together with innovative computing paradigms, such as edge computing, provide further possibilities for the implementation of real-time networked control systems. However, privacy and cyber-security concerns arise when sharing private data between sensors, agents and a third-party computing facility. In this paper, a secure version of the distributed formation control is presented, analyzed and simulated, where gradient-based formation control law is implemented in the edge, with sensor and actuator information being secured by fully homomorphic encryption method based on learning with error (FHE-LWE) combined with a proposed mixed uniform-logarithmic quantizer (MULQ). The novel quantizer is shown to be suitable for realizing secure control systems with FHE-LWE where the critical real-time information can be quantized into a prescribed bounded space of plaintext while satisfying a sector bound condition whose lower and upper-bound can be made sufficiently close to an identity. An absolute stability analysis is presented, that shows the asymptotic stability of the closed-loop secure control system.
- Subjects :
- Control and Optimization
Optimization and Control (math.OC)
Control and Systems Engineering
FOS: Electrical engineering, electronic engineering, information engineering
FOS: Mathematics
Systems and Control (eess.SY)
Electrical Engineering and Systems Science - Systems and Control
Mathematics - Optimization and Control
Computer Science::Cryptography and Security
Subjects
Details
- ISSN :
- 24751456
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Control Systems Letters
- Accession number :
- edsair.doi.dedup.....a2b2c184772d50fada314175da8d95dd