IEEE Transactions on Automatic Control · 2022 · 63 citations · 13 references
ComputingComputer EngineeringComputer ScienceComputer SecurityCryptographyDynamical SystemsData EncryptionHomomorphic EncryptionClosed-loop StabilityLearning With Errors ProblemLinear Time-invariant SystemsLoop StabilityState Transition Matrix
In this article, we present a dynamic feedback controller that computes the next state and the control signal over encrypted data using homomorphic properties of cryptosystems, whose performance is equivalent to the linear dynamic controllers over real-valued data. Assuming that the input as well as the output of the plant is encrypted and transmitted back to the controller, it is shown that the state matrix of any linear time-invariant controller can be always converted to a matrix of integer components. This allows the dynamic feedback controller to operate for infinite time horizon without decryption or reset of its internal state. For implementation in practice, we illustrate the use of a cryptosystem that is based on the Learning With Errors problem, which allows both multiplication and addition over encrypted data. It is also shown that the effect of injected random numbers during encryption for security can be maintained within a small bound by way of the closed-loop stability.
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Fully homomorphic encryption using ideal lattices
Craig Gentry · 2009 · 6.6K citations
On lattices, learning with errors, random linear codes, and cryptography
Oded Regev · Journal of the ACM · 2009 · 2.2K citations