4 citations · 5 across the 11 of their papers we have counts for
12 papers
Encrypted collision avoidance maneuver via variational optimization
Yeongjun Jang, Jihoon Suh, Kenshiro Oguri +1
We propose an encrypted collision avoidance maneuver (CAM) design protocol using homomorphic encryption (HE) that enables operators to outsource CAM design to an untrusted server w…
On the invariance of risk-sensitive LQR gain under input randomization
Yeongjun Jang
This paper shows that the optimal gain of the risk-sensitive linear quadratic regulator (LQR) problem is invariant under input randomization when the cost penalizes the realized no…
Variational Encrypted Model Predictive Control
Jihoon Suh, Yeongjun Jang, Junsoo Kim +1
We develop a variational encrypted model predictive control (VEMPC) protocol whose online execution relies only on encrypted polynomial operations. The proposed approach reformulat…
A Distributionally Robust Optimal Control Approach for Differentially Private Dynamical Systems
Yeongjun Jang, Kaoru Teranishi, Junsoo Kim
In this paper, we develop a distributionally robust optimal control approach for differentially private dynamical systems, enabling a plant to securely outsource control computatio…
Inverse Learning-Based Output Feedback Control of Nonlinear Systems with Verifiable Guarantees
Yeongjun Jang, Hamin Chang, Heein Park +3
In this paper, we present a data-driven output feedback controller for nonlinear systems that achieves practical output regulation, using noise-free input/output measurement data.…
Taking Advantage of Rational Canonical Form for Faster Ring-LWE based Encrypted Controller with Recursive Multiplication
Donghyeon Song, Yeongjun Jang, Joowon Lee +1
This paper aims to provide an efficient implementation of encrypted linear dynamic controllers that perform recursive multiplications on a Ring-Learning With Errors (Ring-LWE) base…
Sensor Attack Detection Method for Encrypted State Observers
Yeongjun Jang, Sangwon Lee, Junsoo Kim
This paper proposes an encrypted state observer that is capable of detecting sensor attacks without decryption. We first design a state observer that operates over a finite field o…
Privacy-Preserving Fully Distributed Gaussian Process Regression
Yeongjun Jang, Kaoru Teranishi, Jihoon Suh +1
Although distributed Gaussian process regression (GPR) enables multiple agents to jointly learn a model of the target function, its collaborative nature poses a risk of private dat…
Relative Entropy Regularized Reinforcement Learning for Efficient Encrypted Policy Synthesis
Jihoon Suh, Yeongjun Jang, Kaoru Teranishi +1
We propose an efficient encrypted policy synthesis to develop privacy-preserving model-based reinforcement learning. We first demonstrate that the relative-entropy-regularized rein…
Documentation on Encrypted Dynamic Control Simulation Code using Ring-LWE based Cryptosystems
Yeongjun Jang, Joowon Lee, Junsoo Kim
Encrypted controllers offer secure computation by employing modern cryptosystems to execute control operations directly over encrypted data without decryption. However, incorporati…
Ring-LWE based encrypted controller with unlimited number of recursive multiplications and effect of error growth
Yeongjun Jang, Joowon Lee, Seonhong Min +3
In this paper, we propose an encrypted dynamic controller that executes an unlimited number of recursive homomorphic multiplications on a Ring Learning With Errors (Ring-LWE) based…
A Learning With Errors based encryption scheme for dynamic controllers that discloses residue signal for anomaly detection
Yeongjun Jang, Joowon Lee, Junsoo Kim +2
Although encrypted control systems ensure confidentiality of private data, it is challenging to detect anomalies without the secret key as all signals remain encrypted. To address…