Opacity is an important information-flow security property which characterizes the plausible deniability of certain “secret behaviors” in dynamical systems. In this paper, we study the problem of synthesizing contro...
Opacity is an important information-flow security property which characterizes the plausible deniability of certain “secret behaviors” in dynamical systems. In this paper, we study the problem of synthesizing controllers enforcing a notion of opacity over discrete-time control systems with continuous state sets. In this paper, we develop an abstraction-based approach to tackle the controller synthesis problem. Specifically, we adopt a notion of approximate opacity which is suitable for continuous-space control systems. We propose a notion of approximate initial-state opacity preserving alternating simulation relation which characterizes the closeness between two systems in terms of opacity preservation. We show that, based on this new notion of system relation, one can synthesize an opacity-enforcing controller for the abstract system which is finite and then refine it back to enforce opacity over the original control system. Finally, we present a method for constructing opacity-preserving finite abstractions for discrete-time control systems under some stability properties. Our results are illustrated on a two-room temperature control problem.
In recent years,there are numerous studies on chaotic systems with special equilibrium curves having various shapes such as circle,butterfly,heart and *** paper describes a new 3-D chaotic dynamical system with a caps...
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In recent years,there are numerous studies on chaotic systems with special equilibrium curves having various shapes such as circle,butterfly,heart and *** paper describes a new 3-D chaotic dynamical system with a capsule-shaped equilibrium *** proposed chaotic system has two quadratic,two cubic and two quartic nonlinear *** is noted that the proposed chaotic system has a hidden attractor since it has an infinite number of equilibrium *** is also established that the proposed chaotic system exhibits multi-stability with two coexisting chaotic attractors for the same parameter values but differential initial states.A detailed bifurcation analysis with respect to variations in the system parameters is portrayed for the new chaotic system with capsule equilibrium *** have shown MATLAB plots to illustrate the capsule equilibrium curve,phase orbits of the new chaotic system,bifurcation diagrams and *** an engineering application,we have proposed a speech cryptosystem with a numerical algorithm,which is based on our novel 3-D chaotic system with a capsule-shaped equilibrium *** proposed speech cryptosystem follows its security evolution and implementation on Field Programmable Gate Array(FPGA)*** results show that the proposed encryption system utilizes 33%of the FPGA,while the maximum clock frequency is 178.28 MHz.
A recently proposed fully passive quantum key distribution (QKD) removes all source modulator side channels. In this work, we combine fully passive sources with measurement-device-independent (MDI) QKD to simultaneous...
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A recently proposed fully passive quantum key distribution (QKD) removes all source modulator side channels. In this work, we combine fully passive sources with measurement-device-independent (MDI) QKD to simultaneously remove side channels from source modulators and detectors. We show a numerical simulation of passive MDI QKD, and we obtain an acceptable key rate while achieving much better implementation security, as well as ease of implementation, compared with a recently proposed fully passive twin-field QKD, paving the way towards more secure and practical QKD systems. We prove that a fully passive protocol is compatible with MDI QKD and we propose a novel idea that can improve the sifting efficiency.
Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the f...
Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.
Adaptive robotics plays an essential role in achieving truly co-creative cyber physical systems. In robotic manipulation tasks, one of the biggest challenges is to estimate the pose of given workpieces. Even though th...
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Adaptive robotics plays an essential role in achieving truly co-creative cyber physical systems. In robotic manipulation tasks, one of the biggest challenges is to estimate the pose of given workpieces. Even though the recent deep-learning-based models show promising results, they require an immense dataset for training. In this paper, two vision-based, multi-object grasp pose estimation models (MOGPE), the MOGPE Real-Time and the MOGPE High-Precision are proposed. Furthermore, a sim2real method based on domain randomization to diminish the reality gap and overcome the data shortage. Our methods yielded an 80% and a 96.67% success rate in a real-world robotic pick-and-place experiment, with the MOGPE Real-Time and the MOGPE High-Precision model respectively. Our framework provides an industrial tool for fast data generation and model training and requires minimal domain-specific data.
K-SVD (K-Singular Value Decomposition)is a com-monly used dictionary learning method that progressively opti-mizes dictionaries to better represent data by iterating sparse coding and dictionary update steps. However,...
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ISBN:
(数字)9798331511074
ISBN:
(纸本)9798331511081
K-SVD (K-Singular Value Decomposition)is a com-monly used dictionary learning method that progressively opti-mizes dictionaries to better represent data by iterating sparse coding and dictionary update steps. However, with the increasing data size, the traditional K -SVD method faces significant challenges in terms of computational efficiency. Therefore, this paper proposes an asynchronous distributed parallel K-SVD method based on Ray framework to cope with the computational efficiency problem in large-scale data processing. This method achieves efficient parallel computation by decomposing the sparse coding and dictionary updating steps of the K-SVD method into multiple independent tasks and utilizing the distributed scheduling capability of the Ray framework. Since the zero elements of the coefficient matrix are unevenly distributed, we introduce a stride partitioning approach when performing the decomposition. In addition, in order to avoid the method falling into local optima and failing to find global optima due to parallelism, this paper synchronizes with the global at the same time as the atomic update of the dictionary. Meanwhile, for the purpose of avoiding the overhead caused by data synchronization, a parameter server is introduced to realize asynchronous updating of dictionary and coefficient matrix to reduce the overhead caused by communication. The experimental results show that, compared with the traditional K-SVD method, the method proposed in this paper has a significant advantage in computational efficiency and is able to efficiently process hyperspectral image datasets under the premise of guaranteeing the sparse representation accuracy. Compared with the synchronous parallel K-SVD method, the proposed method has faster error convergence and does not fall into local optima.
We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challe...
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In the study of hydraulic seepage prediction, it is often necessary to target multiple feature dimensions. In this paper, a variety of traditional machine learning algorithms based on stepwise regression filtering fea...
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In pursuit-evasion the objective of the pursuer is to capture the evader. In this work, the faster pursuer is modeled to have limited range and therefore optimal strategies for the pursuer and evader change. Depending...
In pursuit-evasion the objective of the pursuer is to capture the evader. In this work, the faster pursuer is modeled to have limited range and therefore optimal strategies for the pursuer and evader change. Depending upon the range limits of the pursuer the evader may evade capture by the pursuer. This paper describes the optimal strategies and nuances that appear for point-capture or when the pursuer is endowed with a non-zero capture radius.
This research involves the description of the newly developed acoustic communication system that can improve high data rates in the underwater channel. The problems in the conventional underwater communication techniq...
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