scholarly journals Investigation of the Required Discreteness of Interpolation Movement Parameters in Cyber-physical Systems

2021 ◽  
Author(s):  
Volodymyr Kombarov ◽  
Yevgen Tsegelnyk ◽  
Sergiy Plankovskyy ◽  
Yevhen Aksonov ◽  
Yevhen Kryzhyvets
Keyword(s):  
Data Processing ◽  
High Speed ◽  
Internal Representation ◽  
Cyber Physical Systems ◽  
High Speed Machining ◽  
Cnc System ◽  
Physical Systems ◽  
System Equations ◽  
And Performance ◽  
Movement Parameters

Improving the accuracy, reliability, and performance of cyber-physical systems such as high-speed machining, laser cutting, welding and cladding etc. is one of the most pressing challenges in modern industry. CNC system carries out data processing and significantly affect on accuracy of operation such equipment. The paper considers the problem of controlled axes motion differential characteristics data processing in the internal representation of the discrete space of the CNC system. Equations for determining the required discreteness of the differential characteristics position and resolution, such as the speed, acceleration, and jerk are proposed. For the most widely used CNC equipment specific discreteness and resolution values have been determined.

scholarly journals Accelerating privacy-preserving momentum federated learning for industrial cyber-physical systems

2021 ◽  
Author(s):  
Linlin Zhang ◽  
Zehui Zhang ◽  
Cong Guan
Keyword(s):  
Convergence Rate ◽  
Performance Improvement ◽  
Gradient Descent ◽  
Homomorphic Encryption ◽  
Cyber Physical Systems ◽  
Privacy Preserving ◽  
Fully Homomorphic Encryption ◽  
Physical Systems ◽  
Cloud Server ◽  
And Performance

AbstractFederated learning (FL) is a distributed learning approach, which allows the distributed computing nodes to collaboratively develop a global model while keeping their data locally. However, the issues of privacy-preserving and performance improvement hinder the applications of the FL in the industrial cyber-physical systems (ICPSs). In this work, we propose a privacy-preserving momentum FL approach, named PMFL, which uses the momentum term to accelerate the model convergence rate during the training process. Furthermore, a fully homomorphic encryption scheme CKKS is adopted to encrypt the gradient parameters of the industrial agents’ models for preserving their local privacy information. In particular, the cloud server calculates the global encrypted momentum term by utilizing the encrypted gradients based on the momentum gradient descent optimization algorithm (MGD). The performance of the proposed PMFL is evaluated on two common deep learning datasets, i.e., MNIST and Fashion-MNIST. Theoretical analysis and experiment results confirm that the proposed approach can improve the convergence rate while preserving the privacy information of the industrial agents.

Stability and Control of Tooling System for High-Speed Machining

2014 ◽  
Vol 684 ◽  
pp. 375-380
Author(s):  
Deng Sheng Zheng ◽  
Jian Chen ◽  
D.F. Tao ◽  
L. Lv ◽  
Gui Cheng Wang
Keyword(s):  
Natural Frequency ◽  
High Speed ◽  
System Stability ◽  
Finite Model ◽  
High Speed Machining ◽  
Cnc Machine ◽  
And Performance ◽  
The Stability ◽  
Tooling System ◽  
And Control

Tooling system for high-speed machining is one of the key components of high-end CNC machine , its stability and reliability directly affects the quality and performance of the machine. Based on the finite element method, developing a 3D finite model of high-speed machining tool system, studying on the stability of the high Speed machining tool from the natural frequency by the method of modal analysis. Analysis the amount of the overhang and clamping of the tooling , different shank taper interference fit and under different speed conditions, which affects the natural frequency of high-speed machining tool system. Proposed to the approach of improving system stability, which also provides a theoretical basis for the development of new high-speed machining tool system.

scholarly journals SNPL: One Scheme of Securing Nodes in IoT Perception Layer

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1090 ◽  
Author(s):  
Yongkai Fan ◽  
Guanqun Zhao ◽  
Kuan-Ching Li ◽  
Bin Zhang ◽  
Gang Tan ◽  
...  
Keyword(s):  
Cyber Physical Systems ◽  
Security Risk ◽  
Practical Application ◽  
Malicious Nodes ◽  
Physical Systems ◽  
Security Scheme ◽  
Performance Requirements ◽  
Different Types ◽  
Series Of Experiments ◽  
And Performance

The trustworthiness of data is vital data analysis in the age of big data. In cyber-physical systems, most data is collected by sensors. With the increase of sensors as Internet of Things (IoT) nodes in the network, the security risk of data tampering, unauthorized access, false identify, and others are overgrowing because of vulnerable nodes, which leads to the great economic and social loss. This paper proposes a security scheme, Securing Nodes in IoT Perception Layer (SNPL), for protecting nodes in the perception layer. The SNPL is constructed by novel lightweight algorithms to ensure security and satisfy performance requirements, as well as safety technologies to provide security isolation for sensitive operations. A series of experiments with different types and numbers of nodes are presented. Experimental results and performance analysis show that SNPL is efficient and effective at protecting IoT from faulty or malicious nodes. Some potential practical application scenarios are also discussed to motivate the implementation of the proposed scheme in the real world.

Design Space Exploration for Secure IoT Devices and Cyber-Physical Systems

2021 ◽  
Vol 20 (4) ◽  
pp. 1-24
Author(s):  
Lukas Gressl ◽  
Christian Steger ◽  
Ulrich Neffe
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Cyber Physical Systems ◽  
Embedded Devices ◽  
Daily Lives ◽  
System Designer ◽  
Physical Systems ◽  
Network Availability ◽  
And Performance

With the advent of the Internet of Things (IoT) and Cyber-Physical Systems (CPS), embedded devices have been gaining importance in our daily lives, as well as industrial processes. Independent of their usage, be it within an IoT system or a CPS, embedded devices are always an attractive target for security attacks, mainly due to their continuous network availability and the importance of the data they handle. Thus, the design of such systems requires a thorough consideration of the various security constraints they are liable to. Introducing these security constraints, next to other requirements, such as power consumption, and performance increases the number of design choices a system designer must consider. As the various constraints are often conflicting with each other, designers face the complex task of balancing them. System designers facilitate Design Space Exploration (DSE) tools to support a system designer in this job. However, available DSE tools only offer a limited way of considering security constraints during the design process. In this article, we introduce a novel DSE framework, which allows the consideration of security constraints, in the form of attack scenarios, and attack mitigations in the form of security tasks. Based on the descriptions of the system’s functionality and architecture, possible attacks, and known mitigation techniques, the framework finds the optimal design for a secure IoT device or CPS. Our framework’s functionality and its benefits are shown based on the design of a secure sensor system.

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