Guest Editors
Professor Qi Liu, Nanjing University of Information Science and Technology, China
Professor Xiaodong Liu, Edinburgh Napier University, UK
Professor Radu Grosu, Vienna University of Technology, Austria
Professor Ching-Nung Yang, National Dong Hwa University, Taiwan
Summary
With the extensive growth of novel hardware and software compositions creating smart, autonomously acting devices in recent years, Cyber Physical Systems (CPS) become attractive enabling efficient end-to-end workflows and new forms of user-machine interaction. On one hand, these CPS applications can provide critical services in various emerging application domains such as energy management, health care, traffic control, industrial measurement and surveillance, etc. performance of internal functionality and processes highly relies on the design and optimization of intelligent models, security algorithms and resilient components due to their heterogeneous, evolving and distributed nature.
Recent advancement of Artificial Intelligence and Cyber Security has been well investigated and applied to CPS systems, but still meets the challenges in a large-scale distributed CPS system. In addition, resilient services are critically required in a CPS to provide "acceptance-level" operational normalcy, e.g. state awareness, disturbance recognition and responses, etc.; nonetheless, existing approaches and tools are only able to support limited resilience in a non-dynamic manner, i.e., fail to consider and respond to a comprehensive profile of run-time situation without needs of the devices and individuals in a CPS. In terms of a large-scale CPS, more issues need to be addressed such as how to securely maintain the resilient services, how to introduce intelligent responses in a CPS based on retrieved and/or recognized run-time states, and so on.
This special issue is intended for researchers, engineers and practitioners from both academia and industry, who are interested in issues on intelligent models, cyber security and resilience in large-scale CPS systems.
Potential topics include but are not limited to:
1. Intelligent Models in a Cyber Physical System
2. Data Security in a Cyber Physical System
3. Service Resilience in a Cyber Physical System
4. Machine Learning for Cyber Security and Privacy Protection in a CPS
5. AI and Deep Learning in an Industrial CPS
6. CPS Data Hiding in Plain- or Cipher-Formats
7. Threat Detection and Reliable Computing in a CPS
8. Industrial CPS and its Transmission Security
9. Perception, Recognition and Resilient Responses in a Large-Scale CPS
10. Process Resilience and Adaptation in a Large-Scale CPS
Keywords
Intelligent Models; Data Security; Service Resilience; Cyber Physical Systems; Machine Learning and Deep Learning; Threat Detection and Reliability; Process Resilience and Adaptation
Published Papers
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Open Access
EDITORIAL
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Open Access
ARTICLE
An Evolutionary Algorithm for Non-Destructive Reverse Engineering of Integrated Circuits
Huan Zhang, Jiliu Zhou, Xi Wu
Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1151-1175, 2021, DOI:10.32604/cmes.2021.015462
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract In hardware Trojan detection technology, destructive reverse engineering can restore an original integrated circuit with the highest accuracy. However, this method has a much higher overhead in terms of time, effort, and cost than bypass detection. This study proposes an algorithm, called mixed-feature gene expression programming, which applies non-destructive reverse engineering to the chip with bypass detection data. It aims to recover the original integrated circuit hardware, or else reveal the unknown circuit design in the chip.
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Open Access
ARTICLE
A Smart Wearable Ring Device for Sensing Hand Tremor of Parkinson’s Patients
Haixia Yang, Yixian Shen, Wei Zhuang, Chunming Gao, Dong Dai, Weigong Zhang
Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1217-1238, 2021, DOI:10.32604/cmes.2021.014558
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Parkinson’s disease (PD) is a very common neurodegenerative disease that occurs mostly in the elderly. There are many main clinical manifestations of PD, such as tremor, bradykinesia, muscle rigidity, etc. Based on the current research on PD, the accurate and convenient detection of early symptoms is the key to detect PD. With the development of microelectronic and sensor technology, it is much easier to measure the barely noticeable tremor in just one hand for the early detection of Parkinson’s disease. In this paper, we present a smart wearable device for detecting hand tremor, in which MPU6050 (MIDI Processing Unit) consisting…
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Open Access
ARTICLE
A Trusted NUMFabric Algorithm for Congestion Price Calculation at the Internet-of-Things Datacenter
Shan Chun, Xiaolong Chen, Guoqiang Deng, Hao Liu
Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1203-1216, 2021, DOI:10.32604/cmes.2021.012230
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information. However, it is difficult to predict the congestion state of the link-end accurately at the source. In this paper, we presented an improved NUMFabric algorithm for calculating the overall congestion price. In the proposed scheme, the whole network structure had been obtained by the central control server in the Software Defined Network, and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.…
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Open Access
ARTICLE
Run-Time Dynamic Resource Adjustment for Mitigating Skew in MapReduce
Zhihong Liu, Shuo Zhang, Yaping Liu, Xiangke Wang, Dong Yin
Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 771-790, 2021, DOI:10.32604/cmes.2021.013244
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract MapReduce is a widely used programming model for large-scale data processing. However, it still suffers from the skew problem, which refers to the case in which load is imbalanced among tasks. This problem can cause a small number of tasks to consume much more time than other tasks, thereby prolonging the total job completion time. Existing solutions to this problem commonly predict the loads of tasks and then rebalance the load among them. However, solutions of this kind often incur high performance overhead due to the load prediction and rebalancing. Moreover, existing solutions target the partitioning skew for reduce tasks,…
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Open Access
ARTICLE
An Anonymous Authentication Scheme with Controllable Linkability for Vehicle Sensor Networks
Yousheng Zhou, Lvjun Chen, Xiaofeng Zhao, Zheng Yang
Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1101-1118, 2020, DOI:10.32604/cmes.2021.013289
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Vehicle sensor networks (VSN) play an increasingly important part
in smart city, due to the interconnectivity of the infrastructure. However
similar to other wireless communications, vehicle sensor networks are susceptible to a broad range of attacks. In addition to ensuring security for
both data-at-rest and data-in-transit, it is essential to preserve the privacy
of data and users in vehicle sensor networks. Many existing authentication
schemes for vehicle sensor networks are generally not designed to also preserve
the privacy between the user and service provider (e.g., mining user data to
provide personalized services without infringing on user privacy). Controllable linkability can…
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Open Access
ARTICLE
Combining Trend-Based Loss with Neural Network for Air Quality Forecasting in Internet of Things
Weiwen Kong, Baowei Wang
Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 849-863, 2020, DOI:10.32604/cmes.2020.012818
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Internet of Things (IoT) is a network that connects things in a
special union. It embeds a physical entity through an intelligent perception
system to obtain information about the component at any time. It connects
various objects. IoT has the ability of information transmission, information
perception,andinformationprocessing.Theairqualityforecastinghasalways
been an urgent problem, which affects people’s quality of life seriously. So
far, many air quality prediction algorithms have been proposed, which can be
mainly classifed into two categories. One is regression-based prediction, the
other is deep learning-based prediction. Regression-based prediction is aimed
to make use of the classical regression algorithm and the various…
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Open Access
ARTICLE
Performance Analysis of Intelligent CR-NOMA Model for Industrial IoT Communications
Yinghua Zhang, Jian Liu, Yunfeng Peng, Yanfang Dong, Changming Zhao
Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 239-257, 2020, DOI:10.32604/cmes.2020.010778
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Aiming for ultra-reliable low-latency wireless communications required
in industrial internet of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal multiple access (CR-NOMA) downlink system. This
system consists of two secondary users (SUs) dynamically interfered by the primary user (PU), and its performance is characterized by the outage probability of
the SU communications. This outage probability is calculated under two conditions where, a) the transmission of PU starts after the channel state information
(CSI) is acquired, so the base station (BS) is oblivious of the interference, and
b) when the BS is aware of the PU interference, and…
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Open Access
ARTICLE
Threshold-Based Adaptive Gaussian Mixture Model Integration (TA-GMMI) Algorithm for Mapping Snow Cover in Mountainous Terrain
Yonghong Zhang, Guangyi Ma, Wei Tian, Jiangeng Wang, Shiwei Chen
Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1149-1165, 2020, DOI:10.32604/cmes.2020.010932
（This article belongs to this Special Issue:
Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Snow cover is an important parameter in the fields of computer modeling, engineering technology and energy development. With the extensive growth of
novel hardware and software compositions creating smart, cyber physical systems’
(CPS) efficient end-to-end workflows. In order to provide accurate snow detection
results for the CPS’s terminal, this paper proposed a snow cover detection algorithm
based on the unsupervised Gaussian mixture model (GMM) for the FY-4A satellite
data. At present, most snow cover detection algorithms mainly utilize the characteristics of the optical spectrum, which is based on the normalized difference snow
index (NDSI) with thresholds in different wavebands. These…
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