Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

Security Analysis in Smart Agriculture: Insights from a Cyber-Physical System Application

Smart agriculture modifies traditional farming practices,and offers innovative approaches to boost production and sustainability by leveraging contemporary technologies.In today’s world where technology is everything,these technologies are utilized to streamline regular tasks and procedures in agriculture,one of the largest and most significant industries in every nation.This research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture systems.Divided into three main sections-security analysis,system architecture and design and risk assessment of Cyber-Physical Systems(CPS)applications-the study delves into various elements crucial for smart farming,such as data sources,infrastructure components,communication protocols,and the roles of different stakeholders such as farmers,agricultural scientists and researchers,technology providers,government agencies,consumers and many others.In contrast to earlier research,this work analyzes the resilience of smart agriculture systems using approaches such as threat modeling,penetration testing,and vulnerability assessments.Important discoveries highlight the concerns connected to unsecured communication protocols,possible threats from malevolent actors,and vulnerabilities in IoT devices.Furthermore,the study suggests enhancements for CPS applications,such as strong access controls,intrusion detection systems,and encryption protocols.In addition,risk assessment techniques are applied to prioritize mitigation tactics and detect potential hazards,addressing issues like data breaches,system outages,and automated farming process sabotage.The research sets itself apart even more by presenting a prototype CPS application that makes use of a digital temperature sensor.This application was first created using a Tinkercad simulator and then using actual hardware with Arduino boards.The CPS application’s defenses against potential threats and vulnerabilities are strengthened by this integrated approach,which distinguishes this research for its depth and usefulness in the field of smart agriculture security.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.

Novel cyber-physical collaborative detection and localization method against dynamic load altering attacks in smart energy grids

Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.

3D MERGE与3D SPACE STIR序列在腰椎间盘突出症检查中的应用比较

目的:对比三维多回波恢复梯度回波(3D MERGE)、三维可变反转角快速自旋回波(3D SPACE STIR)序列在腰椎间盘突出症(LDH)检查中的应用效果。方法:选择2020年1月~2022年11月收治的135例LDH患者,回顾性分析患者临床和磁共振成像(MRI)资料,所有患者均接受常规MRI扫描及3D MERGE、3D SPACE STIR序列扫描,对比3D MERGE、3D SPACE STIR序列测量神经根直径的一致性,评价两种序列的图像质量参数[信噪比(SNR)、对比噪声比(CNR)]、图像清晰度评分。结果:3D MERGE和3D SPACE STIR序列测量的L3~S1神经根直径比较差异无统计学意义(P>0.05),且两组序列测量的L3、L4、L5和S1直径均显示出较高相关性(r=0.957,0.986,0.975,0.972,P<0.05);3D MERGE序列的SNR及CNR均高于3D SPACE STIR序列,神经根显示分级、图像清晰度评分优于3D SPACE STIR序列,差异有统计学意义(P<0.05)。结论:3D MERGE、3D SPACE STIR序列在LDH神经根直径测量中具有极高一致性,3D MERGE序列较3D SPACE STIR序列能够更清晰显示神经跟的解剖形态,图像质量更好。

A topology and risk-aware access control framework for cyber-physical space

Cyber-physical space is a spatial environment that integrates the cyber world and the physical world,aiming to provide an intelligent environment for users to conduct their day-to-day activities.The interplay between the cyber space and physical space proposes specific security requirements that are not captured by traditional access control frameworks.On one hand,the security of the physical space and the cyber space should be both concerned in the cyber-physical space.On the other hand,the bad results caused by failure in providing secure policy enforcement may directly affect the controlled physical world.In this paper,we propose an effective access control framework for the cyber-physical space.Firstly,a topology-aware access control(TAAC)model is proposed.It can express the cyber access control,the physical access control,and the interaction access control simultaneously.Secondly,a risk assessment approach is proposed for the policy enforcement phase.It is used to evaluate the user behavior and ensures that the suspicious behaviors executed by authorized users can be handled correctly.Thirdly,we propose a role activation algorithm to ensure that the objects are accessed only by legal and honest users.Finally,we evaluate our approach by using an illustrative example and the performance analysis.The results demonstrate the feasibility of our approach.

Specification and Verification of a Topology-Aware Access Control Model for Cyber-Physical Space

The cyber-physical space is a spatial environment that integrates the cyber and physical worlds to provide an intelligent environment for users to conduct their day-to-day activities. Mobile users and mobile objects are ubiquitous in this space, thereby exerting tremendous pressure on its security model. This model must ensure that both cyber and physical objects are always handled securely in this dynamic environment. In this paper,we propose a systematic solution to be able to specify security policies of the cyber-physical space and ensure that security requirements hold in these policies. We first formulate a topology configuration model to capture the topology characteristics of the cyber and physical worlds. Then, based on this model, a Topology-Aware CyberPhysical Access Control model(TA-CPAC) is proposed, which can ensure the security of the cyber and physical worlds at the same time by adjusting permission assignment dynamically. Then, the topology configuration and TA-CPAC models are formalized by bigraphs and Bigraph Reactive System(BRS), respectively, allowing us to use model checking to rationalize the consequences of the evolution of topological configurations on the satisfaction of security requirements. Finally, a case study on a building automation access control system is conducted to evaluate the effectiveness of the proposed approach.

中国人才政策研究的现状与趋势——基于Cite Space的可视化分析

科学的人才政策是实现人才强国和科教兴国战略的重要保障。借助Cite Space量化分析软件,分别从发文作者、发文机构、高被引文献、关键词等方面对人才政策研究情况进行可视化分析,在整合既有研究基础上展望未来。研究表明:我国人才政策研究主要聚焦于人才政策本身、实施存在的问题、可行性路径三个维度。当前的研究热点主题为人才战略、人才开发、人才培养,已有关键词之间关联性不强,机构合作密度不高,缺少系统研究框架和强大理论支持。据此,今后人才政策的研究应该加强跨学科融合思考,建构具有中国特色的本土化研究架构,注重人才培养的硬环境和软环境建设。

基于Cite Space对螺旋藻藻蓝蛋白的研究进展与热点分析

螺旋藻(Spirulina)藻蓝蛋白具有独特的理化特性及生理功能,是药物、食品和化妆品的天然原料,具有较大的开发潜力。为探讨螺旋藻藻蓝蛋白的研究现状与发展前景,对中国知网和Web of Science数据库中1990—2023年发表的文献进行检索并筛选,使用Cite Space软件对文章发文量、研究团队及研究热点进行图谱分析。综合分析可知,国内年发文量偏少,呈平稳趋势;国外年发文量持续上升,尤其近几年发文量迅速增长,且发文量超过了100篇;国外研究热点集中于藻蓝蛋白在食品、医药行业的应用方面,而国内研究热点集中在提取纯化、稳定性、功能活性的研究与应用,下一步应结合研究现状开发适合规模化生产的提取纯化工艺,进一步加强藻蓝蛋白研究的广度与深度;国内外研究群体主要是高校的相关生物技术学院或研究机构等,总体来讲,学者间存在较为密切的合作,但研究机构间尚未形成紧密的合作关系,在地域上比较分散,各大高校和研究机构应突破地区或机构间的各种限制,促进该研究领域的深度融合和快速发展,深入挖掘藻蓝蛋白在各个领域的潜在应用。

基于CiteSpace的红色文创设计可视化分析与方法研究

目的基于CiteSpace概述国内红色文创设计的发展状况,梳理关于红色文创设计的相关方法与理论模型,探讨未来红色文创设计发展的趋势,为研究者提供相关设计思路与发展动向。方法通过对国内相关文献的研究,梳理了红色文创设计的概念与发展现状,归纳了当前红色文创设计中包括文化转译维度、文化层次理论、叙事性设计的三种主要方法与理论模型。结论目前红色文创设计方法较为单一,很难满足用户的不同需求,且缺乏具体针对性的完整理论体系与设计方法。在今后的红色文创设计中,可以综合运用叙事性及文化转译维度等设计理论和手段,对红色文创设计和方法加以探究和创新,打造具有中国特色的红色文创产品,使红色文化得到更好的普及和弘扬。

基于Cite Space可视化分析我国多发伤急救研究热点及趋势

目的梳理国内多发伤急救相关研究文献,分析研究现状、热点和趋势,为我国多发伤急救研究提供借鉴和指导。方法检索中国知网数据库中2011—2021年关于多发伤急救的相关文献,使用Cite Space 6.1.R3可视化软件对该领域的年发文量、机构、作者、关键词进行分析。结果最终纳入多发伤急救研究文献2519篇,整体发文数量较平稳,以2016年为小高峰;发文量最高的机构是华中科技大学附属同济医院。多发伤急救研究热点包括院前急救、并发症护理、风险因素分析和预后效果评估,研究前沿包括不同多发伤人群的诊断、治疗、手术和护理体会等方面。结论本文通过可视化分析国内多发伤急救研究的热点及趋势,指明了多发伤目前研究存在的问题和未来研究发展的方向,为进一步完善多发伤急救卫生服务和管理体系提供指导。

基于CiteSpace的我国高校公共空间研究热点及趋势分析

文章基于CiteSpace软件对CNKI数据库中相关609篇文献进行可视化分析,发现当前我国关于高校公共空间的研究具有阶段性、各地域间相互独立的特点;研究热点分布于空间扩充、功能拓展、设计优化多个角度,并朝着精细化、人性化、多学科交叉等趋势探索。总结现有研究提出加强地域间机构合作、融合多学科研究视角、引入创新性研究方法等发展方向,以期为新时代我国高校公共空间的研究提供思路和参考。

Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

Stochastic Models to Mitigate Sparse Sensor Attacks in Continuous-Time Non-Linear Cyber-Physical Systems

Cyber-Physical Systems are very vulnerable to sparse sensor attacks.But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely.Therefore,in this paper,we propose a new non-linear generalized model to describe Cyber-Physical Systems.This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and randomeffects in the physical and computationalworlds.Besides,the digitalization stage in hardware devices is represented too.Attackers and most critical sparse sensor attacks are described through a stochastic process.The reconstruction and protectionmechanisms are based on aweighted stochasticmodel.Error probability in data samples is estimated through different indicators commonly employed in non-linear dynamics(such as the Fourier transform,first-return maps,or the probability density function).A decision algorithm calculates the final reconstructed value considering the previous error probability.An experimental validation based on simulation tools and real deployments is also carried out.Both,the new technology performance and scalability are studied.Results prove that the proposed solution protects Cyber-Physical Systems against up to 92%of attacks and perturbations,with a computational delay below 2.5 s.The proposed model shows a linear complexity,as recursive or iterative structures are not employed,just algebraic and probabilistic functions.In conclusion,the new model and reconstructionmechanism can protect successfully Cyber-Physical Systems against sparse sensor attacks,even in dense or pervasive deployments and scenarios.

基于CiteSpace知识图谱的智慧养老领域研究文献综述

“十四五”规划将发展智慧养老产业上升为国家战略高度。文章借助Cite Space和Vosviewer绘图软件对2012-2022年国内外智慧养老领域研究的发文量、突现词等进行可视化分析。发现国内外研究都经历了三个发展阶段,国外研究起步早,研究成果丰富;国内研究虽然起步较晚,但进展快速。总结出“智慧养老内涵”“智慧养老模式”“智慧养老产业”“智慧养老平台”“智慧养老产品”“智慧养老用户”六大国内外都重点关注的研究议题,发现技术赋能智慧养老发展是近年来国内外共同关注的研究热点,大数据、物联网、养老金融、数字技术、区块链等成为围绕智慧养老文献的关键词。

体育教师信念的国际研究现状与趋势——基于CiteSpace的文献计量分析

高质量教师是高质量教育发展的中坚力量。教师信念作为教师专业素养构成的关键要素,对促进教师专业发展、提升教师质量具有重要作用与影响。为借鉴国际体育教师信念研究的成果与经验,促进国内对体育教师信念的研究,研究利用CiteSpace软件,对Web of Science核心合集数据库中1960—2022年的英文文献进行可视化研究。发现:体育教师信念研究高潮出现于2021年,载文数量最多的期刊是Journal of Teaching in Physical Education;研究中心度最高的国家是美国,核心圈层的代表学者是Richards KAR、Kulinna PH和Curtner-smith MD等人;研究热点趋势集中于体力活动促进、职业社会化、批判性教学法、职前体育教师、专业发展等方面。启示:国内未来研究应重点关注体育教师信念对课程改革的影响以及促进职前、职后阶段体育教师信念的发展。

Aquila Optimization with Machine Learning-Based Anomaly Detection Technique in Cyber-Physical Systems

Cyber-physical system(CPS)is a concept that integrates every computer-driven system interacting closely with its physical environment.Internet-of-things(IoT)is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds.Since the complexity level of the CPS increases,an adversary attack becomes possible in several ways.Assuring security is a vital aspect of the CPS environment.Due to the massive surge in the data size,the design of anomaly detection techniques becomes a challenging issue,and domain-specific knowledge can be applied to resolve it.This article develops an Aquila Optimizer with Parameter Tuned Machine Learning Based Anomaly Detection(AOPTML-AD)technique in the CPS environment.The presented AOPTML-AD model intends to recognize and detect abnormal behaviour in the CPS environment.The presented AOPTML-AD framework initially pre-processes the network data by converting them into a compatible format.Besides,the improved Aquila optimization algorithm-based feature selection(IAOA-FS)algorithm is designed to choose an optimal feature subset.Along with that,the chimp optimization algorithm(ChOA)with an adaptive neuro-fuzzy inference system(ANFIS)model can be employed to recognise anomalies in the CPS environment.The ChOA is applied for optimal adjusting of the membership function(MF)indulged in the ANFIS method.The performance validation of the AOPTML-AD algorithm is carried out using the benchmark dataset.The extensive comparative study reported the better performance of the AOPTML-AD technique compared to recent models,with an accuracy of 99.37%.

A Deep CNN-LSTM-Based Feature Extraction for Cyber-Physical System Monitoring

A potential concept that could be effective for multiple applications is a“cyber-physical system”(CPS).The Internet of Things(IoT)has evolved as a research area,presenting new challenges in obtaining valuable data through environmental monitoring.The existing work solely focuses on classifying the audio system of CPS without utilizing feature extraction.This study employs a deep learning method,CNN-LSTM,and two-way feature extraction to classify audio systems within CPS.The primary objective of this system,which is built upon a convolutional neural network(CNN)with Long Short Term Memory(LSTM),is to analyze the vocalization patterns of two different species of anurans.It has been demonstrated that CNNs,when combined with mel-spectrograms for sound analysis,are suitable for classifying ambient noises.Initially,the data is augmented and preprocessed.Next,the mel spectrogram features are extracted through two-way feature extraction.First,Principal Component Analysis(PCA)is utilized for dimensionality reduction,followed by Transfer learning for audio feature extraction.Finally,the classification is performed using the CNN-LSTM process.This methodology can potentially be employed for categorizing various biological acoustic objects and analyzing biodiversity indexes in natural environments,resulting in high classification accuracy.The study highlights that this CNNLSTM approach enables cost-effective and resource-efficient monitoring of large natural regions.The dissemination of updated CNN-LSTM models across distant IoT nodes is facilitated flexibly and dynamically through the utilization of CPS.

基于Cite Space对近5年发酵领域的研究进展与热点分析

近年来,我国生物产业快速发展,且发酵对身体和胃肠道健康具有很多益处,有关微生物发酵的研究逐渐增多。为探讨发酵领域近5年的研究现状与发展前景,对中国知网和Web of Science数据库中2019—2023年发表的文献进行检索并筛选,使用Cite Space软件对文章发文量、研究团队、研究热点进行图谱分析。结果表明,近5年国内发酵领域发文量偏少,年发文量平稳上升;国外发文量较多,年发文量超过100篇,2023年发文量达到200篇;国内外研究群体主要是中医药高校和研究机构;国内外研究热点集中在抗氧化和肠道菌群,国内研究重点为发酵技术,而国外研究范围较广,重点为益生菌的研究;国内外学者间合作较为密切,但研究机构间尚未形成紧密的合作关系。高校和研究机构应突破地区间的限制,促进发酵研究领域的融合。肠道菌群是近5年发酵的研究热点,也是未来发酵研究深入的对象。