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.

Smart Cities as Cyber-Physical Social Systems

The emerging prototype for a Smart City is one of an urban environment with a new generation of inno- vative services for transportation, energy distribution, healthcare, environmental monitoring, business, commerce, emergency response, and social activities. Enabling the technology for such a setting re- quires a viewpoint of Smart Cities as cyber-physical systems （CPSs） that include new software platforms and strict requirements for mobility, security, safety, privacy, and the processing of massive amounts of information. This paper identifies some key defining characteristics of a Smart City, discusses some lessons learned from viewing them as CPSs, and outlines some fundamental research issues that remain largely open.

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.

Cyber-Physical-Social Based Security Architecture for Future Internet of Things

As the Internet of Things (IoT) is emerging as an attractive paradigm, a typical IoT architecture that U2IoT (Unit IoT and Ubiquitous IoT) model has been presented for the future IoT. Based on the U2IoT model, this paper proposes a cyber-physical-social based security architecture (IPM) to deal with Information, Physical, and Management security perspectives, and presents how the architectural abstractions support U2IoT model. In particular, 1) an information security model is established to describe the mapping relations among U2IoT, security layer, and security requirement, in which social layer and additional intelligence and compatibility properties are infused into IPM;2) physical security referring to the external context and inherent infrastructure are inspired by artificial immune algorithms;3) recommended security strategies are suggested for social management control. The proposed IPM combining the cyber world, physical world and human social provides constructive proposal towards the future IoT security and privacy protection.

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral response.Recent studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and hippocampus.Determining how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress psychopathology.In this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of depression.We focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine circuit.We determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic system.Therefore,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

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.

On Zero Dynamics and Controllable Cyber-Attacks in Cyber-Physical Systems and Dynamic Coding Schemes as Their Countermeasures

In this paper, we study stealthy cyber-attacks on actuators of cyber-physical systems(CPS), namely zero dynamics and controllable attacks. In particular, under certain assumptions, we investigate and propose conditions under which one can execute zero dynamics and controllable attacks in the CPS. The above conditions are derived based on the Markov parameters of the CPS and elements of the system observability matrix. Consequently, in addition to outlining the number of required actuators to be attacked, these conditions provide one with the minimum system knowledge needed to perform zero dynamics and controllable cyber-attacks. As a countermeasure against the above stealthy cyber-attacks, we develop a dynamic coding scheme that increases the minimum number of the CPS required actuators to carry out zero dynamics and controllable cyber-attacks to its maximum possible value. It is shown that if at least one secure input channel exists, the proposed dynamic coding scheme can prevent adversaries from executing the zero dynamics and controllable attacks even if they have complete knowledge of the coding system. Finally, two illustrative numerical case studies are provided to demonstrate the effectiveness and capabilities of our derived conditions and proposed methodologies.

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.

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.

Correlation between anxiety, depression, and social stress in young patients with thoracolumbar spine fractures

BACKGROUND Traumatic injuries,such as falling,car accidents,and crushing mostly cause spinal fractures in young and middle-aged people,and>50%of them are thoracolumbar fractures.This kind of fracture is easily combined with serious injuries to peripheral nerves and soft tissues,which causes paralysis of the lower limbs if there is no timely rehabilitation treatment.Young patients with thoracolumbar fractures find it difficult to recover after the operation,and they are prone to depression,low self-esteem,and other negative emotions.AIM To investigate the association between anxiety,depression,and social stress in young patients with thoracolumbar spine fractures and the effect on rehabilitation outcomes.METHODS This study retrospectively analyzed 100 patients admitted to the orthopedic department of Honghui Hospital,Xi’an Jiaotong University who underwent thoracolumbar spine fracture surgery from January 2022 to June 2023.The general data of the patients were assessed with the Hamilton anxiety scale(HAMA),Hamilton depression scale(HAMD),life events scale,and social support rating scale(SSRS)to identify the correlation between anxiety,depression scores,and social stress and social support.The Japanese Orthopedic Association(JOA)was utilized to evaluate the rehabilitation outcomes of the patients and to analyze the effects of anxiety and depression scores on rehabilitation.RESULTS According to the scores of HAMD and HAMA in all patients,the prevalence of depression in patients was 39%(39/100),and the prevalence of anxiety was 49%(49/100).Patients were categorized into non-depression(n=61)and depression(n=39),non-anxiety(n=51),and anxiety(n=49)groups.Statistically significant differences in gender,occupation,Pittsburgh Sleep Quality Index(PSQI)score,and monthly family income were observed between the non-depression and depression groups(P<0.05).A significant difference in occupation and PSQI score was found between the non-anxiety and anxiety groups.Both depression(r=0.207,P=0.038)and anxiety scores(r=0.473,P<0.001)were significantly and positively correlated with negative life events.The difference in negative life event scores as well as SSRS total and item scores was statist-ically significant between patients in the non-depression and depression groups(P<0.05).The difference between the non-anxiety and anxiety groups was statistically significant(P<0.05)in the negative life event scores as well as the total SSRS scores.Additionally,JOA scores were significantly lower in both anxious and depressed patients.CONCLUSION Young patients with thoracolumbar fractures are prone to anxiety and depression.Patients’anxiety and depression are closely associated with social pressure,which reduces the life pressure of young patients with thoracolumbar fractures,enhances social support,and improves the psychology of anxiety and depression.,which affects patients’recovery.

Mediating role of health literacy in the relationship between social isolation and psychological distress among pre-frail older adults

BACKGROUND Frailty has become a significant public health issue.The recent increase in the number of frail older adults has led to increased attention being paid to psycho-logical care services in communities.The social isolation of pre-frail older adults can impact their psychological distress.AIM To explore the mediating effect of health literacy between social isolation and psychological distress among communitydwelling older adults with pre-frailty.METHODS This descriptive cross-sectional study was conducted with 254 pre-frail older individuals aged 60 years and over.Social isolation,health literacy,and psycholo-gical distress were comprehensively measured using the Lubben Social Network Scale-6,12-item Short-Form Health Literacy Questionnaire,and the Kessler Psy-chological Distress Scale-10.Data were evaluated using the SPSS 27.0 package program and the PROCESS macro tool.Descriptive statistical analyses,correlation analyses,and bootstrap mediation tests were used to assess associations between the variables.RESULTS The results showed that social isolation had an effect on health literacy among pre-frail older adults(β=0.240,P<0.001),social isolation impact on psycho-logical distress pre-frail older adults(β=-0.415,P<0.001);health literacy was identified effect on psychological distress among pre-frail older persons(β=-0.307,P<0.001).Health literacy partially mediated the relationship between social isolation and psychological distress among community-dwelling older adults with pre-frailty,with a mediation effect of-0.074,accounting for 17.83%of the total effect.

Social function scores and influencing factors in patients with residual depressive symptoms

BACKGROUND At present,the influencing factors of social function in patients with residual depressive symptoms are still unclear.Residual depressive symptoms are highly harmful,leading to low mood in patients,affecting work and interpersonal communication,increasing the risk of recurrence,and adding to the burden on families.Studying the influencing factors of their social function is of great significance.AIM To explore the social function score and its influencing factors in patients with residual depressive symptoms.METHODS This observational study surveyed patients with residual depressive symptoms(case group)and healthy patients undergoing physical examinations(control group).Participants were admitted between January 2022 and December 2023.Social functioning was assessed using the Sheehan Disability Scale(SDS),and scores were compared between groups.Factors influencing SDS scores in patients with residual depressive symptoms were analyzed by applying multiple linear regression while using the receiver operating characteristic curve,and these RESULTS The SDS scores of the 158 patients with depressive symptoms were 11.48±3.26.Compared with the control group,the SDS scores and all items in the case group were higher.SDS scores were higher in patients with relapse,discon-tinuous medication,drug therapy alone,severe somatic symptoms,obvious residual symptoms,and anxiety scores≥8.Disease history,medication compliance,therapy method,and residual symptoms correlated positively with SDS scores(r=0.354,0.414,0.602,and 0.456,respectively).Independent influencing factors included disease history,medication compliance,therapy method,somatic symptoms,residual symptoms,and anxiety scores(P<0.05).The areas under the curve for predicting social functional impairment using these factors were 0.713,0.559,0.684,0.729,0.668,and 0.628,respectively,with sensitivities of 79.2%,61.8%,76.8%,81.7%,63.6%,and 65.5%and specificities of 83.3%,87.5%,82.6%,83.3%,86.7%,and 92.1%,respectively.CONCLUSION The social function scores of patients with residual symptoms of depression are high.They are affected by disease history,medication compliance,therapy method,degree of somatic symptoms,residual symptoms,and anxiety.

Cyber-physical-social System in Intelligent Transportation

A cyber-physical system (CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels. CPS is helpful to improve the controllability, efficiency and reliability of a physical system, such as vehicle collision avoidance and zero-net energy buildings systems. It has become a hot R&D and practical area from US to EU and other countries. In fact, most of physical systems and their cyber systems are designed, built and used by human beings in the social and natural environments. So, social systems must be of the same importance as their CPSs. The indivisible cyber, physical and social parts constitute the cyber-physical-social system (CPSS), a typical complex system and it's a challengeable problem to control and manage it under traditional theories and methods. An artificial systems, computational experiments and parallel execution (ACP) methodology is introduced based on which data-driven models are applied to social system. Artificial systems, i.e., cyber systems, are applied for the equivalent description of physical-social system (PSS). Computational experiments are applied for control plan validation. And parallel execution finally realizes the stepwise control and management of CPSS. Finally, a CPSS-based intelligent transportation system (ITS) is discussed as a case study, and its architecture, three parts, and application are described in detail. © 2014 Chinese Association of Automation.

Deep Learning Based Attack Detection for Cyber-Physical System Cybersecurity:A Survey

With the booming of cyber attacks and cyber criminals against cyber-physical systems(CPSs),detecting these attacks remains challenging.It might be the worst of times,but it might be the best of times because of opportunities brought by machine learning(ML),in particular deep learning(DL).In general,DL delivers superior performance to ML because of its layered setting and its effective algorithm for extract useful information from training data.DL models are adopted quickly to cyber attacks against CPS systems.In this survey,a holistic view of recently proposed DL solutions is provided to cyber attack detection in the CPS context.A six-step DL driven methodology is provided to summarize and analyze the surveyed literature for applying DL methods to detect cyber attacks against CPS systems.The methodology includes CPS scenario analysis,cyber attack identification,ML problem formulation,DL model customization,data acquisition for training,and performance evaluation.The reviewed works indicate great potential to detect cyber attacks against CPS through DL modules.Moreover,excellent performance is achieved partly because of several highquality datasets that are readily available for public use.Furthermore,challenges,opportunities,and research trends are pointed out for future research.

Blockchain-Assisted Secure Fine-Grained Searchable Encryption for a Cloud-Based Healthcare Cyber-Physical System

The concept of sharing of personal health data over cloud storage in a healthcare-cyber physical system has become popular in recent times as it improves access quality.The privacy of health data can only be preserved by keeping it in an encrypted form,but it affects usability and flexibility in terms of effective search.Attribute-based searchable encryption(ABSE)has proven its worth by providing fine-grained searching capabilities in the shared cloud storage.However,it is not practical to apply this scheme to the devices with limited resources and storage capacity because a typical ABSE involves serious computations.In a healthcare cloud-based cyber-physical system(CCPS),the data is often collected by resource-constraint devices;therefore,here also,we cannot directly apply ABSE schemes.In the proposed work,the inherent computational cost of the ABSE scheme is managed by executing the computationally intensive tasks of a typical ABSE scheme on the blockchain network.Thus,it makes the proposed scheme suitable for online storage and retrieval of personal health data in a typical CCPS.With the assistance of blockchain technology,the proposed scheme offers two main benefits.First,it is free from a trusted authority,which makes it genuinely decentralized and free from a single point of failure.Second,it is computationally efficient because the computational load is now distributed among the consensus nodes in the blockchain network.Specifically,the task of initializing the system,which is considered the most computationally intensive,and the task of partial search token generation,which is considered as the most frequent operation,is now the responsibility of the consensus nodes.This eliminates the need of the trusted authority and reduces the burden of data users,respectively.Further,in comparison to existing decentralized fine-grained searchable encryption schemes,the proposed scheme has achieved a significant reduction in storage and computational cost for the secret key associated with users.It has been verified both theoretically and practically in the performance analysis section.

Cyber-Physical Production Systems for Data-Driven,Decentralized,and Secure Manufacturing-A Perspective

With the concepts of Industry 4.0 and smart manufacturing gaining popularity,there is a growing notion that conventional manufacturing will witness a transition toward a new paradigm,targeting innovation,automation,better response to customer needs,and intelligent systems.Within this context,this review focuses on the concept of cyber–physical production system(CPPS)and presents a holistic perspective on the role of the CPPS in three key and essential drivers of this transformation:data-driven manufacturing,decentralized manufacturing,and integrated blockchains for data security.The paper aims to connect these three aspects of smart manufacturing and proposes that through the application of data-driven modeling,CPPS will aid in transforming manufacturing to become more intuitive and automated.In turn,automated manufacturing will pave the way for the decentralization of manufacturing.Layering blockchain technologies on top of CPPS will ensure the reliability and security of data sharing and integration across decentralized systems.Each of these claims is supported by relevant case studies recently published in the literature and from the industry;a brief on existing challenges and the way forward is also provided.

Challenges and Requirements for the Application of Industry 4.0:A Special Insight with the Usage of Cyber-Physical System

Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.

A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach

In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucial for the vehicle design and safe control.However,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of autonomy.In this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified units.These techniques are utilized to obtain more accurate model for brake pressure state estimation applications.The proposed model is trained using real experimental training data which were collected via conducting real vehicle testing.The vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving cycles.Based on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated accordingly.The results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa.

Analysis of cascading failures of power cyber-physical systems considering false data injection attacks

This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system,and identifies vulnerable nodes.First,considering the monitoring and control functions of a cyber network and power flow characteristics of a power network,a power cyber-physical system model is established.Then,the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied,and a cascading failure analysis process is proposed for the cyber-attack environment.In addition,a vulnerability evaluation index is defined from two perspectives,i.e.,the topology integrity and power network operation characteristics.Moreover,the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyberphysical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index.Finally,an IEEE14-bus power network is selected for constructing a power cyber-physical system.Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks,which affect the ability of the cyber network to suppress the propagation of cascading failures,and expand the scale of the cascading failures.The vulnerability evaluation index is calculated for each node,so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.