Medical Cyber-physical Systems Research Articles

Modeling R^3 Needle Steering in Uppaal

Medical cyber-physical systems are safety-critical, and as such, require ongoing verification of their correct behavior, as system failure during run time may cause severe (or even fatal) personal damage. However, creating a verifiable model often conflicts with other application requirements, most notably regarding data precision and model accuracy, as efficient model checking promotes discrete data (over continuous) and abstract models to reduce the state space. In this paper, we approach the task of medical needle steering in soft tissue around potential obstacles. We design a verifiable model of needle motion (implemented in Uppaal Stratego) and a framework embedding the model for online needle steering. We mitigate the conflict by imposing boundedness on both the data types, reducing from R^3 to Z^3 when needed, and the motion and environment models, reducing the set of allowed local actions and global paths. In experiments, we successfully apply the static model alone, as well as the dynamic framework in scenarios with varying environment complexity and both a virtual and real needle setting, where up to 100% of targets were reached depending on the scenario and needle.

Blockchain-Based Digital Twins Collaboration for Smart Pandemic Alerting: Decentralized COVID-19 Pandemic Alerting Use Case.

Emerging technologies such as digital twins, blockchain, Internet of Things (IoT), and Artificial Intelligence (AI) play a vital role in driving the industrial revolution in all domains, including the healthcare sector. As a result of COVID-19 pandemic outbreak, there is a significant need for medical cyber-physical systems to adopt these emerging technologies to combat COVID-19 paramedic crisis. Also, acquiring secure real-time data exchange and analysis across multiple participants is essential to support the efforts against COVID-19. Therefore, we have introduced a blockchain-based collaborative digital twins framework for decentralized epidemic alerting to combat COVID-19 and any future pandemics. The framework has been proposed to bring together the existing advanced technologies (i.e., blockchain, digital twins, and AI) and then provide a solution to decentralize epidemic alerting to combat COVID-19 outbreaks. Also, we have described how the conceptual framework can be applied in the decentralized COVID-19 pandemic alerting use case.

Lightweight Certificateless Privacy-Preserving Integrity Verification with Conditional Anonymity for Cloud-Assisted Medical Cyber-Physical Systems

Lightweight Certificateless Privacy-Preserving Integrity Verification with Conditional Anonymity for Cloud-Assisted Medical Cyber-Physical Systems

Assessing the Human Condition in Medical Cyber-Physical System Based on Microservices Architecture

The goal of the work is to propose architectural and information model for assessing the human condition on the basis of microservice architecture in medical cyber-physical system, which, in contrast to the known models for assessing the human condition, can simultaneously provide scaling, fault tolerance and increase the speed of human condition assessment. The theoretical substantiation and the new decision of an actual scientific problem of development and research means of an estimation of a human condition in medical cyber-physical system have been considered. These means involve the parallel processing of data on vital signs of the human condition, organizing the means of information processing into separate independent logical elements — microservices, in comparison with other existing medical cyber-physical systems. An architectural model based on microservice architecture has been proposed.

A new approach for task managing in the fog-based medical cyber-physical systems using a hybrid algorithm

PurposeThis paper aims to offer a hybrid genetic algorithm and the ant colony optimization (GA-ACO) algorithm for task mapping and resource management. The paper aims to reduce the makespan and total response time in fog computing- medical cyber-physical system (FC-MCPS).Design/methodology/approachSwift progress in today’s medical technologies has resulted in a new kind of health-care tool and therapy techniques like the MCPS. The MCPS is a smart and reliable mechanism of entrenched clinical equipment applied to check and manage the patients’ physiological condition. However, the extensive-delay connections among cloud data centers and medical devices are so problematic. FC has been introduced to handle these problems. It includes a group of near-user edge tools named fog points that are collaborating until executing the processing tasks, such as running applications, reducing the utilization of a momentous bulk of data and distributing the messages. Task mapping is a challenging problem for managing fog-based MCPS. As mapping is an non-deterministic pol ynomial-time-hard optimization issue, this paper has proposed a procedure depending on the hybrid GA-ACO to solve this problem in FC-MCPS. ACO and GA, that is applied in their standard formulation and combined as hybrid meta-heuristics to solve the problem. As such ACO-GA is a hybrid meta-heuristic using ACO as the main approach and GA as the local search. GA-ACO is a memetic algorithm using GA as the main approach and ACO as local search.FindingsMATLAB is used to simulate the proposed method and compare it to the ACO and MACO algorithms. The experimental results have validated the improvement in makespan, which makes the method a suitable one for use in medical and real-time systems.Research limitations/implicationsThe proposed method can achieve task mapping in FC-MCPS by attaining high efficiency, which is very significant in practice.Practical implicationsThe proposed approach can achieve the goal of task scheduling in FC-MCPS by attaining the highest total computational efficiency, which is very significant in practice.Originality/valueThis research proposes a GA-ACO algorithm to solve the task mapping in FC-MCPS. It is the most significant originality of the paper.

Data Access Control Based on Blockchain in Medical Cyber Physical Systems

The current medical cyber physical systems involve a wide range of institutions and a large number of participants. Data sharing among distributed medical institutions is already a development trend. However, the security is worrying; e.g., the access to medical data lacks uniformity and standardization. What is more, data is easy to be tampered with and leaked. This has a very negative impact on the medical industry. Therefore, a strict and reliable access control mechanism for data in the medical cyber physical systems is a prerequisite for ensuring the implementation of modern medical functions. We deal with how to design effective access control in medical cyber physical systems. Combined with blockchain technology, we design the medical cyber physical systems based on blockchain data access control mechanism and unite data in the chain of union Fabric network resources access control. We qualitatively classify medical data, define the weight level of different data, design a medical data access framework based on blockchain, build an applicable model, formulate access control strategy, and specify the role assignment and access task matching of users, so as to achieve secure and effective data access control. The Hyperledger Fabric network is established as the alliance chain for managing access control rights distribution through smart contracts so as to achieve case-based medical data access control under the blockchain.

Blockchain-Based Efficient Device Authentication Protocol for Medical Cyber-Physical Systems

As the background of application in the field of smart health care, the flexible interaction between patients and medical system is provided by medical cyber-physical systems (MCPSs) to realize all-round three-dimensional medical service. According to the controllable and credible requirements of MCPS, it needs a secure and reliable device identity authentication mechanism to build the security barrier. Based on the blockchain technology, a lightweight authentication scheme is designed for sensor/execution devices, users, and gateway nodes in MCPS. The security analysis and experimental results show that the scheme can resist the existing attacks with better efficiency; thus, our proposed scheme can be efficiently applied to the medical field.

Security preservation in industrial medical CPS using Chebyshev map: An AI approach

Cyber–Physical System (CPS) are widely used in various areas such as industrial manufacturing, telemedicine and energy, etc. Specifically, industrial medical CPS utilizes various medical devices connected to the network to realize real-time management and treatment of patient. However, the underlying wireless channel makes industrial medical CPS vulnerable to external attacks, which may leak patient privacy and even threaten patients’ lives. Besides, most of the authentication schemes are not suitable for real-time applications such as medical CPS due to the latency. Hence, the artificial intelligence (AI) techniques can be useful in this environment to cater to the aforementioned challenges. It necessitates constructing a secure and lightweight authentication protocol to prevent the unauthorized access and control of medical devices. Traditional authentication schemes adopt a password-based or smartcard to validate the authenticity of users, which may suffer from password guessing or smartcard lost attack. However, the AI-assisted biometrics technique can effectively resist the aforementioned attacks. Therefore, an AI-assisted lightweight authentication protocol for real-time access using a Chebyshev map in industrial medical CPS is designed in this paper, which is robust and resolve security and privacy issues. The proposed protocol is capable of resisting various known attacks through security analysis. The proposed protocol has less computational overhead with a slight increase in communication overhead. Also, the proposed protocol supports stringent security features and functionalities compared to other existing protocols.

A new enhanced cyber security framework for medical cyber physical systems

A new enhanced cyber security framework for medical cyber physical systems

AARIN: Affordable, accurate, reliable and innovative mechanism to protect a medical cyber-physical system using blockchain technology

The enhancement (in the past decade) in electronics devices/technology, a rise in most of the accidents concerning security and surveillance intruding the private lives of the users question the existing systems being used to combat this challenge wherein, the third-parties gather and handle large amounts of individual details. As part of the constant evolution of the cyber physical system architecture, one of the goals of our system is to reduce the latency time for enrollment of new information. Generally, the efficiency and benefit of a Cyber Physical Systems (CPS) depends heavily on interconnection of individual devices or nodes. Exchange of data and information relevant to an overall task or functionality is the key to many applications such as smart grids, smart cities, and many others. Trustworthiness of data is needed to make such systems (especially in MCPS systems) successful. To be able to fulfill policies to guarantee the safety of all entities within a Medical Cyber Physical Systems (MCPS) and to provide security measures to enforce these cryptographic solutions have to be embedded. This paper describes a decentralized e-healthcare application framework for personal data management that ensures that users own and access their data. This work proposes a novel mechanism to secure Medical Cyber Physical Systems (MCPS), i.e., as an automated access-control manager (including building trust in a third party). This work also integrates some features in security building blocks in ultra-small devices to provide essential properties to secure embedded systems.

Towards efficient federated learning‐based scheme in medical cyber‐physical systems for distributed data

SummaryIn recent years, Cyber‐Physical Systems (CPS) and Artificial Intelligence (AI) have made good progress in the medical field. The medical CPS (MCPS) based on AI can realize the efficient and reasonable utilization of medical resources and improve the quality of medical process. However, current MCPS are still facing several challenges, and the privacy protection of medical data is one of the most critical challenges. Since medical data is stored in different hospitals, most studies collect data from decentralized hospitals to train a disease diagnosis model, which is not conducive to the privacy protection of patients. And in some existing solutions, it is also difficult for doctors to select the optimal model from multiple models in clinical diagnosis. In this paper, we propose a novel scheme based on federated learning in MCPS for training disease diagnosis models from distributed medical image data. Our scheme is divided into three parts: the model provider, the server, and the consumer, and a detailed working process is designed for each part. This scheme can not only effectively solve the problem of privacy protection, but also solve the problem of model selection for doctors and save storage space. It can ensure that consumers automatically get a steadily improved disease diagnosis model. This scheme is performed on simulated distributed medical image datasets. The experimental results show the effectiveness and superiority of our scheme.

Lightweight Misbehavior Detection Management of Embedded IoT Devices in Medical Cyber Physical Systems

We propose a lightweight specification-based misbehavior detection management technique to efficiently and effectively detect misbehavior of an IoT device embedded in a medical cyber physical system through automatic model checking and formal verification. We verify our specification-based misbehavior detection technique with a patient-controlled analgesia (PCA) device embedded in a medical health monitoring system. Through extensive ns3 simulation, we verify its superior performance over popular machine learning anomaly detection methods based on support vector machine (SVM) and k-nearest neighbors (KNN) techniques in both effectiveness and efficiency performance metrics.

Controlled BTG: Toward Flexible Emergency Override in Interoperable Medical Systems

INTRODUCTION: In medical cyber-physical systems (mCPS), availability must be prioritized over other security properties, making it challenging to craft least-privilege authorization policies which preserve patient safety and confidentiality even during emergency situations. For example, unauthoriz

A constraint and risk-aware approach to attribute-based access control for cyber-physical systems

Cyber-physical systems (CPSs) integrate cyber components and physical processes. This integration enhances the capabilities of physical systems by incorporating intelligence into objects and services. On the other hand, the integration of cyber and physical components and the interaction between them introduce new security threats. Since CPSs are mostly safety-critical systems, data stored and communicated in them are highly critical. Hence, there is a crucial need for protecting the data and resources in CPSs against unauthorized accesses. In this paper, we propose an access control (AC) framework to address CPS related security issues. The proposed framework consists of two parts: a Cyber-Physical Access Control model (CPAC) and a Generalized Action Generation Model (GAGM). CPAC utilizes an attribute-based approach and extends it with cyber-physical components and cyber-physical interactions. In addition, we incorporate Separation of Duty (SoD) constraints into the CPAC model. GAGM is used to augment the enforcement of access policies. We present formal representations of CPAC and GAGM and demonstrate their use in a sample scenario for a medical CPS. We propose an algorithm for enforcing authorization policies. We implement the CPAC model and compare its performance against the core attribute-based access control model. We present an authorization enforcement approach and show through our experimental results its feasibility.

Efficient NTRU Lattice-Based Certificateless Signature Scheme for Medical Cyber-Physical Systems.

An electronic health (e-health) system, such as a medical cyber-physical system, offers a number of benefits (e.g. inform medical diagnosis). There are, however, a number of considerations in the implementation of the medical cyber-physical system, such as the integrity of medical / healthcare data (e.g. manipulated data can result in misdiagnosis). A number of digital signature schemes have been proposed in recent years to mitigate some of these challenges. However, the security of existing signatures is mostly based on conventional difficult mathematical problems, which are known to be insecure against quantum attacks. In this paper, we propose a certificateless signature scheme, based on NTRU lattice. The latter is based on the difficulty of small integer solutions on the NTRU lattice, and is known to be quantum attack resilience. Security analysis and performance evaluations demonstrate that our proposed scheme achieves significantly reduced communication and computation costs in comparison to two other competing quantum resilience schemes, while being quantum attack resilience.

An Efficient Certificateless Aggregate Signature Scheme for Blockchain-Based Medical Cyber Physical Systems.

Different from the traditional healthcare field, Medical Cyber Physical Systems (MCPS) rely more on wireless wearable devices and medical applications to provide better medical services. The secure storage and sharing of medical data are facing great challenges. Blockchain technology with decentralization, security, credibility and tamper-proof is an effective way to solve this problem. However, capacity limitation is one of the main reasons affecting the improvement of blockchain performance. Certificateless aggregation signature schemes can greatly tackle the difficulty of blockchain expansion. In this paper, we describe a two-layer system model in which medical records are stored off-blockchain and shared on-blockchain. Furthermore, a multi-trapdoor hash function is proposed. Based on the proposed multi-trapdoor hash function, we present a certificateless aggregate signature scheme for blockchain-based MCPS. The purpose is to realize the authentication of related medical staffs, medical equipment, and medical apps, ensure the integrity of medical records, and support the secure storage and sharing of medical information. The proposed scheme is highly computationally efficient because it does not use bilinear maps and exponential operations. Many certificateless aggregate signature schemes without bilinear maps in Internet of things (IoT) have been proposed in recent years, but they are not applied to the medical field, and they do not consider the security requirements of medical data. The proposed scheme in this paper has high computing and storage efficiency, while meeting the security requirements in MCPS.

Task scheduling mechanisms in fog computing: review, trends, and perspectives

Purpose In the past, with the development of the internet of things (IoT), this paper aims to consider fog computing (FC) as an efficient accompaniment to the cloud to control the IoT’s information and relation requirements. Wholly, FC is placed carefully around the IoT systems/sensors and develops cloud-based computing, memory and networking devices. Fog shares many similarities with the cloud, but the only difference between them is its location, in which fog devices are very close to end-users to process and respond to the client in less time. On the other hand, this system is useful for real-time flowing programs, sensor systems, and IoT that need high speed and reliable internet connectivity. However, there are many applications such as remote healthcare and medical cyber-physical systems, where low latency is needed. To reduce the latency of FC, the task scheduler plays a vital role. The task scheduling means to devote the task to fog resources in an efficient way. Yet, according to the findings, in spite of the preference of task scheduling techniques in the FC, there is not any review and research in this case. So, this paper offers systematic literature research about the available task scheduling techniques. In addition, the advantages and disadvantages associated with different task scheduling processes are considered, and the main challenges of them are addressed to design a more efficient task scheduler in the future. Additionally, according to the seen facts, future instructions are provided for these studies. Design/methodology/approach The paper complies with the methodological requirements of systematic literature reviews (SLR). The present paper investigates the newest systems and studies their practical techniques in detail. The applications of task scheduling mechanisms in FC have been categorized into two major groups, including heuristic and meta-heuristic. Findings Particularly, the replies to the project problem analyzed task scheduling are principal aim, present problems, project terminologies, methods and approaches in the fog settings. The authors tried to design his systematic discussion as precisely as possible. However, it might have still endured various confidence risks. Research limitations/implications This study aimed to be comprehensive but there were some limitations. First, the usage of affair scheduling in fog settings are contained in many places such as editorial notes, academic publications, technical writings, Web pages and so on. The published papers in national magazines were omitted. Also, the papers with the purpose of a special task scheduling issue, which probably consider other subjects rather than affair planning issue are omitted. So, in the competence of this study, this systematic analysis must be considered as the studies published in the central international FC journals. Second, the given issues might not have considered the general task scheduling area, which points to the possibility of describing more related questions that could be described. Third, research and publication bias: five confident electronic databases were chosen based on past study experiments. Finally, the numbers show that these five electronic databases must suggest the most related and reliable projects. Yet, selecting all main performing projects has not been confirmed. Probably some effective projects were omitted throughout the processes in Section 3. Different from the conclusion, changing from the search string to the information extraction exists, and the authors tried to exclude this by satisfying the source in central projects. Practical implications The results of this survey will be valuable for academicians, and it can provide visions into future research areas in this domain. Moreover, the disadvantages and advantages of the above systems have been studied, and their key issues have been emphasized to develop a more effective task scheduling mechanisms in the FC mechanisms. Originality/value It is useful to show the authors the state-of-the-art in the fog task scheduling area. The consequences of this project make researchers provide a more effective task planning approach in fog settings.

Secure Health Data Sharing for Medical Cyber-Physical Systems for the Healthcare 4.0.

The recent spades of cyber attacks have compromised end-users' data security and privacy in Medical Cyber-Physical Systems (MCPS) in the era of Health 4.0. Traditional standard encryption algorithms for data protection are designed based on a viewpoint of system architecture rather than a viewpoint of end-users. As such encryption algorithms are transferring the protection on the data to the protection on the keys, data safety, and privacy will be compromised once the key is exposed. In this paper, we propose a secure data storage and sharing method consisted of a selective encryption algorithm combined with fragmentation and dispersion to protect the data safety and privacy even when both transmission media (e.g. cloud servers) and keys are compromised. This method is based on a user-centric design that protects the data on a trusted device such as the end-users' smartphone and lets the end-user control the access for data sharing. We also evaluate the performance of the algorithm on a smartphone platform to prove efficiency.

Mobile Wi-Fi Based Scheduling of Cyber-Physical Systems in Healthcare

Wireless Body Area Networks (WBANs) and Wireless Local Area Networks (WLANs) have been widely regarded as solution providers for future Cyber-Physical Systems (CPS)-based ehealthcare amenities. The IEEE 802.11 standard specifies media access protocols in wireless networks, along with channel access methods. WBANs are expected to improve the existing healthcare services significantly, but several research challenges also have to be tackled for apt utilization of the technology. Guarantee of Quality-of-Service (QoS) differentiation between various health parameters, such as temperature and blood pressure, during mobility is a major challenge for the provision of ehealthcare services. The scheme proposed in this paper for the Mobile Wi-Fi based connectivity of WBANs is designed to provide QoS-based priorities for ehealthcare subscribers by altering the Contention Window (CW) for different applications of patient health monitoring. The relationship between CW and QoS is utilized to achieve efficient resource assignment. Three different health parameters, i.e., ECG (Electrocardiogram), BP (blood pressure) and temperature. are monitored using medical CPS in this work. The performance evaluation results, such as end-to-end packet delay and throughput for various data traffic classes reveal that the proposed scheme improves QoS provision.

A novel proxy-oriented public auditing scheme for cloud-based medical cyber physical systems

Cloud-based medical cyber-physical system (MCPS) is attracting more and more attention, since it can break through the limitations of time, space and object, and allow doctors to make accurate telemedicine diagnosis for patients. However, since medical information is directly related to the safety of patients’ lives and property, it has become an urgent problem to ensure the integrity and availability of medical data. To solve the above problems, many integrity auditing schemes have been proposed in recent years. Unfortunately, most existing schemes have security flaws or poor performance. Very recently, Zhang et al. proposed an identity-based proxy-oriented auditing scheme for checking the integrity of medical data, and claimed that their scheme was secure. However, we find that their scheme fails to achieve its purpose since it is vulnerable to the user impersonation attack and misusing delegation attack. we propose a new proxy-oriented public auditing scheme to fix the security vulnerabilities. Security analysis and performance evaluation demonstrate that our proposed scheme greatly reduces the communication and computation costs while ensuring a novel security level. Compared with Zhang et al.’s scheme, our scheme is more suitable for applications in cloud-based MCPS.