Lingnan Xie, Linning Peng, Junqing Zhang, Aiqun Hu
Radio frequency fingerprint (RFF) identification is a promising technique for identifying Internet of Things (IoT) devices. This paper presents a comprehensive survey on RFF identification, which covers various aspects ranging from related definitions to details of each stage in the identification process, namely signal preprocessing, RFF feature extraction, further processing and RFF identification. Specifically, three main steps of preprocessing are summarized, including carrier frequency offset estimation, noise elimination and channel cancellation. Besides, three kinds of RFFs are categorized, comprising I/Q signal-based, parameter-based and transformation-based features. Meanwhile, feature fusion and feature dimension reduction are elaborated as two main further processing methods. Furthermore, a novel framework is established from the perspective of closed set and open set problems, and the related state-of-the-art methodologies are investigated, including approaches based on traditional machine learning, deep learning and generative models. Additionally, we highlight the challenges faced by RFF identification and point out future research trends in this field.
{"title":"Radio Frequency Fingerprint Identification for Internet of Things: A Survey","authors":"Lingnan Xie, Linning Peng, Junqing Zhang, Aiqun Hu","doi":"10.1051/sands/2023022","DOIUrl":"https://doi.org/10.1051/sands/2023022","url":null,"abstract":"Radio frequency fingerprint (RFF) identification is a promising technique for identifying Internet of Things (IoT) devices. This paper presents a comprehensive survey on RFF identification, which covers various aspects ranging from related definitions to details of each stage in the identification process, namely signal preprocessing, RFF feature extraction, further processing and RFF identification. Specifically, three main steps of preprocessing are summarized, including carrier frequency offset estimation, noise elimination and channel cancellation. Besides, three kinds of RFFs are categorized, comprising I/Q signal-based, parameter-based and transformation-based features. Meanwhile, feature fusion and feature dimension reduction are elaborated as two main further processing methods. Furthermore, a novel framework is established from the perspective of closed set and open set problems, and the related state-of-the-art methodologies are investigated, including approaches based on traditional machine learning, deep learning and generative models. Additionally, we highlight the challenges faced by RFF identification and point out future research trends in this field.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80956490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qingjiang Xiao, J. Zhao, Sheng Feng, Guyue Li, A. Hu
As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks.
{"title":"Securing NextG Networks with Physical-Layer Key Generation: A Survey","authors":"Qingjiang Xiao, J. Zhao, Sheng Feng, Guyue Li, A. Hu","doi":"10.1051/sands/2023021","DOIUrl":"https://doi.org/10.1051/sands/2023021","url":null,"abstract":"As the development of next-generation (NextG) communication networks continues, tremendous devices are accessing the network and the amount of information is exploding. However, with the increase of sensitive data that requires confidentiality to be transmitted and stored in the network, wireless network security risks are further amplified. Physical-layer key generation (PKG) has received extensive attention in security research due to its solid information-theoretic security proof, ease of implementation, and low cost. Nevertheless, the applications of PKG in the NextG networks are still in the preliminary exploration stage. Therefore, we survey existing research and discuss (1) the performance advantages of PKG compared to cryptography schemes, (2) the principles and processes of PKG, as well as research progresses in previous network environments, and (3) new application scenarios and development potential for PKG in NextG communication networks, particularly analyzing the effect and prospects of PKG in massive multiple-input multiple-output (MIMO), reconfigurable intelligent surfaces (RISs), artificial intelligence (AI) enabled networks, integrated space-air-ground network, and quantum communication. Moreover, we summarize open issues and provide new insights into the development trends of PKG in NextG networks.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"82 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83547877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper develops an event-triggered resilient consensus control method for the nonlinear multiple unmanned systems with a data-based autoregressive integrated moving average (ARIMA) agent state prediction mechanism against periodic denial-of-service (DoS) attacks. The state predictor is used to predict the state of neighbor agents during periodic DoS attacks and maintain consistent control of multiple unmanned systems under DoS attacks. Considering the existing prediction error between the actual state and the predicted state, the estimated error is regarded as the uncertainty system disturbance, which is dealt with by the designed disturbance observer. The estimated result is used in the design of the consistent controller to compensate for the system uncertainty error term. Furthermore, this paper investigates dynamic event-triggered consensus controllers to improve resilience and consensus under periodic DoS attacks and reduce the frequency of actuator output changes. It is proved that the Zeno behavior can be excluded. Finally, the resilience and consensus capability of the proposed controller and the superiority of introducing a state predictor are demonstrated through numerical simulations.
{"title":"Event-Triggered Resilient Consensus Control of Multiple Unmanned Systems Against Periodic DoS Attacks Based on State Predictor","authors":"You-min Zhang, Haichuan Yang, Ziquan Yu","doi":"10.1051/sands/2023017","DOIUrl":"https://doi.org/10.1051/sands/2023017","url":null,"abstract":"This paper develops an event-triggered resilient consensus control method for the nonlinear multiple unmanned systems with a data-based autoregressive integrated moving average (ARIMA) agent state prediction mechanism against periodic denial-of-service (DoS) attacks. The state predictor is used to predict the state of neighbor agents during periodic DoS attacks and maintain consistent control of multiple unmanned systems under DoS attacks. Considering the existing prediction error between the actual state and the predicted state, the estimated error is regarded as the uncertainty system disturbance, which is dealt with by the designed disturbance observer. The estimated result is used in the design of the consistent controller to compensate for the system uncertainty error term. Furthermore, this paper investigates dynamic event-triggered consensus controllers to improve resilience and consensus under periodic DoS attacks and reduce the frequency of actuator output changes. It is proved that the Zeno behavior can be excluded. Finally, the resilience and consensus capability of the proposed controller and the superiority of introducing a state predictor are demonstrated through numerical simulations.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82150862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies the secure motion control problem for micro-spacecraft systems. A novel semi-homomorphic encrypted control framework, consisting of a logarithmic quantizer, two uniform quantizers, and an encrypted control law based on the Paillier cryptosystem is developed. More specifically, a logarithmic quantizer is adopted as a digitizer to convert the continuous relative motion information to digital signals. Two uniform quantizers with different quantization sensitivities are designed to encode the control gain matrix and digitized motion information to integer values. Then, we develop an encrypted state-feedback control law based on the Paillier cryptosystem, which allows the controller to compute the control input using only encrypted data. Using the Lyapunov stability theory and the homomorphic property of the Paillier cryptosystem, we prove that all signals in the closed-loop system are uniformly ultimately bounded. Different from the traditional motion control laws of spacecraft, the proposed encrypted control framework ensures the security of the exchanged data over the communication network of the spacecraft, even when communication channels are eavesdropped by malicious adversaries. Finally, we verify the effectiveness of the proposed encrypted control framework using numerical simulations.
{"title":"Secure Motion Control of Micro-Spacecraft Using Semi-Homomorphic Encryption","authors":"Q. Hu, Yongxia Shi, Ehsan Nekouei","doi":"10.1051/sands/2023018","DOIUrl":"https://doi.org/10.1051/sands/2023018","url":null,"abstract":"This paper studies the secure motion control problem for micro-spacecraft systems. A novel semi-homomorphic encrypted control framework, consisting of a logarithmic quantizer, two uniform quantizers, and an encrypted control law based on the Paillier cryptosystem is developed. \u0000 More specifically, a logarithmic quantizer is adopted as a digitizer to convert the continuous relative motion information to digital signals. Two uniform quantizers with different quantization sensitivities are designed to encode the control gain matrix and digitized motion information to integer values. Then, we develop an encrypted state-feedback control law based on the Paillier cryptosystem, which allows the controller to compute the control input using only encrypted data. Using the Lyapunov stability theory and the homomorphic property of the Paillier cryptosystem, we prove that all signals in the closed-loop system are uniformly ultimately bounded. Different from the traditional motion control laws of spacecraft, the proposed encrypted control framework ensures the security of the exchanged data over the communication network of the spacecraft, even when communication channels are eavesdropped by malicious adversaries. Finally, we verify the effectiveness of the proposed encrypted control framework using numerical simulations.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83195906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Radio frequency fingerprint identification (RFFI) shows great potential as a means for authenticating wireless devices. As RFFI can be addressed as a classification problem, deep learning techniques are widely utilized in modern RFFI systems for their outstanding performance. RFFI is suitable for securing the legacy existing Internet of Things (IoT) networks since it does not require any modifications to the existing end-node hardware and communication protocols. However, most deep learning-based RFFI systems require the collection of a great number of labelled signals for training, which is time-consuming and not ideal, especially for the IoT end nodes that are already deployed and configured with long transmission intervals. Moreover, the long time required to train a neural network from scratch also limits rapid deployment on legacy IoT networks. To address the above issues, two transferable RFFI protocols are proposed in this paper leveraging the concept of transfer learning. More specifically, they rely on fine-tuning and distance metric learning, respectively, and only require only a small amount of signals from the legacy IoT network. As the dataset used for transfer is small, we propose to apply augmentation in the transfer process to generate more training signals to improve performance. A LoRa-RFFI testbed consisting of 40 commercial-off-the-shelf (COTS) LoRa IoT devices and a software-defined radio (SDR) receiver is built to experimentally evaluate the proposed approaches. The experimental results demonstrate that both the fine-tuning and distance metric learning-based RFFI approaches can be rapidly transferred to another IoT network with less than ten signals from each LoRa device. The classification accuracy is over 90%, and the augmentation technique can improve the accuracy by up to 20%.
{"title":"Exploration of Transferable Deep Learning-Aided Radio Frequency Fingerprint Identification Systems","authors":"Junqing Zhang, Guanxiong Shen","doi":"10.1051/sands/2023019","DOIUrl":"https://doi.org/10.1051/sands/2023019","url":null,"abstract":"Radio frequency fingerprint identification (RFFI) shows great potential as a means for authenticating wireless devices. As RFFI can be addressed as a classification problem, deep learning techniques are widely utilized in modern RFFI systems for their outstanding performance. RFFI is suitable for securing the legacy existing Internet of Things (IoT) networks since it does not require any modifications to the existing end-node hardware and communication protocols. However, most deep learning-based RFFI systems require the collection of a great number of labelled signals for training, which is time-consuming and not ideal, especially for the IoT end nodes that are already deployed and configured with long transmission intervals. Moreover, the long time required to train a neural network from scratch also limits rapid deployment on legacy IoT networks. To address the above issues, two transferable RFFI protocols are proposed in this paper leveraging the concept of transfer learning. More specifically, they rely on fine-tuning and distance metric learning, respectively, and only require only a small amount of signals from the legacy IoT network. As the dataset used for transfer is small, we propose to apply augmentation in the transfer process to generate more training signals to improve performance. A LoRa-RFFI testbed consisting of 40 commercial-off-the-shelf (COTS) LoRa IoT devices and a software-defined radio (SDR) receiver is built to experimentally evaluate the proposed approaches. The experimental results demonstrate that both the fine-tuning and distance metric learning-based RFFI approaches can be rapidly transferred to another IoT network with less than ten signals from each LoRa device. The classification accuracy is over 90%, and the augmentation technique can improve the accuracy by up to 20%.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80334030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, an attainable-equilibrium-set-based safety flight envelope (SFE) calculation method and a prescribed-performance-control-based SFE protection scheme are proposed for the attitude dynamic of a unmanned air vehicle (UAV) in the presence of external disturbances. To estimate the unknown external disturbances and their derivatives, a higher order disturbance observer (HODO) is developed. The definition and calculation of the SFE based on attainable equilibrium set (AES) under disturbances are studied. A safety desired trajectory based on the time-varying safety margin function and the first-order filter is developed to ensure the flight safety of UAV. A SFE protection controller is proposed based on the safety desired trajectory, backstepping method, HODO, and prescribed performance (PP) control technique. The stability of the closed-loop system is proved by the Lyapunov function method and the effectiveness of the SFE protection control law is verified by simulation.
{"title":"Safety Flight Envelope Calculation and Protection Control of UAV Based on Disturbance Observer","authors":"Biao Ma, Mou Chen","doi":"10.1051/sands/2023020","DOIUrl":"https://doi.org/10.1051/sands/2023020","url":null,"abstract":"In this paper, an attainable-equilibrium-set-based safety flight envelope (SFE) calculation method and a prescribed-performance-control-based SFE protection scheme are proposed for the attitude dynamic of a unmanned air vehicle (UAV) in the presence of external disturbances. To estimate the unknown external disturbances and their derivatives, a higher order disturbance observer (HODO) is developed. The definition and calculation of the SFE based on attainable equilibrium set (AES) under disturbances are studied. A safety desired trajectory based on the time-varying safety margin function and the first-order filter is developed to ensure the flight safety of UAV. A SFE protection controller is proposed based on the safety desired trajectory, backstepping method, HODO, and prescribed performance (PP) control technique. The stability of the closed-loop system is proved by the Lyapunov function method and the effectiveness of the SFE protection control law is verified by simulation.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86928515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kaibo Shi, Xiao Cai, Kun She, S. Zhong, Shixian Wen, Yuanlun Xie
This study focuses on the networked control systems (NCSs) under Denial of Service (DoS) attacks with periodicity and attack intensity. A DoS attack with attack strength is studied, which has important research significance for establishing a suitable defense mechanism. First, the construction of appropriate Lyapunov-Krasovskii functionals (LKFs) can reduce the constraints of the basic conditions and help lower the criterion's conservatism. Then, the selection problem of the trigger threshold is transformed into an optimization problem with constraints, and the gradient descent algorithm (GDA) is used to select the trigger threshold to save sampling resources better. Next, an intelligent event-triggered controller (IETC) is designed to ensure the safe operation of the system under DoS attacks. Finally, the correctness of the method is verified through the experiment of the autonomous ground vehicle (AGV) system based on the Simulink platform.
{"title":"Communication Security of Autonomous Ground Vehicles Based on Networked Control Systems: The Optimized LMI Approach","authors":"Kaibo Shi, Xiao Cai, Kun She, S. Zhong, Shixian Wen, Yuanlun Xie","doi":"10.1051/sands/2023016","DOIUrl":"https://doi.org/10.1051/sands/2023016","url":null,"abstract":"This study focuses on the networked control systems (NCSs) under Denial of Service (DoS) attacks with periodicity and attack intensity. A DoS attack with attack strength is studied, which has important research significance for establishing a suitable defense mechanism. First, the construction of appropriate Lyapunov-Krasovskii functionals (LKFs) can reduce the constraints of the basic conditions and help lower the criterion's conservatism. Then, the selection problem of the trigger threshold is transformed into an optimization problem with constraints, and the gradient descent algorithm (GDA) is used to select the trigger threshold to save sampling resources better. Next, an intelligent event-triggered controller (IETC) is designed to ensure the safe operation of the system under DoS attacks. Finally, the correctness of the method is verified through the experiment of the autonomous ground vehicle (AGV) system based on the Simulink platform.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74708694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shiya Liu, Hong Zou, Xing Zhao, Chunhui Wang, Yang Fan
In recent years, as the flow dividend peaking and supervision tend to be rigorous due to industrial monopolization, mobile internet has suffered from a development bottleneck at the top. Liu illustrates this issue in her article and gives a general overview of the security issues of the metaverse [1]. As she says, the essence of mobile internet is platform economy. Such “movement of enclosures” based on the user resource reaches the top with the advent of the mobile terminal era and also steps into the dilemma with the enhancement of closure and monopoly, it is more urgent to transform new development pattern. As a new generation of information technology becomes clear in the development path, the “Metaverse” concept based on composite new information technology has been proposed and is highly concerned. Such a new model with the attribute of “being owned by users” and “decentralization” complies with the underlying demands of industry breakthrough and becomes the next generation of network solutions which is put into practice by more and more leading companies. However, the “Metaverse” develops at the initial phase, because the technology ecology, business ecology, and public cognition are not perfect, and confront multi-dimensional and coupled safety issues. We hereby have organized the “Metaverse security” topic in the Security and Safety (S&S) for such an emerging and hot field, covering the contribution of seven groups of research personnel in every field. We have been devoted to covering the safety issue of “Metaverse” from the perspective of construction, operation, recognition, etc., providing the corresponding solution and offering wisdom and direction for its steady development. The “Metaverse” needs to be achieved by compounding various technologies, including Virtual Reality, Artificial Intelligence, Cloud computing, Blockchain, etc., so, it is necessary to construct lots of infrastructure facilities accordingly to support its operation. In this topic, there is a review from Li et al. [2], which expounds on the main components of “Metaverse” infrastructure facilities and systematically summarizes the inherent security risks in “Metaverse” infrastructure facilities. Then Li et al., guided by the system security technology philosophy, propose to construct the safety defense system of “Metaverse” in terms of computing, cloud, network, digital assets, terminal, etc. from different perspectives, which lays a solid foundation for coping with “Metaverse” security risk and challenges. Except for the support of infrastructure facilities, the generalized function security issue, including functional safety and network safety exists in the operation of “Metaverse”. The traditional system reliability technology and network defense technology cannot provide the quantifiable design implementation theory and method. The operating system as the footstone of the software system needs an efficient security guarantee. Here is an article from Song et al.
{"title":"Preface: Security and Safety in the “Metaverse”","authors":"Shiya Liu, Hong Zou, Xing Zhao, Chunhui Wang, Yang Fan","doi":"10.1051/sands/2023014","DOIUrl":"https://doi.org/10.1051/sands/2023014","url":null,"abstract":"In recent years, as the flow dividend peaking and supervision tend to be rigorous due to industrial monopolization, mobile internet has suffered from a development bottleneck at the top. Liu illustrates this issue in her article and gives a general overview of the security issues of the metaverse [1]. As she says, the essence of mobile internet is platform economy. Such “movement of enclosures” based on the user resource reaches the top with the advent of the mobile terminal era and also steps into the dilemma with the enhancement of closure and monopoly, it is more urgent to transform new development pattern. As a new generation of information technology becomes clear in the development path, the “Metaverse” concept based on composite new information technology has been proposed and is highly concerned. Such a new model with the attribute of “being owned by users” and “decentralization” complies with the underlying demands of industry breakthrough and becomes the next generation of network solutions which is put into practice by more and more leading companies. However, the “Metaverse” develops at the initial phase, because the technology ecology, business ecology, and public cognition are not perfect, and confront multi-dimensional and coupled safety issues. We hereby have organized the “Metaverse security” topic in the Security and Safety (S&S) for such an emerging and hot field, covering the contribution of seven groups of research personnel in every field. We have been devoted to covering the safety issue of “Metaverse” from the perspective of construction, operation, recognition, etc., providing the corresponding solution and offering wisdom and direction for its steady development. The “Metaverse” needs to be achieved by compounding various technologies, including Virtual Reality, Artificial Intelligence, Cloud computing, Blockchain, etc., so, it is necessary to construct lots of infrastructure facilities accordingly to support its operation. In this topic, there is a review from Li et al. [2], which expounds on the main components of “Metaverse” infrastructure facilities and systematically summarizes the inherent security risks in “Metaverse” infrastructure facilities. Then Li et al., guided by the system security technology philosophy, propose to construct the safety defense system of “Metaverse” in terms of computing, cloud, network, digital assets, terminal, etc. from different perspectives, which lays a solid foundation for coping with “Metaverse” security risk and challenges. Except for the support of infrastructure facilities, the generalized function security issue, including functional safety and network safety exists in the operation of “Metaverse”. The traditional system reliability technology and network defense technology cannot provide the quantifiable design implementation theory and method. The operating system as the footstone of the software system needs an efficient security guarantee. Here is an article from Song et al.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78906619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the trend of digitalization, intelligence, and networking sweeping the world, functional safety and cyber security are increasingly intertwined and overlapped, evolving into the issue of generalized functional safety. Traditional system reliability technology and network defense technology cannot provide quantifiable design implementation theories and methods. As the cornerstone of software systems, operating systems in particular are in need of efficient safety assurance. The DHR architecture is a mature and comprehensive solution, and it is necessary to implement an OS-level DHR architecture, for which the multi-kernel operating system is a good carrier. The multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy, heterogeneity, and dynamism on the kernel, so it has the generalized robustness of the DHR architecture. This article analyzes the significance and requirements of OS-level DHR architecture, and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.
{"title":"Multikernel: Operating System Solution to Generalized Functional Safety","authors":"Yi Song, Huasheng Dai, Jinhu Jiang, Weihua Zhang","doi":"10.1051/sands/2023007","DOIUrl":"https://doi.org/10.1051/sands/2023007","url":null,"abstract":"With the trend of digitalization, intelligence, and networking sweeping the world, functional safety and cyber security are increasingly intertwined and overlapped, evolving into the issue of generalized functional safety. Traditional system reliability technology and network defense technology cannot provide quantifiable design implementation theories and methods. As the cornerstone of software systems, operating systems in particular are in need of efficient safety assurance. The DHR architecture is a mature and comprehensive solution, and it is necessary to implement an OS-level DHR architecture, for which the multi-kernel operating system is a good carrier. The multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy, heterogeneity, and dynamism on the kernel, so it has the generalized robustness of the DHR architecture. This article analyzes the significance and requirements of OS-level DHR architecture, and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86018394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lei Shi, Zhen Chen, Yucheng Shi, Lin Wei, Yongcai Tao, Mengyang He, Qingxian Wang, Yuan Zhou, Yufei Gao
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{"title":"MPHM: Model Poisoning Attacks on Federal Learning Using Historical Information Momentum","authors":"Lei Shi, Zhen Chen, Yucheng Shi, Lin Wei, Yongcai Tao, Mengyang He, Qingxian Wang, Yuan Zhou, Yufei Gao","doi":"10.1051/sands/2023006","DOIUrl":"https://doi.org/10.1051/sands/2023006","url":null,"abstract":".","PeriodicalId":79641,"journal":{"name":"Hospital security and safety management","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89254169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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