Vladimir Rocha, Daniel Czeresnia, Carlo Kleber da Silva Rodrigues
Chord is a Distributed Hash Table widely used for its efficiency in searching for information. The efficiency of this structure relies on creating short paths of O(log2 n) between two nodes, in which n is the number of nodes. To enhance efficiency, several studies use replication in the nodes belonging to the network, assuming that searches will converge in these replicated nodes. This work proposes a convergence formula and analyzes the number of searches converging on nodes for different network sizes (small, medium, and large), up to one million nodes. The experiments show that the convergence creates three zones and the results support the replication techniques from previous studies and demonstrate that it is feasible to replicate in nodes that were not considered in these studies.
Chord 是一种分布式散列表，因其搜索信息的效率高而被广泛使用。这种结构的效率依赖于在两个节点之间创建 O（log2 n）的短路径，其中 n 是节点数。为了提高效率，一些研究在属于网络的节点中使用了复制，假设搜索会在这些复制节点中收敛。这项工作提出了一个收敛公式，并分析了不同网络规模（小型、中型和大型）（最高达一百万个节点）的节点上收敛的搜索次数。实验表明，收敛会产生三个区域，结果支持了之前研究中的复制技术，并证明在这些研究未考虑的节点上复制是可行的。
{"title":"Analysis of Path Convergence in Chord DHT","authors":"Vladimir Rocha, Daniel Czeresnia, Carlo Kleber da Silva Rodrigues","doi":"10.37256/cnc.2220244753","DOIUrl":"https://doi.org/10.37256/cnc.2220244753","url":null,"abstract":"Chord is a Distributed Hash Table widely used for its efficiency in searching for information. The efficiency of this structure relies on creating short paths of O(log2 n) between two nodes, in which n is the number of nodes. To enhance efficiency, several studies use replication in the nodes belonging to the network, assuming that searches will converge in these replicated nodes. This work proposes a convergence formula and analyzes the number of searches converging on nodes for different network sizes (small, medium, and large), up to one million nodes. The experiments show that the convergence creates three zones and the results support the replication techniques from previous studies and demonstrate that it is feasible to replicate in nodes that were not considered in these studies.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"38 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141804113","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}
Cloud computing enables users to access required resources, with the invention of high-end devices leading to exponential increases in cloud resource requests. This poses significant challenges for resource management due to the scale of the cloud and unpredictable user demands. This paper presents an approach to managing resources during peak request periods for virtual machines (VMs) by leveraging cloud federation, outsourcing requests to other federation members. An algorithm is proposed to initiate cloud federation and allocate customer requests within it. The primary objectives are to increase the profit of cloud providers and improve resource utilization. An ensemble algorithm maximizes profit using both the proposed algorithm and three established ones. Experimental results demonstrate that our method outperforms existing approaches in profit, resource utilization, and rejected requests in most scenarios.
{"title":"Optimizing Cloud Resource Allocation in Federated Environments through Outsourcing Strategies","authors":"Arash Mazidi","doi":"10.37256/cnc.2220244747","DOIUrl":"https://doi.org/10.37256/cnc.2220244747","url":null,"abstract":"Cloud computing enables users to access required resources, with the invention of high-end devices leading to exponential increases in cloud resource requests. This poses significant challenges for resource management due to the scale of the cloud and unpredictable user demands. This paper presents an approach to managing resources during peak request periods for virtual machines (VMs) by leveraging cloud federation, outsourcing requests to other federation members. An algorithm is proposed to initiate cloud federation and allocate customer requests within it. The primary objectives are to increase the profit of cloud providers and improve resource utilization. An ensemble algorithm maximizes profit using both the proposed algorithm and three established ones. Experimental results demonstrate that our method outperforms existing approaches in profit, resource utilization, and rejected requests in most scenarios.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"105 51","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141667034","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}
The sharing of private information is a daunting, multifaceted, and expensive undertaking. Furthermore, identity management is an additional challenge that poses significant technological, operational, and legal obstacles. Present solutions and their accompanying infrastructures rely on centralized models that are susceptible to hacking and can hinder data control by the rightful owner. Consequently, blockchain technology has generated interest in the fields of identity and access control. This technology is viewed as a potential solution due to its ability to offer decentralization, transparency, provenance, security, and privacy benefits. Nevertheless, a completely decentralized and private solution that enables data owners to control their private data has yet to be presented. In this research, we introduce DeAuth, a novel decentralized, authentication and authorization scheme for secure private data transfer. DeAuth combines blockchain, smart-contracts, decentralized identity, and distributed peer-to-peer (P2P) storage to give users more control of their private data, and permissioning power to share without centralized services. For this scheme, identity is proven using decentralized identifiers and verifiable credentials, while authorization to share data is performed using the blockchain. A prototype was developed using the Ethereum Blockchain and the InterPlanetary Files System, a P2P file sharing protocol. We evaluated DeAuth through a use-case study and metrics such as security, performance, and cost. Our findings indicate DeAuth to be viable alternative to using centralized services; however, the underlying technologies are still in its infancies and require more testing before it can supplant traditional services.
{"title":"DeAuth: A Decentralized Authentication and Authorization Scheme for Secure Private Data Sharing","authors":"Phillipe Austria, Yoohwan Kim, Ju-Yeon Jo","doi":"10.37256/cnc.2220244281","DOIUrl":"https://doi.org/10.37256/cnc.2220244281","url":null,"abstract":"The sharing of private information is a daunting, multifaceted, and expensive undertaking. Furthermore, identity management is an additional challenge that poses significant technological, operational, and legal obstacles. Present solutions and their accompanying infrastructures rely on centralized models that are susceptible to hacking and can hinder data control by the rightful owner. Consequently, blockchain technology has generated interest in the fields of identity and access control. This technology is viewed as a potential solution due to its ability to offer decentralization, transparency, provenance, security, and privacy benefits. Nevertheless, a completely decentralized and private solution that enables data owners to control their private data has yet to be presented. In this research, we introduce DeAuth, a novel decentralized, authentication and authorization scheme for secure private data transfer. DeAuth combines blockchain, smart-contracts, decentralized identity, and distributed peer-to-peer (P2P) storage to give users more control of their private data, and permissioning power to share without centralized services. For this scheme, identity is proven using decentralized identifiers and verifiable credentials, while authorization to share data is performed using the blockchain. A prototype was developed using the Ethereum Blockchain and the InterPlanetary Files System, a P2P file sharing protocol. We evaluated DeAuth through a use-case study and metrics such as security, performance, and cost. Our findings indicate DeAuth to be viable alternative to using centralized services; however, the underlying technologies are still in its infancies and require more testing before it can supplant traditional services.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":" 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676004","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}
The edge computing devices running models based on deep learning have drawn a lot of interest as a prominent way of handling various applications based on AI. Due to limited memory and computing resources, it is still difficult to deploy deep learning models on edge devices in a production context with effective inference. This study examines the deployment of a lightweight facemask detection model on edge devices with real-time inference. The proposed framework uses a dual-stage convolutional neural network (CNN) architecture with two main modules that use Caffe-DNN for face detection and a proposed model based on CNN architecture or customized models based on transfer learning (e.g., MobileNet-v2, resNet50, denseNet121, NASNetMobile, Inception-v3, and XceptionNet) for facemask classification. The study does numerous analyses based on the models' performance in terms of accuracy, precision, recall, and F1-score and compares all models with low disk size and good accuracy as the main priorities for memory-constrained edge devices. The proposed CNN model for facemask detection outperforms other state-of-the-art models in terms of accuracy, achieving 99%, 99%, and 99% on the training, validation, and testing, respectively, with the facemask detection ~12K image datasets available on Kaggle. This accuracy is comparable to other transfer learning-based models, and it also achieves the smallest number of total trainable parameters and, thus, the smallest disk size of all models.
{"title":"FaceLite: A Real-Time Light-Weight Facemask Detection Using Deep Learning: A Comprehensive Analysis, Opportunities, and Challenges for Edge Computing","authors":"Anup Kumar Paul","doi":"10.37256/cnc.2120244439","DOIUrl":"https://doi.org/10.37256/cnc.2120244439","url":null,"abstract":"The edge computing devices running models based on deep learning have drawn a lot of interest as a prominent way of handling various applications based on AI. Due to limited memory and computing resources, it is still difficult to deploy deep learning models on edge devices in a production context with effective inference. This study examines the deployment of a lightweight facemask detection model on edge devices with real-time inference. The proposed framework uses a dual-stage convolutional neural network (CNN) architecture with two main modules that use Caffe-DNN for face detection and a proposed model based on CNN architecture or customized models based on transfer learning (e.g., MobileNet-v2, resNet50, denseNet121, NASNetMobile, Inception-v3, and XceptionNet) for facemask classification. The study does numerous analyses based on the models' performance in terms of accuracy, precision, recall, and F1-score and compares all models with low disk size and good accuracy as the main priorities for memory-constrained edge devices. The proposed CNN model for facemask detection outperforms other state-of-the-art models in terms of accuracy, achieving 99%, 99%, and 99% on the training, validation, and testing, respectively, with the facemask detection ~12K image datasets available on Kaggle. This accuracy is comparable to other transfer learning-based models, and it also achieves the smallest number of total trainable parameters and, thus, the smallest disk size of all models.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"62 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140984850","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}
Physical layer Network Coding (PNC) is a promising strategy to improve the spectral efficiency in a relay-based wireless transmission. This paper employs lattice-based channel coding at the source nodes for better performance during Multiple Access Channel (MAC) phase transmission. The achievable transmission rate in various PNC relaying such as Decode and Forward (DF), Amplify and Forward (AF), and Compute and Forward (CF) for the Two Way Relay Network model (TWRN) is derived and simulated through MATLAB software and analyzed. The analysis shows that the rate performance of CF relaying outperforms other relaying techniques in the Additive White Gaussian Noise (AWGN) channel, but it degrades for the Rayleigh fading channel. To mitigate the fading effects, channel aware precoding technique is employed at source nodes, Bit Error Rate (BER) and Symbol Error Rate (SER) performance are analyzed for CF relaying, and Monte Carlo simulations are used to demonstrate the theoretical results. Channel precoding performance of CF relaying is compared with DF relaying.
{"title":"Channel Precoding for Compute and Forward Relaying in Two Way Relay Network Model","authors":"Jeyalakshmi Vijayarajan, S. T. Selvi","doi":"10.37256/cnc.2120244057","DOIUrl":"https://doi.org/10.37256/cnc.2120244057","url":null,"abstract":"Physical layer Network Coding (PNC) is a promising strategy to improve the spectral efficiency in a relay-based wireless transmission. This paper employs lattice-based channel coding at the source nodes for better performance during Multiple Access Channel (MAC) phase transmission. The achievable transmission rate in various PNC relaying such as Decode and Forward (DF), Amplify and Forward (AF), and Compute and Forward (CF) for the Two Way Relay Network model (TWRN) is derived and simulated through MATLAB software and analyzed. The analysis shows that the rate performance of CF relaying outperforms other relaying techniques in the Additive White Gaussian Noise (AWGN) channel, but it degrades for the Rayleigh fading channel. To mitigate the fading effects, channel aware precoding technique is employed at source nodes, Bit Error Rate (BER) and Symbol Error Rate (SER) performance are analyzed for CF relaying, and Monte Carlo simulations are used to demonstrate the theoretical results. Channel precoding performance of CF relaying is compared with DF relaying.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"62 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140364848","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}
Mobile banking applications make users' daily lives easier by allowing them to access banking services, such as balance inquiries and bill payments, anytime and anywhere. Since these applications manage very sensitive financial data, special attention must be paid to data security. Several works in the literature assess the security of mobile banking applications. However, we observe the lack of a widely adopted framework among researchers for assessing the security of mobile banking applications. In this paper, we propose a framework consisting of twenty-six criteria for assessing the security of Android mobile banking applications. These criteria are divided into five categories: mobile device security, data in transit, data storage, cryptographic misuse, and others. Subsequently, we evaluate the proposed framework based on predefined requirements. These requirements are no redundancy, no ambiguity, and comprehensiveness. As a case study, we assess the security of the Android mobile banking applications of seven major Canadian banks. The results show that data in transit is adequately protected by these applications.
{"title":"A Framework for Security Assessment of Android Mobile Banking Applications","authors":"Loïc D. Tsobdjou, Samuel Pierre, A. Quintero","doi":"10.37256/cnc.2120243929","DOIUrl":"https://doi.org/10.37256/cnc.2120243929","url":null,"abstract":"\u0000Mobile banking applications make users' daily lives easier by allowing them to access banking services, such as balance inquiries and bill payments, anytime and anywhere. Since these applications manage very sensitive financial data, special attention must be paid to data security. Several works in the literature assess the security of mobile banking applications. However, we observe the lack of a widely adopted framework among researchers for assessing the security of mobile banking applications. In this paper, we propose a framework consisting of twenty-six criteria for assessing the security of Android mobile banking applications. These criteria are divided into five categories: mobile device security, data in transit, data storage, cryptographic misuse, and others. Subsequently, we evaluate the proposed framework based on predefined requirements. These requirements are no redundancy, no ambiguity, and comprehensiveness. As a case study, we assess the security of the Android mobile banking applications of seven major Canadian banks. The results show that data in transit is adequately protected by these applications.\u0000","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"20 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140259730","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}
Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.
可穿戴无线传感器网络（WWSN）设备被广泛应用于医疗保健领域，以监测健康数据。然而，当 WWSN 用户通过无线连接向医疗专业人员或第三方传输数据时，他们面临着隐私和安全漏洞。本文旨在找出医疗保健领域可穿戴传感器设备中尚未解决的隐私和安全挑战，尤其是以往研究忽略的方面。主要研究问题是：医疗保健领域的可穿戴传感器设备有哪些尚未解决的隐私和安全挑战，它们对用户和医疗保健专业人员有何影响？本系统性综述采用特定的关键词来搜索文献数据库中的相关出版物，包括 Google Scholar、Scopus、IEEE Xplore 和 Web of Science。系统综述和元分析首选报告项目（PRISMA）图表有助于筛选和总结所选论文。研究结果强调了可能使 WWSN 容易受到安全攻击的关键领域。研究结果探讨了云计算、雾计算、物联网 (IoT) 等领域中可穿戴传感设备的安全和隐私问题。许多研究之所以对物联网进行研究，是因为物联网在隐私和安全方面面临挑战，尤其是在处理大量数据、使用公共渠道、部署先进技术、在无线设备数量不断增加的同时管理共享策略以及保护数据免受黑客攻击等方面。这些挑战严重威胁着 WWSN 用户在基于云的环境和物联网中向医疗保健专业人员或第三方传输的健康数据的保密性、完整性和可用性，而有限的资源又加剧了这些挑战。因此，重要发现集中于物联网中尚未解决的领域。本文旨在防范针对医疗保健的网络攻击，提高用户对 WWSN 设备的采用率。
{"title":"Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review","authors":"Ranjit Kaur, Seyed Shahrestani, Chun Ruan","doi":"10.37256/cnc.2120243852","DOIUrl":"https://doi.org/10.37256/cnc.2120243852","url":null,"abstract":"Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864557","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}
Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.
可穿戴无线传感器网络（WWSN）设备被广泛应用于医疗保健领域，以监测健康数据。然而，当 WWSN 用户通过无线连接向医疗专业人员或第三方传输数据时，他们面临着隐私和安全漏洞。本文旨在找出医疗保健领域可穿戴传感器设备中尚未解决的隐私和安全挑战，尤其是以往研究忽略的方面。主要研究问题是：医疗保健领域的可穿戴传感器设备有哪些尚未解决的隐私和安全挑战，它们对用户和医疗保健专业人员有何影响？本系统性综述采用特定的关键词来搜索文献数据库中的相关出版物，包括 Google Scholar、Scopus、IEEE Xplore 和 Web of Science。系统综述和元分析首选报告项目（PRISMA）图表有助于筛选和总结所选论文。研究结果强调了可能使 WWSN 容易受到安全攻击的关键领域。研究结果探讨了云计算、雾计算、物联网 (IoT) 等领域中可穿戴传感设备的安全和隐私问题。许多研究之所以对物联网进行研究，是因为物联网在隐私和安全方面面临挑战，尤其是在处理大量数据、使用公共渠道、部署先进技术、在无线设备数量不断增加的同时管理共享策略以及保护数据免受黑客攻击等方面。这些挑战严重威胁着 WWSN 用户在基于云的环境和物联网中向医疗保健专业人员或第三方传输的健康数据的保密性、完整性和可用性，而有限的资源又加剧了这些挑战。因此，重要发现集中于物联网中尚未解决的领域。本文旨在防范针对医疗保健的网络攻击，提高用户对 WWSN 设备的采用率。
{"title":"Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review","authors":"Ranjit Kaur, Seyed Shahrestani, Chun Ruan","doi":"10.37256/cnc.2120243852","DOIUrl":"https://doi.org/10.37256/cnc.2120243852","url":null,"abstract":"Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"22 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139804745","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}
Many key applications in Cyber-Physical Systems require the transmission of speech, audio, or video. These scenarios involve the use of traditional Real-Time Communication (RTC) protocols and technologies, which cannot always be used in the context of core networks. This is particularly critical in the context of Event-Driven Architectures (EDAs), where RTC protocols require the use of complex topologies that rely on costly infrastructure. One way to avoid this is by encapsulating all media traffic in EDA protocols. However, this approach does not come without challenges. Specifically, the nature of the transport protocols causes the media to be heavily affected by application layer impairments that render their usage highly impractical. To prevent this from happening, this paper introduces a unified scheme that supports the efficient encapsulation of media traffic in EDA scenarios. This is accomplished through a mechanism that relies on a Machine Learning (ML) model that is exercised in an experimental framework.
{"title":"Mechanism for Efficient Media Propagation in Event-Driven Cyber-Physical Systems","authors":"Rolando Herrero","doi":"10.37256/cnc.2120243999","DOIUrl":"https://doi.org/10.37256/cnc.2120243999","url":null,"abstract":"Many key applications in Cyber-Physical Systems require the transmission of speech, audio, or video. These scenarios involve the use of traditional Real-Time Communication (RTC) protocols and technologies, which cannot always be used in the context of core networks. This is particularly critical in the context of Event-Driven Architectures (EDAs), where RTC protocols require the use of complex topologies that rely on costly infrastructure. One way to avoid this is by encapsulating all media traffic in EDA protocols. However, this approach does not come without challenges. Specifically, the nature of the transport protocols causes the media to be heavily affected by application layer impairments that render their usage highly impractical. To prevent this from happening, this paper introduces a unified scheme that supports the efficient encapsulation of media traffic in EDA scenarios. This is accomplished through a mechanism that relies on a Machine Learning (ML) model that is exercised in an experimental framework.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"65 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139593764","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 terms of fundamental research and technology development level, Wireless Body Area Network (WBAN) is a well-established paradigm of wireless system. However, like any wireless system, channel modeling of WBAN is one of the most challenging research eras. Also, literature suggests Channel Model-3, termed as CM-3 scenario based on the positioning of the Nano antenna, is one of the most useful deployment scenarios of WBAN. Further, arrival time and the number of arrivals, which plays an important role in the CM-3 scenario of WBAN, are modeled using the Poisson distribution. However, in Poisson distribution the variance and mean are equal and the probability of success is kept fixed. Hence, the versatility of the channel model based Poisson distribution is limited due to limited parameters. On the other hand, Negative Binomial (NB) distribution with extra parameters is a more general distribution. Therefore, this manuscript employs Negative Binomial distribution to present a more general channel model under the CM-3 scenario. In addition, effects of different windowing techniques, such as Bartlett and Gaussian window, on the channel model are analyzed under both, Poisson distribution and Negative Binomial distributions.
{"title":"Channel Model for CM-3 Scenario Over Generalized Distribution Under Various Window Functions","authors":"Shekhar Singh, S. P. Singh, L. M","doi":"10.37256/cnc.2120244017","DOIUrl":"https://doi.org/10.37256/cnc.2120244017","url":null,"abstract":"In terms of fundamental research and technology development level, Wireless Body Area Network (WBAN) is a well-established paradigm of wireless system. However, like any wireless system, channel modeling of WBAN is one of the most challenging research eras. Also, literature suggests Channel Model-3, termed as CM-3 scenario based on the positioning of the Nano antenna, is one of the most useful deployment scenarios of WBAN. Further, arrival time and the number of arrivals, which plays an important role in the CM-3 scenario of WBAN, are modeled using the Poisson distribution. However, in Poisson distribution the variance and mean are equal and the probability of success is kept fixed. Hence, the versatility of the channel model based Poisson distribution is limited due to limited parameters. On the other hand, Negative Binomial (NB) distribution with extra parameters is a more general distribution. Therefore, this manuscript employs Negative Binomial distribution to present a more general channel model under the CM-3 scenario. In addition, effects of different windowing techniques, such as Bartlett and Gaussian window, on the channel model are analyzed under both, Poisson distribution and Negative Binomial distributions.","PeriodicalId":505128,"journal":{"name":"Computer Networks and Communications","volume":"9 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139609541","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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