{"title":"Secured Frank Wolfe learning and Dirichlet Gaussian Vicinity based authentication for IoT edge computing","authors":"","doi":"10.1007/s12083-024-01667-1","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>With the evolution of the Internet of Things (IoT) several users take part in different applications via sensors. The foremost confront here remains in selecting the most confidential users or sensors in the edge computing system of the IoT. Here, both the end-users and the edge servers are likely to be malicious or compromised sensors. Several works have been contributed to identifying and isolating the malicious end-users or edge servers. Our work concentrates on the security aspects of edge servers of IoT. The Frank-Wolfe Optimal Service Requests (FWOSR) algorithm is utilized to evaluate the boundaries or limits of the logistic regression model, in which the convex problem under a linear approximation is solved for weight sparsity (i.e. several user requests competing for closest edge server) to avoid over-fitting in the supervised machine learning process. We design a Frank Wolfe Supervised Machine Learning (FWSL) technique to choose an optimal edge server and further minimize the computational and communication costs between the user requests and the edge server. Next, Dirichlet Gaussian Blocked Gibbs Vicinity-based Authentication model for location-based services in Cloud networks is proposed. Here, the vicinity-based authentication is implemented based on Received Signal Strength Indicators (RSSI), MAC address and packet arrival time. With this, the authentication accuracy is improved by introducing the Gaussian function in the vicinity test and provides flexible vicinity range control by taking into account multiple locations. Simulation and experiment are also conducted to validate the computational cost, communication cost, time complexity and detection error rate.</p>","PeriodicalId":49313,"journal":{"name":"Peer-To-Peer Networking and Applications","volume":"55 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Peer-To-Peer Networking and Applications","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s12083-024-01667-1","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
With the evolution of the Internet of Things (IoT) several users take part in different applications via sensors. The foremost confront here remains in selecting the most confidential users or sensors in the edge computing system of the IoT. Here, both the end-users and the edge servers are likely to be malicious or compromised sensors. Several works have been contributed to identifying and isolating the malicious end-users or edge servers. Our work concentrates on the security aspects of edge servers of IoT. The Frank-Wolfe Optimal Service Requests (FWOSR) algorithm is utilized to evaluate the boundaries or limits of the logistic regression model, in which the convex problem under a linear approximation is solved for weight sparsity (i.e. several user requests competing for closest edge server) to avoid over-fitting in the supervised machine learning process. We design a Frank Wolfe Supervised Machine Learning (FWSL) technique to choose an optimal edge server and further minimize the computational and communication costs between the user requests and the edge server. Next, Dirichlet Gaussian Blocked Gibbs Vicinity-based Authentication model for location-based services in Cloud networks is proposed. Here, the vicinity-based authentication is implemented based on Received Signal Strength Indicators (RSSI), MAC address and packet arrival time. With this, the authentication accuracy is improved by introducing the Gaussian function in the vicinity test and provides flexible vicinity range control by taking into account multiple locations. Simulation and experiment are also conducted to validate the computational cost, communication cost, time complexity and detection error rate.
期刊介绍：
The aim of the Peer-to-Peer Networking and Applications journal is to disseminate state-of-the-art research and development results in this rapidly growing research area, to facilitate the deployment of P2P networking and applications, and to bring together the academic and industry communities, with the goal of fostering interaction to promote further research interests and activities, thus enabling new P2P applications and services. The journal not only addresses research topics related to networking and communications theory, but also considers the standardization, economic, and engineering aspects of P2P technologies, and their impacts on software engineering, computer engineering, networked communication, and security.
The journal serves as a forum for tackling the technical problems arising from both file sharing and media streaming applications. It also includes state-of-the-art technologies in the P2P security domain.
Peer-to-Peer Networking and Applications publishes regular papers, tutorials and review papers, case studies, and correspondence from the research, development, and standardization communities. Papers addressing system, application, and service issues are encouraged.
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