Secure and pervasive communication framework using Named Data Networking for connected healthcare

Dudeja, Rajan Kumar; Bali, Rasmeet Singh; Aujla, Gagangeet Singh

doi:10.1016/j.compeleceng.2022.107806

Cited by 9 publications

(5 citation statements)

References 24 publications

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“…In equations 9 to 11, hi, Ti, and Bi represent the delay, the number of hops, and the bandwidth of interfaces, i and m, are the number of output interfaces for each router, and dH, dt, db are the bandwidth deviation degree, delay deviation degree, and the number of hops deviation degree, respectively, which will be used for dynamic weighting of metrics in equation (13).…”

Section: Dynamic Weighting Of Metricsmentioning

confidence: 99%

“…Since this paper uses three criteria of bandwidth, delay, and hop count, we use equations (14)(15)(16) for dynamically determining the weight of each criterion based on equation (13).…”

Section: Dynamic Weighting Of Metricsmentioning

confidence: 99%

“…This leads to severe congestion and increases network resource consumption such as bandwidth and internal memory [4]. Among these challenges, forwarding in name-based networks has recently been investigated in various fields such as the Internet of Things [12], smart healthcare [13], smart cities [14], wireless networks [15], vehicle-to-vehicle communication [16], video streams [17], and others.…”

Section: Introductionmentioning

confidence: 99%

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FSCN: a novel forwarding method based on Shannon entropy and COPRAS decision process in named data networking

et al. 2023

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One of the next-generation Information-Centric Networking (ICN) architectures for the future Internet is Named Data Networking (NDN). The appropriate output interface (forwarding) has recently emerged as a key challenge affecting the performance of this network and has received a lot of attention from researchers due to its importance. Although efforts have been made through the methods introduced so far to address this challenge, the neglect of effective network load balancing parameters, non-dynamic weighting, and the use of only a few criteria have been suggested for selecting the output interface have made it vital to further improve the network delay, congestion, and ultimately the network's throughput. Regarding this matter, a new strategy is presented in this article based on the COPRAS Decision-Making Process with the dynamic weighting of Shannon's entropy called FSCN for transmitting request packets through the optimal output interface. The essential parameters identified in the suggested approach such as bandwidth, delay, and the number of hops can be dynamically weighted using the Shannon entropy technique and conditions. Then, the interfaces are scored using the COPRAS method, and the suitable output interface is ascertained. The advantages of the proposed method include considering influential criteria to characterize the path's performance and the dynamic weighting of criteria. The simulation outcomes in NDNsim demonstrated enhancements in critical parameters, including interest throughput, satisfaction ratio, packet drop, and delivery time when compared to comparable approaches.

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Section: Dynamic Weighting Of Metricsmentioning

confidence: 99%

“…Since this paper uses three criteria of bandwidth, delay, and hop count, we use equations (14)(15)(16) for dynamically determining the weight of each criterion based on equation (13).…”

Section: Dynamic Weighting Of Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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FSCN: a novel forwarding method based on Shannon entropy and COPRAS decision process in named data networking

et al. 2023

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“…Several studies have been proposed and used to preserve privacy of data along with the application of intrusion detection in IoT and industrial healthcare systems [1], [9], [11], [23], [24]. Various researchers used Machine Learning (ML) and Deep Learning (DL)-based techniques to design IDS in healthcare systems.…”

Section: Related Workmentioning

confidence: 99%

“…I N recent years, there has been remarkable growth and development in the Internet of Things (IoT)-driven applications and services including transportation, smart grid industry, networking, smart cities, and healthcare [1]. The extension of IoT in industrial settings, referred as Industrial Internet of Things (IIoT) has been introduced to substantially improve the quality of conventional industries by removing geographic barriers, and enabling autonomous manufacturing, remote monitoring, and real-time data delivery to customers [2].…”

Section: Introductionmentioning

confidence: 99%

Permissioned Blockchain and Deep Learning for Secure and Efficient Data Sharing in Industrial Healthcare Systems

Kumar

Tripathi

et al. 2022

IEEE Trans. Ind. Inf.

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The industrial healthcare system has enabled the possibility of realizing advanced real-time monitoring of patients and enriched the quality of medical services through data sharing among intelligent wearable devices and sensors. However, this connectivity brings the intrinsic vulnerabilities related to security and privacy due to the need of continuous communication and monitoring over public network (insecure channel). Motivated from the aforementioned discussions, we integrate Permissioned Blockchain and smart contract with Deep Learning (DL) techniques to design a novel secure and efficient data sharing framework named PBDL. Specifically, PBDL first has a blockchain scheme to register, verify (using zero-knowledge proof) and validate the communicating entities using smart contract-based consensus mechanism. Second, the authenticated data is used to propose a novel DL scheme that combines Stacked Sparse Variational AutoEncoder (SSVAE) with Self-Attentionbased Bidirectional Long Short Term Memory (SA-BiLSTM). In this scheme, SSVAE encodes or transforms the healthcare data into new format and SA-BiLSTM identifies and improves attack detection process. The security analysis and experimental results using IoT-Botnet and ToN-IoT datasets confirms the superiority of PBDL framework over existing state-of-the-art techniques.

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Software Defined Virtual Clustering-Based Content Distribution Mechanism in VNDN

Sharma

Garg

Mittal

et al. 2023

Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities

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Secure and pervasive communication framework using Named Data Networking for connected healthcare

Cited by 9 publications

References 24 publications

FSCN: a novel forwarding method based on Shannon entropy and COPRAS decision process in named data networking

FSCN: a novel forwarding method based on Shannon entropy and COPRAS decision process in named data networking

Permissioned Blockchain and Deep Learning for Secure and Efficient Data Sharing in Industrial Healthcare Systems

Software Defined Virtual Clustering-Based Content Distribution Mechanism in VNDN

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