Data Security and Privacy Concern in the Healthcare System

Sourav, Ahuja

doi:10.1002/9781119792468.ch1

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…The internet's need for the application of communication technologies (voice, video, and data) is bringing about a very vital change in modern times today [1], [2], [3]. This brings changes to the gadget industry to develop technologies that can facilitate current communication needs, one of which is using VoIP (Voice over Internet Protocol) [4], [5], [6]. VoIP is a technology that enables long-distance voice conversation over the internet.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of VPN Protocols at Layer 2 Focusing on Voice Over Internet Protocol

Budiyanto

Gunawan

2023

IEEE Access

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Voice over Internet Protocols (VoIP) is an IP-based communication technology or commonly known as Internet Protocols (IP). In which, IP is currently widely used for mobile communication activities. However, the main concern in the application of VoIP technology is the system ability to maintain information confidentiality while guaranteeing protection to its primary users. For this reason, it requires to do the addition of Virtual Private Network (VPN) features. Conceptually, it aims to create connection lines in secret by utilizing the internal network structure (intranet) and to be accessed remotely using tunneling protocols in its security system. The purpose of this research is to compare the Quality of Service (QoS) on several tunneling protocols. Moreover, it is conducted to also analyze several security system mechanisms including Delay, Jitter, Throughput and Packet Loss. This analyzation is used for determining the best quality of some of the piloted tunneling security protocols. Furthermore, this work compares several methods of VoIP voicecall-testing in term of Generic Routing Encapsulation with IPSecurity (GRE+IPSec), Internet Protocol in Internet Protocol based Session Initiation Protocol (IPIP+SIP-based), Secure Socket Layer (SSL), and Layer 2 Tunneling Protocol IPSecurity (L2TP+IPSec). Accordingly, the comparative results show the better performance compared to the existing work, which is proven by the ability of the proposed method to provide the VoIP based on ITU-T.G.1010.

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Section: Introductionmentioning

confidence: 99%

Comparative Analysis of VPN Protocols at Layer 2 Focusing on Voice Over Internet Protocol

Budiyanto

Gunawan

2023

IEEE Access

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Usefulness of Honeypots Towards Data Security: A Systematic Literature Review

Silaen,

Meyliana,

Warnars

et al. 2023

2023 International Workshop on Artificial Intelligence and Image Processing (IWAIIP)

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Recent Advances in Big Medical Image Data Analysis Through Deep Learning and Cloud Computing

Shakor,

Khaleel

2024

Electronics

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This comprehensive study investigates the integration of cloud computing and deep learning technologies in medical data analysis, focusing on their combined effects on healthcare delivery and patient outcomes. Through a methodical examination of implementation instances at various healthcare facilities, we investigate how well these technologies manage a variety of medical data sources, such as wearable device data, medical imaging data, and electronic health records (EHRs). Our research demonstrates significant improvements in diagnostic accuracy (15–20% average increase) and operational efficiency (60% reduction in processing time) when utilizing cloud-based deep learning systems. We found that healthcare organizations implementing phased deployment approaches achieved 90% successful integration rates, while hybrid cloud architectures improved regulatory compliance by 50%. This study also revealed critical challenges, with 35% of implementations facing data integration issues and 5% experiencing security breaches. Through empirical analysis, we propose a structured implementation framework that addresses these challenges while maintaining high performance standards. Our findings indicate that federated learning techniques retain 95% model accuracy while enhancing privacy protection, and edge computing reduces latency by 40% in real-time processing. By offering quantitative proof of the advantages and difficulties of combining deep learning and cloud computing in medical data analysis, as well as useful recommendations for healthcare organizations seeking technological transformation, this study adds to the expanding body of knowledge on healthcare digitalization.

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Data Security and Privacy Concern in the Healthcare System

Cited by 3 publications

References 20 publications

Comparative Analysis of VPN Protocols at Layer 2 Focusing on Voice Over Internet Protocol

Comparative Analysis of VPN Protocols at Layer 2 Focusing on Voice Over Internet Protocol

Usefulness of Honeypots Towards Data Security: A Systematic Literature Review

Recent Advances in Big Medical Image Data Analysis Through Deep Learning and Cloud Computing

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