Patil, Bharat Purushottam (2023) Encryption of the Healthcare Data to Protect Against Various Attacks. Masters thesis, Dublin, National College of Ireland.
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Abstract
The rapid advancement of technology and the advent of the Internet of Things (IoT) have revolutionized various industries, including healthcare. IoT devices in healthcare systems offer promising opportunities to improve patient care, increase operational efficiency, and enhance medical research. However, the integration of these devices into critical healthcare infrastructures raises significant concerns about security and privacy. This research delves into the multifaceted landscape of security challenges posed by IoT devices in healthcare systems and explores potential solutions to safeguard patient data, maintain the integrity of medical operations, and protect against potential cyber threats.
The first part of this research involves a comprehensive review of the current state of IoT devices in healthcare systems. It examines the various types of IoT devices deployed, ranging from wearable health monitors to smart medical devices and connected medical facilities. The analysis highlights their indispensable role in real-time patient monitoring, disease management, and remote patient care. Despite their transformative potential, these IoT devices also introduce new entry points for cyber attackers to exploit vulnerabilities and access sensitive patient data. With a focus on security threats, the second section of this research identifies and categorizes potential risks associated with IoT devices in healthcare systems. It sheds light on common attack vectors such as unauthorized access, data breaches, and denial-of-service (DoS) attacks.
The first part of this research involves a comprehensive review of the current state of IoT devices in healthcare systems. It examines the various types of IoT devices deployed, ranging from wearable health monitors to smart medical devices and connected medical facilities. The analysis highlights their indispensable role in real-time patient monitoring, disease management, and remote patient care. Despite their transformative potential, these IoT devices also introduce new entry points for cyber attackers to exploit vulnerabilities and access sensitive patient data. With a focus on security threats, the second section of this research identifies and categorizes potential risks associated with IoT devices in healthcare systems. It sheds light on common attack vectors such as unauthorized access, data breaches, and denial-of-service (DoS) attacks.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Heeney, Sean UNSPECIFIED |
Uncontrolled Keywords: | Cloud Security Confidentiality; Data Classification; Machine Learning; Cryptography Algorithm |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security H Social Sciences > HM Sociology > Information Science > Communication > Medical Informatics |
Divisions: | School of Computing > Master of Science in Cloud Computing |
Depositing User: | Tamara Malone |
Date Deposited: | 18 Oct 2024 15:44 |
Last Modified: | 18 Oct 2024 15:44 |
URI: | https://norma.ncirl.ie/id/eprint/7099 |
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