ISSN:2582-5208

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Paper Key : IRJ************042
Author: Victoria A Kehinde, Ifeoluwa Temitayo Ibigbami
Date Published: 01 Nov 2024
Abstract
The rapid advancement of technology has fundamentally transformed various sectors, with the Internet of Things (IoT) becoming a cornerstone in healthcare. Emerging technologies such as artificial intelligence (AI), machine learning, and blockchain have enhanced the efficiency and effectiveness of healthcare delivery, but they also present new cybersecurity challenges. In particular, the proliferation of IoT devices has made healthcare systems increasingly vulnerable to cyber threats, especially spyware attacks. Spyware, designed to covertly monitor and steal sensitive data from IoT devices, poses significant risks to patient privacy and healthcare integrity. Despite the implementation of various countermeasures, the threat of spyware remains prevalent within healthcare IoT systems. This paper explores the intersection of emerging technologies and cybersecurity in the healthcare sector, focusing on effective detection strategies and innovative mitigation techniques against spyware. By analysing the capabilities of AI-driven anomaly detection and machine learning algorithms, as well as the role of blockchain in enhancing data security, this research aims to provide actionable recommendations for healthcare organizations. The study seeks to bolster defenses against spyware, ensuring the protection of sensitive patient information while maximizing the benefits of emerging technologies. Ultimately, this research underscores the necessity of an adaptive cybersecurity framework that evolves alongside technological advancements to safeguard healthcare systems against malicious threats.
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