The digital transformation of the healthcare sector has revolutionized operational efficiency and patient care, yet concurrently exposed healthcare organizations to unprecedented cybersecurity risks, jeopardizing patient confidentiality and organizational integrity. This study undertakes a comprehensive investigation into contemporary cybersecurity strategies and emerging trends within the healthcare industry. Through a meticulous examination of published literature from reputable databases, including PubMed/MEDLINE, CINAHL, and Web of Science, critical patterns and vulnerabilities are discerned, underlining the escalating frequency and severity of cyber threats such as ransomware and phishing attacks. Emphasizing the pivotal role of organizational cyber resilience governance and policies, the study identifies a notable gap in standardized cybersecurity risk assessment methodologies, signaling the urgent need for innovative approaches. In response to identified challenges, the research proposes the development of novel methodologies to fortify cybersecurity defenses and protect patient data. Leveraging cutting-edge technologies such as blockchain and artificial intelligence, the study advocates for proactive measures to mitigate emerging threats and ensure data security and patient privacy in healthcare environments. Moreover, the integration of end-to-end security measures and the adoption of DevOps methodologies are highlighted as promising avenues for enhancing cybersecurity resilience. Results from a systematic literature review underscore the imperative for ongoing research and collaboration to address cybersecurity challenges in healthcare effectively. By offering insights into key cybersecurity features, technologies, and responsibilities within the healthcare sector, this study aims to inform stakeholders and policymakers, facilitating the implementation of robust cybersecurity measures. Furthermore, the study presents key findings regarding the current state of cybersecurity in healthcare, including challenges faced and potential solutions identified through the research process. Ultimately, through concerted efforts and the utilization of innovative strategies, healthcare organizations can navigate the evolving cybersecurity landscape, safeguarding patient information and upholding the integrity of healthcare systems.

Cloud computing is an emerging concept that makes better use of a large number of distributed resources. The most significant issue that affects the cloud computing environment is resource provisioning. Better performance in the shortest amount of time is an important goal in resource provisioning. Create the best solution for dynamically provisioning resources in the shortest time possible. This paper aims to perform resource provisioning with an optimal performance solution in the shortest time. Hybridization of two Meta-heuristics techniques, such as HSMOSA (Hybrid Spider Monkey Optimization with Simulated Annealing), is proposed in resource provisioning for cloud environment. Finds the global and local value using Spider Monkey Optimization's (SMO) social behavior and then utilizes Simulated Annealing (SA) to search around the global value in each iteration. As a result, the proposed approach aids in enhancing their chances of improving their position. The CloudSimPlus Simulator is used to test the proposed approach. The fitness value, execution time, throughput, mean, and standard deviation of the proposed method were calculated over various tasks and execution iterations. These performance metrics are compared with the PSO-SA algorithm. Simulation results validate the better working of the proposed HSMOSA algorithm with minimum time compared to the PSO-SA algorithm.