Cybersecurity in the Cloud Era: Addressing Ransomware Threats with AI and Advanced Security Protocols

Dr. Min-Jun, Lee and Ji-Eun, Park (2020) Cybersecurity in the Cloud Era: Addressing Ransomware Threats with AI and Advanced Security Protocols. International Journal of Trend in Scientific Research and Development, 4 (6). pp. 1927-1945. ISSN 2456-6470

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Abstract

As organizations increasingly transition to cloud-based environments, the risk of cyberattacks, particularly ransomware, has escalated, posing significant threats to the confidentiality, integrity, and availability of critical data. The cloud era offers numerous benefits, including scalability, cost-efficiency, and flexibility; however, it also introduces new vulnerabilities and attack vectors. Ransomware, in particular, has emerged as one of the most dangerous and pervasive cyber threats, exploiting weaknesses in cloud infrastructures, endpoint security, and human error. This paper explores the evolving landscape of ransomware attacks in the cloud era and highlights the pivotal role of Artificial Intelligence (AI) in enhancing cybersecurity measures. By leveraging AI-powered tools, machine learning algorithms, and advanced security protocols, organizations can proactively detect, prevent, and mitigate ransomware attacks. AI enables faster identification of anomalous behavior, early detection of potential threats, and the automation of incident response, which are crucial in minimizing the impact of attacks. Furthermore, the paper examines the integration of advanced security protocols such as zero-trust architectures, encryption, and multi-factor authentication, alongside AI-driven defense mechanisms, to bolster cloud security against ransomware. The research underscores the importance of adopting a multi-layered, AI-powered approach to address the dynamic and evolving nature of cyber threats, ensuring resilience and continuous protection for organizations in the cloud era.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	21 Nov 2024 09:54
Last Modified:	21 Nov 2024 09:54
URI:	http://eprints.umsida.ac.id/id/eprint/14653

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