ENHANCING AUTENTICATION MECHANISMS IN PUBLIC CLOUD ENVIRONMENTS THROUGH IMPROVISATION

computer engineering

Authentication mechanisms form the cornerstone of security in public cloud environments, ensuring the integrity and confidentiality of sensitive data. However, the evolving landscape of cybersecurity threats demands continuous adaptation and enhancement of these mechanisms. This paper proposes a novel approach to improvising authentication mechanisms in the public cloud, aiming to bolster security while maintaining usability and scalability. Drawing upon principles from improvisational theory, the proposed framework incorporates flexibility, adaptability, and responsiveness to dynamic threats. By leveraging techniques such as contextual analysis, behavioral biometrics, and machine learning, the system enhances authentication accuracy and resilience against emerging threats. Furthermore, this approach emphasizes user-centric design, prioritizing user experience without compromising security standards. Through a comprehensive analysis of existing authentication challenges in public cloud environments and a theoretical framework grounded in improvisation, this paper offers a novel perspective on enhancing security in the cloud. Experimental evaluations demonstrate the effectiveness and feasibility of the proposed approach, paving the way for future research and practical implementations in real-world cloud environments.

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