Multi-Key Asymmetric Cryptography: A Model for Preserving Privacy in Work-from-Home Environments

Abstract

In the contemporary landscape of work, the transformative shift towards remote work has necessitated an investigative analysis of the privacy and security challenges associated with the exchange of sensitive information. This research paper responds to this imperative by introducing a pioneering privacy-preserving model, specifically tailored for Work-from-Home (WFH) environments, leveraging the capabilities of Multi-Key Asymmetric Cryptography.  The model's innovation lies in its strategic synthesis of the efficiency inherent in symmetric encryption with an unwavering emphasis on the preservation of privacy. This nuanced approach positions the model as a robust solution to the dynamic and evolving cybersecurity threats faced by remote workers, offering a comprehensive defence mechanism against potential breaches and unauthorised access to sensitive data. The paper conducts a comprehensive analysis, delving into the foundational principles, distinct advantages, implementation considerations, and real-world benefits of the proposed privacy-preserving model. The examination of foundational principles elucidates the theoretical underpinnings, establishing a clear conceptual understanding of the model's architecture and functionality. The exploration of advantages underscores how the model not only addresses existing concerns but also provides additional layers of protection and adaptability to future cybersecurity challenges. The implementation considerations delve into practical aspects, discussing the feasibility and potential challenges of seamlessly integrating the privacy-preserving model into existing WFH infrastructures. Extending the analysis to real-world benefits, the research paper highlights the possible tangible impact and value the proposed model brings to organisations and remote workers. This encompasses enhanced data security, improved privacy compliance, and increased confidence in the integrity of remote work systems.