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Abstract

This paper examines the confluence of cybersecurity advancements and virtual tourism in the context of post-pandemic China.As virtual tourism emerges as a viable alternative in the wake of travel restrictions, ensuring the security and sustainability of virtual tourism platforms becomes paramount.Leveraging insights from the field of wireless cyber-physical systems (CPS), particularly advanced attack detection and data generation techniques using self-training powered generative adversarial networks (GANs), this study proposes a novel approach to fortifying virtual tourism platforms against cyber threats.Drawing upon case studies and empirical data, we explore the application of self-training powered GANs as a means to enhance security in virtual tourism platforms, considering the unique challenges posed by the dynamic landscape of post-pandemic tourism.By synthesizing realistic yet synthetic data through GANs, virtual tourism platforms can bolster their defenses against a myriad of cyber attacks, safeguarding sensitive user information and ensuring uninterrupted service delivery.Furthermore, we analyze the implications of implementing such security measures within the context of post-pandemic China, considering the country's burgeoning virtual tourism industry and its potential to shape global tourism trends.Our findings underscore the importance of proactive cybersecurity measures in fostering trust and confidence among virtual tourists, thereby facilitating the sustainable growth of virtual tourism in the aftermath of the COVID-19 pandemic.Through this interdisciplinary exploration, we aim to provide valuable insights for policymakers, industry stakeholders, and cybersecurity professionals seeking to navigate the evolving landscape of virtual tourism while mitigating associated security risks.Ultimately, by embracing innovative approaches to cybersecurity, virtual tourism platforms can not only thrive in the post-pandemic era but also contribute to the broader goal of building resilient and secure digital ecosystems.

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Publication details

DOI
10.31234/osf.io/vejgx
OpenAlex
W4392002073
Document type
preprint
Language
EN
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