Spatial Digital Twins (SDTs) are digital replicas that integrate physical entities with their virtual counterparts, leveraging data analytics for various applications. This article examines their components, emphasizing the critical role of security and privacy protocols in managing sensitive information, especially location data. The study highlights the necessity of ensuring reliability and transparency in SDTs to facilitate data-driven decisions while addressing the risks associated with identifying individuals through location tracking. Future developments should aim to mitigate these challenges through innovative solutions.
Researchers underscore the necessity of robust security and privacy measures in digital twins to foster trust and enable efficient data-driven decision-making.
Key security and privacy challenges in digital twins directly extend to spatial digital twins, necessitating rigorous frameworks to safeguard sensitive location data.
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