# Tokens Shuffling Approach for Privacy, Security, and Reliability in IoHT under a Pandemic
###### Abstract  
Privacy and security are unavoidable challenges in the future of smart health services and systems. Several approaches for preserving privacy have been provided in the Internet of Health Things (IoHT) applications. However, with the emergence of COVID-19, the healthcare centers needed to track, collect, and share more critical data such as the location of those infected and monitor social distancing. Unfortunately, the traditional privacy-preserving approaches failed to deal effectively with emergency circumstances. In the proposed research, we introduce a Tokens Shuffling Approach (TSA) to preserve collected data's privacy, security, and reliability during the pandemic without the need to trust a third party or service providers. TSA depends on a smartphone application and the proposed protocol to collect and share data reliably and safely. TSA depends on a proposed algorithm for swapping the identities temporarily between cooperated users and then hiding the identities by employing fog nodes. The fog node manages the cooperation process between users in a specific area to improve the system's performance. Finally, TSA uses blockchain to save data reliability, ensure data integrity, and facilitate access. The results prove that TSA performed better than traditional approaches regarding data privacy and the performance level. Further, we noticed that it adapted better during emergency circumstances. Moreover, TSA did not affect the accuracy of the collected data or its related statistics. On the contrary, TSA will not affect the quality of primary healthcare services. protection; health; medical; preserving; attacks; TSA +
Footnote †: journal:  
+++ ==WARNING: Truncated because of repetitions==
addressing the pandemic challenges [13]. The most effective solutions in a virus situation are maintaining social distancing, tracking the infected, real-time monitoring, depending on online services to reduce human mingling, observing people's adherence [14], etc. This is in addition to the medical research that focuses on understanding the virus and its properties. However, new technologies have a dark side, too; this is related to the security and privacy of users' data. It is a critical challenge facing these technologies' future [15]. Unfortunately, most of the research about COVID-19 did not care about this issue (privacy and security of data) due to the exceptional circumstance. Collecting data and finding functional services or applications were the main goals for facing the pandemic [16]. Moreover, most of the provided solutions and applications rely on location-based services (LBS) [17]. So, an attacker or malicious third party can collect the spatial data and then analyze it to detect a lot of sensitive and personal data for each user, such as his behavior, job, home, religion, average income, and ethics, to name a few [18]. Unfortunately, the current approaches and methods of preserving data privacy and security are not suitable for exceptional cases (pandemic situations). This is because they affect the quality of the main service (QoS of Health), affecting the accuracy of the data and service performance. In addition, some protection techniques do not provide enough protection, and most do not care about the reliability of the data, which is critical in the health domain [19]. Therefore, we proposed a novel approach for user data, ensuring the main trinity (privacy, security, and reliability of user data) in a pandemic such as COVID-19. Our solution will not affect the results and accuracy of the applications in the health domain. The proposed solution will pave the road for other researchers to find new ideas on privacy during a pandemic. The contributions of this work are:  
* Proposing a new approach called TSA for preserving privacy in IoHT during the pandemic, especially for LBS. This approach (TSA) will not affect the accuracy of the main services such as health services. * Enhancing the performance by depending on fog computing and users' devices computing (Dev computing).