# Tokens Shuffling Approach for Privacy, Security, and Reliability in IoHT under a Pandemic
## 3 Proposed Approach (TSA)
### Algorithm of TSA
The proposed approach is ideal for applications for protecting privacy in pandemic situations, especially location-based medical services, in order to prevent the spread of infection. Still, it may not be the best option in many applications requiring the user to constantly communicate with the service provider. On the other hand, the user's dependence on storing data on his device may sometimes lead to data loss. Still,

\[\text{E}=-\sum_{i=0}^{\text{k}}\text{Pi}*\text{Log2}(\text{Pi})\]3 Performance Level Comparison based on Time. with the development of cloud services, the user can store these data in an encrypted form within his cloud to protect them and to provide them when needed. ## 5 Case Study--Saudi Arabia

The fresh solutions for pandemics (such as COVID-19) have depended on IoT tools and AI techniques--for example, tracking people and determining the best candidate to have infection according to the rate of intersection with infected persons (by temporal and spatial data from Google-MAP or TWAKALNA \"\(\mid\)S\(\mid\)S\"). The proposed algorithms will use the previous information in addition to medical centers' data to predict the number of potentially infected people. In addition, it is essential to track the exact sites visited by the infected during their incubation period before their quarantine. We could predict that people could carry COVID-19; if the person has multiple interactions with the infected, that means that he is a strong candidate to be infected. Figure 6 depicts the mechanism of action for medical systems during COVID-19. So, TSA can be applied in this scenario to enhance the privacy, security, and reliability of data without affecting the main services. ## 6 Conclusions

This work introduced a new approach, called TSA, to maintaining the security, privacy, and reliability of data collected during epidemics. TSA collected data without the drawbacks of traditional data protection methods (adverse impacts on service accuracy or performance). TSA employed fog nodes and the users' hardware to improve performance, reduce the load on the SP, and ultimately enhance users' privacy. The token exchange method contributed to protecting the identity of users and preventing them from profiling or tracking. Through simulation and discussion, we demonstrated TSA's superiority over popular and main approaches to preserving privacy and security. TSA achieved full misleading (100% uncertainty rate) for the attacker about users' data. As a future development, we will develop a comprehensive work platform and standard medical protocol for working during pandemics. This platform will apply TSA. Finally, we will introduce a comprehensive security approach based on machine learning algorithms to deal with different LBS applications and services. Conceptualization, N.B., A.B., S.S. and A.A.A.S. ; Methodology, N.B. and S.S.; Software, N.B. ; Validation, N.B. ; Formal analysis, N.B. and A.A.A.S. ; ResouWrees, A.B. and S.S.; Writing--original draft, N.B. ; Writing--review & editing, A.B., S.S. and A.A.A.S. ; Supervision, S.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. \[\text{E}=-\sum_{i=0}^{\text{k}}\text{Pi}*\text{Log2}(\text{Pi})\]4 Scenario for Dealing with a Pandemic before Applying TSA for Protection. ## References

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