## 7 Architectural Challenges in Designing Any Smart Healthcare Application
### IoT Privacy in Smart Healthcare  
Versatile privacy challenges arise in the real-time deployment of any smart healthcare applications or services. The significant privacy issues include location privacy, data privacy, resiliency, and identity threats [82]. Ensuring individual privacy is the essential requirement of IoT applications and services, as users' smart devices are connected to the Internet. There is an increased chance of stolen personal raw data with this connectivity. Widespread user adaption depends on the IoT ecosystem's privacy policies [105]. IoT device limitations and the complex heterogeneity of IoT technologies are the two primary bottlenecks hindering users' privacy. IoT devices are resource-constrained, unreliable, and operate at low data rates [106]. Many researchers have found that IoT devices as weak access points which can leak sensitive data. Thus, network-based privacy approaches are better than host-based approaches, and traditional defense systems for IoT privacy cannot serve the purpose [107]. Communication of heterogeneous technologies and devices poses challenges in designing and deploying IoT privacy policies [11]. Significant privacy challenges of IoT ecosystems are presented as:  
* User identification.
* User tracking.
* Profiling.
* Utility monitoring and controlling.  
Privacy preservation in the IoT environment is challenging, as there are no well-defined ecosystem boundaries. Users' data are stored only when they are highly needed. The solutions of IoT privacy preservation for these challenges are:  
* Lightweight authentication.
* Device fingerprinting techniques.
* Context-aware access control.
* Edge computing software modules.
* Privacy-aware systems of user data.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layers of IoT** & **Layers of IoT** & \\
**Interoperability Model** & **Interoperability Model** & **Feature of Layer** \\
**in [102]** & **in [103]** & \\ \hline Connection & No connection & No interoperability between systems \\ \hline Communication & Technical & Basic Network connectivity \\ \hline Semantic & Syntactical & Data exchanging \\ \hline Dynamic & Semantic & Understanding the meaning of the data \\ \hline Behavioral & Programmatic/Dynamic & Application of information \\ \hline Conceptual & Conceptual & Shared view of the world \\ \hline \hline \end{tabular}
\end{table}
Table 7: Interoperability layers and features.  
* Decentralized clouds.
* Data brokers and separation algorithms.
* Denaturing frameworks.
* Data mining.
* Data summarization.  
Some privacy-enhancing technologies are virtual private networks, transport layer security, DNS security extensions, onion routing, and private information retrieval. The Privacy by Design (PbD) scheme can mitigate issues arising from device limitations. Secure data communications, anonymous transmission, and data hiding are some of the practices of PbD. Privacy-enhancing techniques and Privacy by Design techniques achieve confidentiality and anonymity [10]. There are some challenges in privacy regulations of IoT, namely, privacy infringement determination, data and context quality, data transparency and minimization requirement identification, interoperability, and connectivity acknowledgments.