## 8 Discussion
The analysis shows that using the TOR Network for broker/customer MQTT communication offers significant privacy benefits, including IP address anonymization, enhanced security through multilevel encryption, and access to censored regions. However, it also introduces challenges such as higher latency, reduced bandwidth, less reliable connections, and increased complexity in setup and maintenance. While our study does not explicitly model all aspects of the peer-to-peer nature of the Dark Net, our results do reflect some of its implications, including the effects of decentralized routing, network resilience, and scalability challenges. These observations open up avenues for future research to more directly quantify and analyze these peer-to-peer characteristics in the context of IoT communications. In this section, we compare the strengths and weaknesses of various approaches to privacy and security in IoT systems, including both our proposed method and several key works from the literature. The comparison focuses on qualitative aspects such as privacy, security, scalability, and ease of implementation without delving into specific performance metrics that require empirical validation. The Table 3 highlights the differences between our approach and other state-of-the-art methods. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Approach** & **Strengths** & **Weaknesses** \\ \hline
**Our Approach** & High privacy and anonymity, high security, medium scalability for sensitive IoT applications & Medium implementation complexity, slightly higher latency compared to less secure solutions \\ \hline
**[PERSON] et al. [4]** & High privacy and security, optimized for IoT environments & High implementation complexity, requires sophisticated infrastructure \\ \hline
**[PERSON] et al. [6]** & High scalability, good integration with blockchain for security & Medium latency, lower throughput compared to other approaches \\ \hline
**[PERSON] et al. [8]** & Good security, easy implementation & Less robust privacy, reduced performance in high-latency environments \\ \hline
**[PERSON] et al. [9]** & Easy to implement, good compatibility with existing systems & Limited privacy and security, lower resistance to attacks \\ \hline
**[PERSON] et al. [7]** & High privacy and anonymity due to the use of TOR, excellent security & High latency, high implementation complexity \\ \hline \end{tabular}
\end{table} 
Table 3: A qualitative comparison of various approaches. Our method provides strong privacy and anonymity features, with high security and medium scalability for IoT applications that require sensitive data handling. However, this comes with moderate implementation complexity and slightly higher latency compared to approaches that prioritize performance over security. The works of [PERSON] et al. [4] and [PERSON] et al. [6] emphasize privacy and security, but they differ in terms of implementation complexity and throughput. [PERSON] et al. focus on optimized security for IoT environments, which comes at the cost of high implementation complexity. [PERSON] et al. integrate blockchain technology for enhanced security, offering high scalability but with medium latency and reduced throughput. Other works, such as [PERSON] et al. [8] and [PERSON] et al. [9], present easier-to-implement solutions with good compatibility for existing systems, but they trade off some level of privacy and security. Finally, [PERSON] et al. [7] offer an approach with excellent privacy and security through the use of TOR, though it introduces higher latency and greater implementation complexity due to the additional layers of anonymity. This comparative analysis provides a clear overview of the advantages and trade-offs associated with each approach, helping to contextualize our work within the broader landscape of IoT security and privacy solutions.