# A Survey on Formal Verification and Validation Techniques for Internet of Things
## 9 Conclusions and Future Work  
In conclusion, FV&V techniques have the potential to address the challenges of reliability and security in IoT systems. However, the dynamic and heterogeneous nature of IoT systems presents several challenges for applying these techniques. Researchers have developed various techniques, such as abstraction, modularization, symmetry detection, and TAs, to address these challenges. However, there is still a need to develop more-efficient and -effective techniques that can handle the complex interactions and dependencies that exist in IoT systems. Moreover, there is a need for a cultural shift towards a more-formalized approach to software development, where FV&V techniques are integrated into the development process. One possible direction for future research is the development of more-sophisticated formal models and verification techniques that can handle the dynamic and heterogeneous nature of IoT systems. For example, researchers could develop models that capture the interactions and dependencies between devices and networks, as well as the context and environment in which the system operates. They could also develop verification techniques that can handle the large number of states and events that occur in IoT systems, while also maintaining performance and scalability. Another possible direction is the development of tools and frameworks that make it easier to apply FV&V techniques in the development process. These tools could automate the process of model generation and verification, reducing the manual effort required and improving the accuracy and reliability of the models. Moreover, there is a need to develop more-comprehensive standards for IoT devices and networks that can improve the accuracy and reliability of formal models. Standardization can also enable interoperability between devices and networks, improving the scalability and flexibility of IoT systems. Finally, there is a need to investigate the use of machine learning and artificial intelligence techniques in conjunction with FV&V techniques [81; 82; 83; 84]. These techniques can help identify patterns and anomalies in IoT systems, improving their reliability and security. In addition to the future directions discussed above, there are two more directions that warrant further investigation in the context of FV&V for IoT systems. Firstly, the incorporation of novel AI techniques in dynamic and heterogeneous IoT systems is an area of great interest. Specific AI algorithms, such as federated learning and 0 NKP, have shown promise in improving the security of IoT systems. Researchers could explore the integration of these techniques into formal models and verification techniques to detect vulnerabilities and ensure the safety and security of IoT systems. Secondly, there is a need to provide more details related to post-quantum security [85]. With the potential impact of quantum computing on IoT security, it is crucial to investigate post-quantum security mechanisms and protocols. Researchers could explore the use of formal methods in conjunction with these techniques to ensure the safety and security of IoT systems in the face of emerging threats. With these future directions in mind, the continued research and development of FV&V techniques for IoT systems will require collaboration between researchers, developers, and industry stakeholders. By addressing the challenges and open issues discussed in this paper, FV&V techniques can help ensure the reliable and secure operation of IoT systems, enabling their full potential to be realized. In summary, FV&V techniques offer a promising approach to ensuring the reliability and security of IoT systems. Addressing the challenges and open issues discussed in this paper will require a concerted effort from researchers, developers, and industry stakeholders. With continued research and development, FV&V techniques can help realize the full potential of IoT systems in a safe and secure manner. This research received no external funding.