## 6 Discussion  
Our developed system model exploits the environmental noise and physical phenomena IoT sensors detect. This strategy differs from approaches that depend on deterministic hardware or data from human interactions, providing the benefit of smooth integration with current IoT set-ups, thus lowering expenses and simplifying operations. Moreover, while the natural unpredictability of the environmental sources our method employs might result in variations in the quality of randomness, it still serves as a viable option for extensive IoT deployments because of its affordability and straightforward incorporation. From a security standpoint, our proposal utilizes a blend of secure multiparty computation (SMPC) and one-time pads to boost cryptographic security, eliminating the need for intricate key agreement protocols. This proves especially beneficial in a distributed IoT setting, where handling key distribution can be problematic and insecure. Compared to methods dependent on conventional cryptographic protocols or sophisticated approaches like quantum key distribution (QKD), which may provide greater security but often sacrifice scalability and incur higher costs, our strategy aims to balance security and usability. It offers a scalable and sturdy framework that effectively manages cyber and physical threats, making it appropriate for the varied and frequently adverse environments in which IoT devices function. The SMP-OTF4 IOT protocol is introduced and implemented using ZeroC-Ice. The proposed procedure establishes a common key between IoT devices for secure communication. Two primary parties (\(P_{1}\) and \(P_{2}\)) and a dummy server (\(P_{3}\)) sequentially agree on a key \(K\) using true random numbers and a modified (but standard) multiparty security sum procedure, which is applied for encrypted communication with a single pad. The main contributions of this research include the innovative use of a dummy third party (\(P_{3}\)), whose role is crucial to facilitating the establishment of the key but does not have access to the shared encrypted message. This design enhances the security framework by reducing the number of entities accessing sensitive information, minimizing the potential for unauthorized data interception. The protocol exhibits a reduction in communication of a factor of approximately 30%. Furthermore, implementing our protocol in ZeroC-Ice offers significant advantages in connecting devices across different platforms and architectures with reduced complexity. This versatility is essential for the widespread adoption of secure communication protocols within heterogeneous IoT environments. A notable benefit of our approach is the marked efficiency in message transmission, where multiple parameters can be included in a single function call, thereby reducing bandwidth requirements and enhancing communication efficiency. The protocol exhibits a reduction in communication overhead of approximately 30%, a significant improvement that addresses one of the critical challenges in IoT environments: bandwidth conservation. In terms of security, although a formal security analysis of the protocol is deferred to a forthcoming article, we focus on its inherent security properties as implemented. Our protocol is evaluated using the Dolev-Yao threat model against semi-honest or dishonest adversaries. In the semi-honest scenario, the random numbers and their sums transmitted make it challenging for an adversary to deduce the key without knowledge of the exact computations performed by each party. For a dishonest attacker, any alteration in the transmitted random numbers could result in a different key, potentially flagging an interception attempt simply because the encrypted text will not be recovered. This research also addresses potential threats, such as side-channel attacks, which are mitigated through techniques such as random code injection, appropriate data formatting, and dynamic role changes.