## 4 Experimental Results and Analysis
### Security Analysis  
The ECC-based model ensures robust protection against replay attacks by utilizing unique session keys for each communication. Additionally, the use of authenticated key exchange protocols mitigates man-in-the-middle attacks by verifying the legitimacy of all participating devices. These features make the model particularly suitable for securing IoT networks where communication involves highly sensitive data, similar as in [20]. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Algorithm** & **Key Exchange** & \
\begin{tabular}{c} **Power** \\ **Time (ms)** \\ \end{tabular} &
\begin{tabular}{c} **Security Level** \\ **(mW)** \\ \end{tabular} \\ \hline ASCON & 512 & 25 & medium \\ \hline SPONGET & 272 & 12 & medium \\ \hline ECC-160 & 98 & 12 & high \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparative evaluation with NIST general algorithms. The construction method of the proposed model highlights its inherent resilience, specifically tailored for IoT applications where resource constraints and diverse device capabilities pose significant challenges. The robustness of the method stems not only from the efficiency of its design but also from the meticulous way in which the subspaces over which the elliptic curves are defined are constructed. These subspaces form the foundation for parameterization, which directly influences the security and performance of the cryptographic primitives employed. By carefully selecting these subspaces, the model ensures that the cryptographic operations, such as key generation and key exchange, are both computationally efficient and secure against common attack vectors. A critical aspect of the model lies in the parameterization process. This involves defining the elliptic curves over finite fields, with specific constraints designed to optimize the balance between computational overhead and cryptographic strength. The choice of parameters, such as the curve coefficients and the size of the underlying field, ensures that the elliptic curve discrete logarithm problem (ECDLP) remains computationally infeasible for attackers, while still allowing efficient computation for resource-constrained IoT devices. This deliberate design choice is crucial in environments where devices range from low-power sensors to high-performance servers, as it guarantees uniform security across heterogeneous networks. Furthermore, the construction of the cryptographic primitives leverages these parameterizations to create a resilient system that can withstand various types of attacks. For example, the use of deterministic pseudo-random number generators in key generation not only minimizes the need for external entropy sources but also ensures the reproducibility and consistency of the keys within the defined subspaces. This approach reduces the risk of weak keys, which are often a consequence of poorly implemented randomness in constrained environments. Additionally, the modular arithmetic operations performed on the elliptic curve points are optimized to minimize computational latency, thereby enhancing the energy efficiency of the model without compromising its security guarantees. The resilience of the proposed model is further demonstrated by its ability to maintain synchronization across heterogeneous IoT devices. By employing a key propagation scheme, the model ensures that devices with varying computational capabilities can securely exchange keys without introducing significant delays or vulnerabilities. This synchronization mechanism is particularly important in large-scale IoT networks, where maintaining consistent security policies across devices is a significant challenge. The proposed approach mitigates potential vulnerabilities arising from desynchronization, such as unauthorized access or data breaches, by ensuring that all devices operate within a unified cryptographic framework.