## 4 Experimental Results and Analysis  
To evaluate the performance of the adapted ECC algorithm, three categories of representative IoT devices were created, used in the following scenarios:  
1. Low Power Devices (LPD): environmental sensors and monitoring devices with severe computing and memory limitations (for example, sensors based on ARM Cortex-M0 type microcontrollers), limited to 128 KB memory and operating at 48 MHz. 2. Medium Power Devices (MPDs): intermediate devices such as gateways with more advanced microcontrollers (eg ARM Cortex-M4) with moderate processing capabilities, featuring 1 MB memory and a clock speed of 120 MHz. 3. High Power Devices (HPD): servers and advanced computing equipment, such as ARM Cortex-A53 processors, with 4 GB memory and a clock speed of 1.5 GHz. The algorithm was tested in a simulated network environment, with 100 nodes distributed proportionally between the three categories, all being interconnected and the communications encrypted through the session keys generated according to the previously described ECC protocol. In the evaluation of the performance and viability of the algorithm implementation, several essential metrics were monitored. One of the main aspects evaluated was the key generation time, which represents the time required for each device to produce a pair of keys (private and public). This measures the efficiency of the algorithm in generating cryptographic keys, an essential process in establishing the security of a system. The key exchange time was also measured, which indicates the total interval required for two devices to complete the key exchange process and calculate the common session key. This is a crucial parameter in evaluating the efficiency of the algorithm in IoT communication scenarios, where latency can affect overall performance. Figure 3: Parameter contraction on elliptic curve for secure key exchange in IoT. Another important factor monitored was energy consumption, measured in milliwatts (mW), which reflects the amount of energy used by devices during key generation and exchange. Considering the resource restrictions of many IoT devices, this parameter is essential to ensure the long-term sustainability of the implemented cryptographic solutions. The energy consumption calculation model followed the formula \(E_{total}=E_{com}+E_{comp}\), where \(E_{com}\) is the energy consumed for communication (e.g., transmitting and receiving data packets) and \(E_{com}\) is the energy consumed for computational operations (e.g., key generation and encryption). Energy consumption was simulated using a hardware-specific energy model derived from the datasheets of the devices used. The total energy consumption was calculated as the sum of communication energy (\(E_{com}\)) and computational energy (\(E_{comp}\)). For communication, the simulation accounted for the transmission power and packet size, while for computation, it considered the clock speed and number of cryptographic operations performed. In the simulations, the \(NS3\) version 3.43 software was used and in the practical applications, an instrument was used to measure the accumulator values at the start and end of the operation. The memory occupied by each device during the execution of the algorithm was also evaluated, i.e., the space required to store the keys and to operate its own cryptographic process. This was an important measure, considering the hardware limitations of IoT devices, which can have reduced storage and processing capacities. The obtained results are presented in Table 1 and show how each category of devices performs with the proposed ECC algorithm. As shown in Table 2, the experimental results demonstrate a balanced trade-off between resource consumption and security performance across different IoT device categories. Specifically, while LPD devices exhibit a longer key exchange time (120 ms) and lower energy consumption (5 mW), they still comply with the security requirements of the proposed protocol.