# A Secured Intrusion Detection System for Mobile Edge Computing
## 5 Implementation and Results  
To assess the efficacy and functionality of the proposed framework, we employed NS-2 (Network Simulator 2) as the chosen tool for implementation. NS-2 is a versatile and widely adopted discrete event network simulator that provides a platform for the creation and evaluation of complex network scenarios. In this context, we specifically utilized NS-2 to implement a certificate authority (CA)-based intrusion detection system (IDS) tailored for mobile edge computing (MEC) environments. The utilization of NS-2 allows for the simulation and thorough examination of both security and performance aspects within a controlled and replicable environment. This choice of simulation tool facilitates the modeling of diverse network conditions and scenarios, enabling comprehensive testing of the CA-based IDS for MEC. Through NS-2, we can emulate various intrusion scenarios, assess the system's responsiveness to security threats, and evaluate its overall performance under different conditions. The use of NS-2 ensures a robust and versatile platform for the validation and refinement of the proposed framework, contributing to a more thorough understanding of its capabilities and limitations in the context of MEC security. The following parameters in Table 2 were used during the evaluation:  
Figure 2 demonstrates the superior performance of the proposed SEC-IDS system in accurately identifying attacks when compared to existing detection strategies like ZBIDS, EEACK-IDS, and SAZIDS. SEC-IDS showcases a 3.45% improvement by delivering the content with a ratio of 900 in 3 ms, which is a massive improvement over SAZIDS, a significant 12.14% enhancement over the current ZBIDS strategy, and an 8.28% higher detection rate than EEACK-IDS. Similarly, we also evaluated the detection rate and compared with existing approaches as shown in Figure 3.  
Figure 4 displays the assessment of the false alarm rate. The proposed SEC-IDS showcases its effectiveness in reducing the false alarm rate when contrasted with established exploration methods like ZBIDS, EEACK-IDS, and SAZIDS. SEC-IDS manifests a notable 20.18% improvement over SAZIDS, a significant 16% enhancement over EEACK-IDS, and an overall performance improvement of 9.95% by minimizing the FAR up to 1.2, which is ignorable in the given strategies. \begin{table}
\begin{tabular}{c c} \hline \hline
**Simulation Parameters** & **Value** \\ \hline Channel & Wireless Channel \\ MAC & 802.11 \\ Antenna Type & Omni Antenna \\ Routing protocol & AODV \\ Initial Energy & 100 Joules \\ Traffic Type & CBR \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters and perspective values. Figure 4: False alarm rate of the proposed model compared with existing models. Figure 3: Intrusion detection rate of the proposed model compared with existing models. Figure 2: Data delivery ratio of the proposed model compared with existing models. Figure 5 illustrates the assessment of the link change rate, revealing that SEC-IDS adepptly reduces this rate when compared to the established methods of ZBIDS, EEACK-IDS, and SAZIDS. SEC-IDS showcases a significant 16.16% improvement over SAZIDS, a substantial 45.8% enhancement over ZBIDS, and a notable 44% better performance than EEACK-IDS. The intrusion detection system (IDS) designed for edge computing and leveraging certificate authority introduces a robust security framework. This system capitalizes on certificate authority mechanisms to enhance the security posture of edge computing environments. The use of certificates ensures the authenticity and trustworthiness of entities within the edge network. By employing certificate-based validation, the IDS can effectively identify and respond to potential intrusions, safeguarding the integrity and confidentiality of edge computing resources. This approach establishes a secure foundation for edge computing operations, addressing the unique security challenges posed by decentralized and distributed computing environments.