# A Secured Intrusion Detection System for Mobile Edge Computing
## 1 Introduction  
The rapid proliferation of mobile computing has revolutionized the way users interact with information technology, ushering in an era of unprecedented connectivity and pervasive computing. With the advent of resource-constrained devices and the burgeoning demand for low-latency applications, mobile edge computing (MEC) has emerged as a paradigm-shifting technology, pushing computational capabilities closer to end-users [1; 2; 3]. While MEC offers numerous benefits, its unique characteristics also pose distinct security challenges, necessitating innovative solutions to safeguard the integrity and confidentiality of data processed at the edge. In this context, the focus of this paper is on the development and exploration of a cutting-edge solution: a secured edge-based intrusion detection framework tailored explicitly for mobile computing environments. Securing intrusion detection systems (IDSs) in the context of mobile edge computing (MEC) introduces a myriad of challenges and considerations. The convergence of mobile devices with edge computing resources creates a dynamic environment where traditional security measures may fall short. One notable concern is the increased attack surface due to the distributed nature of MEC, making it imperative to safeguard communication channels and data exchanges. Mobile devices, being inherently vulnerable to diverse cyber threats, amplify the need for robust intrusion detection mechanisms. Additionally, the reliance on wireless communication within MEC introduces potential vulnerabilities, emphasizing the necessity for secure transmission protocols and encryption. The integration of edge resources in processing and storing sensitive information calls for stringent access controls and authentication mechanisms to thwart unauthorized access. Furthermore, the seamless integration of signature-based and anomaly-based detection in MEC's IDS introducescomplexities in ensuring real-time responsiveness without compromising accuracy. As MEC environments operate in a resource-constrained setting, optimizing intrusion detection algorithms for efficiency becomes paramount. Addressing these security challenges requires a holistic approach, encompassing cryptographic protocols, secure communication channels, access controls, and tailored intrusion detection strategies to fortify the resilience of mobile edge computing against evolving cyber threats. The central objective is to fortify the security posture of MEC by introducing a robust and adaptive intrusion detection system that leverages the capabilities of edge computing resources [4]. The need for such a framework arises from the dynamic nature of MEC environments, where the edge serves as the focal point for data processing and communication. Conventional intrusion detection systems designed for traditional computing infrastructures may not seamlessly translate to the intricacies of edge computing, necessitating a dedicated approach that aligns with the unique characteristics and constraints of mobile computing environments. The contribution of this paper can be summarized as follows:  
* This paper proposes a secured edge computing-based intrusion detection system (SEC-IDS) approach to intrusion detection, acknowledging the significance of real-time responsiveness and low-latency decision-making in mobile computing scenarios. * By distributing intrusion detection tasks closer to the data source, the framework aims to reduce the impact of latency, enhance the scalability of the system, and improve overall network security. * Furthermore, our proposed framework incorporates a hybrid detection approach, combining signature-based and anomaly-based techniques. This amalgamation enables the system to detect both known attack patterns and previously unseen threats, thereby providing a comprehensive defense against a diverse range of cyber threats.