Intrusion Detection Systems for Enhanced Security in Mobile Edge Computing: A Systematic Review and Survey of the Applications, Challenges, and Future Directions

Mobile Edge Computing (MEC) presents a paradigm shift in the field of computing, where processing and data storage capabilities are extended to the edge of the network, closer to end users and Internet of Things (IoT) devices. The adoption of MEC not only speeds up response times but also boosts the effectiveness of applications that handle large amounts of data. However, the rise of MEC also introduces new challenges in network security, as the decentralized structure of edge computing reveals weak spots that could be targeted by hackers. To address this, Intrusion Detection Systems (IDS) are proving to be an effective solution in protecting MEC environments. These systems are specifically designed for MEC to quickly identify and counter security threats, thus reducing risk and maintaining the reliability of edge networks. This systematic review explores MEC-based IDS strategies. The novelty of this review is its focus on the integration of intrusion detection strategies within the MEC architecture. It highlights the importance of combining security and computing functions at the edge, which is essential for the proper functioning of IoT applications. We analyze a broad range of existing studies, highlighting the various approaches, deployment settings, and performance indicators of these IDS solutions. Additionally, we critically evaluate their advantages and limitations, providing insights into their adaptability, effectiveness, and scalability in different network conditions.