# A Secured Intrusion Detection System for Mobile Edge Computing
## 2 Literature Review
### Related Work
Each zone is equipped with zone-specific intrusion detection modules and customized rulesets, enabling targeted threat detection. The system generates real-time alerts upon detecting suspicious activities, triggering automated responses based on the severity of the threat. Security policies are defined for each zone, guiding the acceptable and unacceptable activities within that segment. ZIDS enforces these policies to ensure compliance with predefined rules and regulations. The model maintains comprehensive logs of network activities and detected intrusions, providing detailed reports for post-incident analysis and continuous security improvement. The ZIDS model is scalable, making it adaptable to diverse network environments and varying security needs. Overall, ZIDS offers a robust and hierarchical approach to intrusion detection, enhancing the security posture of networked systems. Similarly, authors in [21] proposed the EEACK-IDS (enhanced energy-aware clustering and key management-based intrusion detection system) model as an innovative intrusion detection framework designed for wireless sensor networks (WSNs). It combines energy-efficient clustering and key management techniques to enhance the overall security and energy efficiency of WSNs. EEACK-IDS employs an energy-efficient clustering approach to organize sensor nodes into clusters, minimizing energy consumption and prolonging the network's operational lifetime. The model incorporates robust key management mechanisms to secure communication within and between clusters. Key distribution and updating strategies enhance the resilience of the network against potential attacks. EEACK-IDS integrates an intrusion detection system that continuously monitors network activities to identify and respond to potential security threats. The model introduces enhanced security measures to protect against various types of attacks, including data tampering, eavesdropping, and node compromise. EEACK-IDS undergoes performance evaluation to assess its effectiveness in terms of intrusion detection accuracy, energy consumption, and network lifetime. The model aims to achieve a balance between security and energy efficiency, making it suitable for resource-constrained WSNs. Another security-related IDS model, SAZIDS (smart ant colony-based zone intrusion detection system), was proposed in [22]. The model is an innovative intrusion detection framework designed for wireless sensor networks (WSNs). It leverages the principles of ant colony optimization to create an intelligent and adaptive system for detecting intrusions in WSNs. The model organizes the WSN into distinct zones, each with its own set of security requirements. Ant agents patrol these zones, monitoring network activities and identifyingpotential intrusions. SAZIDS prioritizes energy efficiency, a critical consideration for resource-constrained WSNs. The intelligent ant agents optimize their routes and activities to minimize energy consumption while maintaining effective intrusion detection. The decentralized nature of SAZIDS enhances its scalability and resilience [23]. Ant agents operate autonomously, contributing to the robustness of the intrusion detection system. SAZIDS undergoes performance evaluation to assess its effectiveness in terms of intrusion detection accuracy, energy efficiency, and adaptability to changing network conditions.