Lightweight intrusion detection improves KubeEdge service availability
Improving Service Availability in KubeEdge-Based Architectures Using Lightweight Intrusion Detection
Cryptography and SecuritySoftware Engineering
Summary
As more devices get connected to the internet, it's important to keep the systems managing them safe and running well. The authors looked at how security attacks can affect a system called KubeEdge that helps manage devices at the network edge. They created a simple but effective way to detect bad activity quickly, even on devices that don't have a lot of power. Their method helps the system stay up and recover faster when under attack.
What this means in practice
- •For edge system engineers: Enhance the security of KubeEdge clusters by integrating a lightweight intrusion detection rule set that reduces downtime from attacks.
- •For iot infrastructure operators: Maintain higher service availability for IoT applications by detecting and mitigating denial of service and malicious container threats at the edge.
Authors
Harrol Ndjeudji Kuibou, Mostafa Anouar Ghorab, Mohamed Aymen Saied
Abstract
The increasing adoption of the Internet of Things (IoT) and cloud computing has accelerated the evolution of edge computing paradigms [1]. Industry forecasts estimate that the number of connected IoT devices will reach approximately 50 billion by 2030, following an estimated 38 billion connections by 2025 [34], resulting in an unprecedented growth in data generation. This trend necessitates efficient, scalable, and secure data processing mechanisms at the network edge. Consequently, ensuring the reliable management and protection of IoT applications and devices has become a critical challenge. In this context, KubeEdge extends cloud-native capabilities to edge environments, enabling distributed orchestration while introducing new security concerns. This paper investigates the security of container images in IoT-driven and distributed edge architectures. Specifically, we analyze the impact of major security threats, including Denial of Service (DoS) attacks and malicious container deployments, on the availability and operational stability of KubeEdge-based systems. To address these challenges, we propose a lightweight Recommended Intrusion Detection Rule Set (RIDRS) tailored for resource-constrained edge environments. The proposed approach improves system resilience by enabling timely detection and mitigation of security threats. We define system stability as the ability to maintain consistent operational behavior and to recover autonomously under adversarial conditions. Experimental results demonstrate that RIDRS significantly reduces system downtime and enhances service availability, particularly in scenarios involving code injection and malicious pod deployment attacks.