AI-Driven Container Security Approaches for 5G and Beyond: A Survey

Abstract

The rising use of microservices based software deployment on the cloud leverages containerized software extensively. The security of applications running inside containers as well as the container environment itself are critical infrastructure in the cloud setting and 5G. To address the security concerns, research efforts have been focused on container security with subfields such as intrusion detection, malware detection and container placement strategies. These security efforts are roughly divided into two categories: rule based approaches and machine learning that can respond to novel threats. In this study, we have surveyed the container security literature focusing on approaches that leverage machine learning to address security challenges.

14 pages, 2 tables, 1 figure, submitted to Special issue on AI-driven security in 5G and beyond

References in corpus (4)

• Applying Bag of System Calls for Anomalous Behavior Detection of Applications in Linux Containers
• Intrusion Detection System for Applications using Linux Containers
• Threat Modeling and Security Analysis of Containers: A Survey
• Ensemble of Random and Isolation Forests for Graph-Based Intrusion Detection in Containers