AI-driven container security approaches for 5G and beyond: A survey

Date

2023-06-01

Author

Aktolga, Ilter Taha
Kuru, Elif Sena
Sever, Yiğit
Angin, Pelin

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The rising use of microservice-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 for infrastructure in cloud settings and 5G. To address 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 survey the container security literature focusing on approaches that leverage machine learning to address security challenges.

Subject Keywords

Anomaly detection, Container, Intrusion detection, Machine learning

URI

https://www.itu.int/pub/S-JNL-VOL4.ISSUE2-2023-A25
https://hdl.handle.net/11511/107252

Collections

Department of Computer Engineering, Article