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Container Anomaly Detection Using Neural Networks Analyzing System Calls

  • Container environments permeate all areas of computing, such as HPC, since they are lightweight, efficient, and ease the deployment of software. However, due to the shared host kernel, their isolation is considered to be weak, so additional protection mechanisms are needed.This paper shows that neural networks can be used to do anomaly detection by observing the behavior of containers through system call data. In more detail the detection of anomalies in file and directory paths used by system calls is evaluated to show their advantages and drawbacks.

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Metadaten
Author:Holger Gantikow, Tom Zöhner, Christoph ReichORCiDGND
DOI:https://doi.org/10.1109/PDP50117.2020.00069
ISBN:978-1-7281-6582-0
Parent Title (German):2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing : PDP 2020, 11-13 March 2020, Västerås, Sweden
Document Type:Conference Proceeding
Language:English
Year of Completion:2020
Release Date:2020/05/19
Tag:Anomalieerkennung; Container; Neuronale Netze
Pagenumber:5
First Page:408
Last Page:412
Open Access:Innerhalb der Hochschule
Licence (German):License LogoEs gilt das UrhG