Container Anomaly Detection Using Neural Networks Analyzing System Calls

被引：5

作者：

Gantikow, Holger ^{[1
]}

Zoehner, Tom ^{[1
]}

Reich, Christoph ^{[1
]}

机构：

[1] Furtwangen Univ Appl Sci, Inst Data Sci Cloud Comp & IT Secur, Furtwangen, Germany

来源：

2020 28TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING (PDP 2020) | 2020年

关键词：

Container Security; Anomaly Detection; Neural Networks;

D O I：

10.1109/PDP50117.2020.00069

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：408 / 412

页数：5

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