Learning Environment Containerization of Machine Leaning for Cybersecurity

Machine learning plays a critical role in detecting and preventing in the field of cybersecurity. However, many students have difficulties on configuring the appropriate coding environment and retrieving datasets on their own computers, which, to some extent, wastes valuable time for learning core c...

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Bibliographic Details
Published in2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC) pp. 1131 - 1132
Main Authors Shahriar, Hossain, Qian, Kai, Zhang, Hao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2020
Subjects
Computer security
Containerization
Containers
Cybersecurity
Docker
Logistics
Machine learning
Machine learning algorithms
Prediction algorithms
Python
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DOI10.1109/COMPSAC48688.2020.0-105

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Summary:Machine learning plays a critical role in detecting and preventing in the field of cybersecurity. However, many students have difficulties on configuring the appropriate coding environment and retrieving datasets on their own computers, which, to some extent, wastes valuable time for learning core contents of machine learning and cybersecurity. In this paper, we propose an approach with learning environment containerization of machine learning algorithm and dataset. This will help students focus more on learning contents and have valuable hand-on experience through Docker container and get rid of the trouble of configuration coding environment and retrieve dataset. This paper provides an overview of case-based hands-on lab with logistic regression algorithm for credit card fraud prediction.
DOI:10.1109/COMPSAC48688.2020.0-105