International Journal of Mathematical, Engineering and Management Sciences Vol. 7, No. 1, 81-91, 2022 https://doi.org/10.33889/IJMEMS.2022.7.1.006 81 | https://www.ijmems.in A Step Towards Generation of DoS/DDoS Attacks Dataset for Docker- Centric Computing Aparna Tomar Department of Computer Science and Engineering, Graphic Era University, Dehradun, India. E-mail: aparnatomar29@gmail.com Preeti Mishra Department of Computer Science, Doon University, Dehradun, India. Corresponding author: scholar.preeti@gmail.com Rahul Bisht Department of Computer Science and Engineering, Graphic Era University, Dehradun, India. E-mail: me.rahul.bisht@gmail.com Peddoju Sateesh Kumar Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, India. E-mail: sateesh@ieee.org (Received on August 19, 2021; Accepted on December 23, 2021) Abstract Docker provides an effective containerized environment for modern computing. However, the security issues present in Docker provide an edge to the attackers thus resulting in various attacks. Denial of Service (DoS) and Distributed Denial of Service (DDoS) are the common ones. In this paper, DoS and DDoS attack datasets have been generated using realistic testbed environments as older datasets have their own set of limitations, making them insufficient for today’s computing. An architectural framework is provided to depict the process of packet capturing and feature extraction. A total of 45 features are extracted using Flowtbag among which 17 best features are selected using the average correlation coefficient. Six machine learning algorithms namely Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) are applied on datasets with full features and selected features to obtain accuracy, precision, recall, and F1 score. NB gave the lowest accuracy of 0.94917 on full features and DT provided the most accurate results with a performance matrix of 0.99254 accuracy, 0.997 precision, 0.998 recall, and 0.997 F1 Score. Whereas on selected features, accuracies of both the algorithms increased to 0.962434 and 0.992703 respectively. Keywords- Docker, Docker security, Docker swarm, Dataset generation, DoS/DDoS. 1. Introduction Cloud computing is one of the distributed computing paradigms which employs a decentralized computing framework by making use of the compute, network, and storage which are close to the users. The container technologies such as Docker provide a portable, high-performance, and lightweight alternative solution for hosting applications at edge servers. It makes Docker-based applications much faster than VM-based applications at the edges. However, security is a major loophole in Docker containers (White et al., 2021). A number of attacks can take place in the