A comparative study of machine learning tools for detecting Trojan horse infections in cloud computing environments

Aug 2, 2026

Upload by Ezra

Cloud computing provides scalable resources and easy access to applications, but its openness also increases exposure to serious threats, including cloud Trojan horse infection attacks. Machine learning offers an effective way to identify such malicious activity by learning from data rather than relying only on static signatures. This study compares Weka and Python Colab for detecting Trojan horse infections in a control lab environment, evaluating recall, accuracy, F1-score, and computational resources across multiple algorithms, and interpreting the tools’ strengths and limitations.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Introduction

Cloud computing benefits and security concerns

Threat landscape and cloud Trojan injection attacks

Comparative evaluation (Weka vs Python Colab)

Metrics: recall, accuracy, and F1-score

Computational resource requirements

Findings and tool selection guidance

A comparative study of machine learning tools for detecting Trojan horse infections in cloud computing environments Hasan Kanaker1, Monther Tarawneh2, Nader Abdel Karim3, Adeeb Alsaaidah4, Maher Abuhamdeh5, Osama Qtaish6, Essam Alhroob1, Zaid Alhalhouli7 1Department of Cyber Security, Faculty of Information Technology, Isra University, Amman, Jordan 2Department of Information Technology, College of Information Technology, Tafila Technical University, Altafila, Jordan 3Department of Intelligent Systems, Faculty of Artificial Intelligence, Al-Balqa Applied University, Al-Salt, Jordan 4Department of Networks and Cyber Security, Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan 5Department of Computer Information System, Faculty of Information Technology, Isra University, Amman, Jordan 6Department of Software Engineering, Faculty of Information Technology, Isra University, Amman, Jordan 7Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Isra University, Amman, Jordan Article history: Received May 2, 2024 Revised Jul 20, 2024 Accepted Aug 6, 2024 Keywords: Cloud computing Control lab Cybersecurity Machine learning Python Trojan horse infection Weka Corresponding Author: Cloud computing offers several advantages, including cost savings and easy access to resources, it is also could be vulnerable to serious security attacks such as cloud Trojan horse infection attacks. To address this issue, machine learning is a promising approach for detecting these threats. Thus, different machine learning tools and models have been employed to detect Trojan horse infection such as Weka and Python Colab. This study aims to compare the performance of Weka and Python Colab, as popular tools for building machine learning models. This study evaluates the recall, accuracy, and F1-score of machine learning models built with Weka and Python Colab and compares their computational resources required employing several machine learning algorithms. The dataset collected and analyzed using dynamic analysis of Trojan horse infection in control lab environment. The findings of this study can help determine the decision about which tool to use to detect Trojan horse infections and provide insights into the strengths and limitations ofWeka and Python Colab for building machine-learning models in general. This is an open access article under the CC BY-SA license. Hasan Kanaker Department of Cyber Security, Faculty of Information Technology, Isra University Amman, 11622, Jordan [Email: hasan.kanaker@iu.edu.jo](Email: hasan.kanaker@iu.edu.jo) Article Info ABSTRACT 1. INTRODUCTION Cloud computing, an innovative method of information technology, uses the internet and remote servers to deliver a common set of computing resources and applications to meet customer requirements [1] . The advent of cloud computing technologies in the first decade of this century ushered in a new era in the development of information technology (IT) infrastructure, as users can now obtain software and computing power over the Internet or networks. This has also led to the emergence of new models for hosting and distributing online services [2], [3] . Cloud computing allows users to easily access services, facilitating seamless access to data and program execution on a large number of connected computers. Moreover, it removes the requirement for users to install software on their personal computers and instead provides access to resources and applications via an internet connection at any time and from any location [2], [4] . Cloud computing has been widely adopted by public-sector businesses in many countries, including Australia, the United Kingdom (UK), the United State (US), and various European countries [5]–[7] . The government cloud (G-Cloud) infrastructure was introduced by the UK government in 2010, saving an estimated £3.2 billion [5], [8], [9] . The cloud computing mall was al

FAQs

Why is detecting Trojan horse infections important in cloud computing environments?

Trojan horse injection attacks can introduce malicious services, virtual machines, or applications into cloud systems, interfering with or altering cloud functionality. Signature-based methods may miss new variants that change their signatures.

What tools does the study compare for Trojan horse detection?

The study compares Weka and Python Colab as tools for building machine learning models to detect Trojan horse infections.

Which evaluation metrics and comparisons are used in the study?

The study evaluates recall, accuracy, and F1-score, and also compares the computational resources required when using multiple machine learning algorithms in each tool.

Aug 2, 2026

Upload by Ezra