Malware Analysis and Classification Using Grid Search Optimization

Karina Fitriwulandari Ilham*, Tohari Ahmad, Muhammad Aidiel Rachman Putra

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Internet of Things (IoT) technology is experiencing rapid growth, but security and privacy remain a major concern. This is because IoT devices are vulnerable to being targets of malware attacks. On the other hand, detecting malware in IoT networks is challenging. Previous research has introduced several methods for IoT malware detection using several Machine Learning algorithms. However, only a few studies discussed parameter optimization in machine learning models. Thus, this research aims to develop a malware detection model using hyperparameter optimization with grid search in several Machine Learning algorithms. Several Machine Learning algorithms are utilized, such as Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and k Nearest Neighbors (k-NN). This research aims to improve IoT network security by developing a model to mitigate and detect the presence of malware attacks. The experiment using the IoT23 dataset shows a good result with the RF model. RF obtained the best result, achieving accuracy of 99.09%, precision of 98.54%, recall of 99.05%, and an F1 score of 98.79%.

Original languageEnglish
Title of host publication2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350370249
DOIs
Publication statusPublished - 2024
Event15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024 - Kamand, India
Duration: 24 Jun 202428 Jun 2024

Publication series

Name2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

Conference

Conference15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024
Country/TerritoryIndia
CityKamand
Period24/06/2428/06/24

Keywords

  • Grid Search
  • Information Security
  • Internet of Things
  • Intrusion Detection System
  • Malware
  • Network Security

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