Brute Force Detection System Based on Machine Learning Classifier Algorithm in Cloud-Based Infrastructure

Bari Hade Variant Wahono, Asfihani, Ilyas Mahfud, Baskworo Yoga Indra Exshadi, Ary Mazharuddin Shiddiqi

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

Abstract

The increasing adoption of cloud computing across various sectors has led to increased utilization of resources, such as server instances, databases, and microservices. This expansion generates a wide array of log files. The substantial challenge posed by the sheer volume and variety of log files lies in the increasing difficulty of efficiently processing and analyzing them without effective classification. This research focuses on distinguishing brute force attacks from other events in access logs. To achieve this goal, we employ One Hot Encoding for feature extraction and apply machine learning algorithms like Naive Bayes, Decision Tree, Random Forest, and Support Vector Machine. Our findings indicate that Decision Trees and Random Forests are particularly effective, with 87 % accuracy in detecting malicious traffic within log datasets. These results enhance security measures in cloud computing environments and aid in developing more robust and efficient anomaly detection systems.

Original languageEnglish
Title of host publication2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages939-943
Number of pages5
ISBN (Electronic)9798350372229
DOIs
Publication statusPublished - 2024
Event2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024 - Manama, Bahrain
Duration: 28 Jan 202429 Jan 2024

Publication series

Name2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

Conference

Conference2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024
Country/TerritoryBahrain
CityManama
Period28/01/2429/01/24

Keywords

  • decision tree
  • log processing
  • naive bayes
  • random forest
  • support vector machine

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