Autoencoder Ensemble Method for Botnets Detection on IOT Devices

Steven E. Arroyo, Shen Shyang Ho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Like anything else on the internet, IoT devices are very susceptible to cyber-attacks that could take out the device or install spyware. In this paper, we propose an anomaly detection solution driven by an autoencoder ensemble to detect botnets on IOT devices. In particular, the ensemble size is determined by hierarchical clustering of the features in the packet header. Moreover, one does not require an additional neural network to combine the decisions. The proposed approach is a more efficient solution for IOT problem setting and hence, overcomes the issue of lacking computational resources and memory on IOT devices, as well as run-time performance problems. Empirical results on two datasets, one from the 2016 Mirai botnet attacks on IoT devices and the other from Gafgyt malware attacks on various IOT devices, show the competitiveness and feasibility of our proposed solution.

Original languageEnglish (US)
Title of host publicationProceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022
EditorsM. Arif Wani, Mehmed Kantardzic, Vasile Palade, Daniel Neagu, Longzhi Yang, Kit-Yan Chan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages715-720
Number of pages6
ISBN (Electronic)9781665462839
DOIs
StatePublished - 2022
Event21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022 - Nassau, Bahamas
Duration: Dec 12 2022Dec 14 2022

Publication series

NameProceedings - 21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022

Conference

Conference21st IEEE International Conference on Machine Learning and Applications, ICMLA 2022
Country/TerritoryBahamas
CityNassau
Period12/12/2212/14/22

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence
  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'Autoencoder Ensemble Method for Botnets Detection on IOT Devices'. Together they form a unique fingerprint.

Cite this