Impact of Machine Learning Algorithms in Intrusion Detection Systems for Internet of Things

Title

Impact of Machine Learning Algorithms in Intrusion Detection Systems for Internet of Things

Creator

Jose J.; Jose D.V.; Rao K.S.; Janz J.

Description

The importance of security aspects is increased recently due to the enormous usage of IoT devices. Securing the system from all sorts of vulnerabilities is inevitable to use IoT applications. Intrusion detection systems are power mechanism which provides this service. The introduction of artificial intelligence into intrusion detection systems can further enhance its power. This paper is an attempt to understand the impact of machine learning algorithms in attack detection. Using the UNSW-NB 15 dataset, the impact of different machine learning algorithms is assessed. 2021 IEEE.

Source

10th International Conference on Advances in Computing and Communications, ICACC 2021

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Internet of Things; Intrusion Detection System; Machine Learning

Coverage

Jose J., CHRIST University, Department of Computer Science, Bangalore, India; Jose D.V., CHRIST University, Department of Computer Science, Bangalore, India; Rao K.S., CHRIST University, Department of Computer Science, Bangalore, India; Janz J., CHRIST University, Department of Computer Science, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-166543919-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICACC-202152719.2021.9708404

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125809707&doi=10.1109%2fICACC-202152719.2021.9708404&partnerID=40&md5=f38ffee2033a770cc0550b34b6c1f8d8