[HTML][HTML] Classification model for accuracy and intrusion detection using machine learning approach

A Agarwal, P Sharma, M Alshehri, AA Mohamed… - PeerJ Computer …, 2021 - peerj.com
In today's cyber world, the demand for the internet is increasing day by day, increasing the
concern of network security. The aim of an Intrusion Detection System (IDS) is to provide …

A comparative study of machine learning classifiers for network intrusion detection

FA Khan, A Gumaei - Artificial Intelligence and Security: 5th International …, 2019 - Springer
The network intrusion detection system (NIDS) has become an essential tool for detecting
attacks in computer networks and protecting the critical information and systems. The …

[HTML][HTML] A novel ensemble learning-based model for network intrusion detection

N Thockchom, MM Singh, U Nandi - Complex & Intelligent Systems, 2023 - Springer
The growth of Internet and the services provided by it has been growing exponentially in the
past few decades. With such growth, there is also an ever-increasing threat to the security of …

Performance evaluation of intrusion detection based on machine learning using Apache Spark

M Belouch, S El Hadaj, M Idhammad - Procedia Computer Science, 2018 - Elsevier
Nowadays, network intrusion is considered as one of the major concerns in network
communications. Thus, the developed network intrusion detection systems aim to identify …

[HTML][HTML] Overview on Intrusion Detection Systems Design Exploiting Machine Learning for Networking Cybersecurity

P Dini, A Elhanashi, A Begni, S Saponara, Q Zheng… - Applied Sciences, 2023 - mdpi.com
The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to
detect and identify intrusion attacks. With the increasing volume of data generation, the …

[PDF][PDF] Performance analysis of machine learning classifiers for intrusion detection using unsw-nb15 dataset

G Kocher, G Kumar - Comput. Sci. Inf. Technol.(CS IT), 2020 - csitcp.org
With the advancement of internet technology, the numbers of threats are also rising
exponentially. To reduce the impact of these threats, researchers have proposed many …

Machine learning methods for network intrusion detection

M Alkasassbeh, M Almseidin - arXiv preprint arXiv:1809.02610, 2018 - arxiv.org
Network security engineers work to keep services available all the time by handling intruder
attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to …

Implementation of BFS-NB hybrid model in intrusion detection system

S Mishra, C Mahanty, S Dash, BK Mishra - Recent Developments in …, 2019 - Springer
Recently due to rise in technology and connectivity among various components of a system,
various new cybersecurity issues are emerging. To handle this rapid growth in computer …

Comparative evaluation of machine learning algorithms for network intrusion detection and attack classification

M Leon, T Markovic, S Punnekkat - 2022 international joint …, 2022 - ieeexplore.ieee.org
With the increasing use of the internet and reliance on computer-based systems for our daily
lives, any vulnerability in those systems is one of the most important issues for the …

[PDF][PDF] A hybrid approach for network intrusion detection

M Mehmood, T Javed, J Nebhen, S Abbas… - CMC-Comput. Mater …, 2022 - researchgate.net
Due to the widespread use of the internet and smart devices, various attacks like intrusion,
zero-day, Malware, and security breaches are a constant threat to any organization's …