M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning

AV Turukmane, R Devendiran - Computers & Security, 2024 - Elsevier
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …

[HTML][HTML] Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing

F Zola, L Segurola-Gil, JL Bruse, M Galar… - Computers & …, 2022 - Elsevier
Network traffic analysis is an important cybersecurity task, which helps to classify
anomalous, potentially dangerous connections. In many cases, it is critical not only to detect …

Use of machine learning for Web Denial-of-service attacks: a multivocal literature review

M Ayub, O Lajam, A Alnajim, M Niazi - Arabian Journal for Science and …, 2023 - Springer
Abstract Denial-of-service (DoS) attacks conducted on online systems cause the targeted
resources to become inoperative. This is caused by the abnormal traffic intentionally …

An explanation of the LSTM model used for DDoS attacks classification

A Bashaiwth, H Binsalleeh, B AsSadhan - Applied Sciences, 2023 - mdpi.com
With the rise of DDoS attacks, several machine learning-based attack detection models have
been used to mitigate malicious behavioral attacks. Understanding how machine learning …

[PDF][PDF] Cyber security: performance analysis and challenges for cyber attacks detection

AA Salih, MB Abdulrazzaq - Indonesian Journal of Electrical …, 2023 - academia.edu
Nowadays, with the occurrence of new attacks and raised challenges have been facing the
security of computer systems. Cyber security techniques have become essential for …

Detecting distributed denial of service in network traffic with deep learning

M Rusyaidi, S Jaf, Z Ibrahim - International Journal of …, 2022 - sure.sunderland.ac.uk
COVID-19 has altered the way businesses throughout the world perceive cyber security. It
resulted in a series of unique cyber-crime-related conditions that impacted society and …

Optimalisasi Deteksi Serangan DDoS Menggunakan Algoritma Random Forest, SVM, KNN dan MLP pada Jaringan Komputer

I Maulana, A Alamsyah - Indonesian Journal of Mathematics and …, 2023 - journal.unnes.ac.id
Distributed denial of service (DDoS) merupakan serangan pada server komputer yang
menjadi ancaman serius pada keamanan jaringan komputer. Serangan ini dapat …

Combating Network Intrusions using Machine Learning Techniques with Multilevel Feature Selection Method

TC Olayinka, CC Ugwu, OJ Okhuoya… - 2022 IEEE Nigeria …, 2022 - ieeexplore.ieee.org
The heavy dependency on the internet, as well as other emerging technologies for access,
storage, and sharing of information, has triggered a proportional increase in cyberattacks …

A Novel Deep Learning Approach for Detecting Types of Attacks in the NSL-KDD Dataset

HMS SALEEH, H Marouane… - Babylonian …, 2024 - journals.mesopotamian.press
The growing prevalence of Internet intrusions poses significant threats to the security,
privacy, and reliability of systems and networks. Denial-of-service (DoS) attacks are a cause …

An evolutionary approach towards achieving enhanced intrusion detection system

OS Popoọla, II Ayogu, ỌJ MebawỌndu… - 2022 IEEE Nigeria …, 2022 - ieeexplore.ieee.org
Major among the various Information Systems Security breaches are Intrusions. Intrusion
bounds are expanding in scales and sophistications; with high-tech infrastructure, massive …