A holistic review of network anomaly detection systems: A comprehensive survey

N Moustafa, J Hu, J Slay - Journal of Network and Computer Applications, 2019 - Elsevier
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …

Role of machine learning and data mining in internet security: standing state with future directions

B Ahmad, W Jian, Z Anwar Ali - Journal of Computer Networks …, 2018 - Wiley Online Library
As time progresses with vast development of information technology, a large number of
industries are more dependent on network connections for sensitive business trading and …

Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic

N Moustafa - 2017 - unsworks.unsw.edu.au
Abstract Despite a Network Anomaly Detection System (NADS) being capable of detecting
existing and zero-day attacks, it is still not universally implemented in industry and real …

[PDF][PDF] Association Rule Mining Frequent-Pattern-Based Intrusion Detection in Network.

S Sivanantham, V Mohanraj, Y Suresh… - … Systems Science & …, 2023 - cdn.techscience.cn
In the network security system, intrusion detection plays a significant role. The network
security system detects the malicious actions in the network and also conforms the …

[图书][B] An intrusion detection system using machine learning algorithm

CJ Ugochukwu, EO Bennett, P Harcourt - 2019 - iiardjournals.org
Security of data in a network based computer system has become a major challenge in the
world today. With the high increase of network traffic, hackers and malicious users are …

[PDF][PDF] Enhancing Network Intrusion Detection Model Using Machine Learning Algorithms.

NA Awad - Computers, Materials & Continua, 2021 - cdn.techscience.cn
After the digital revolution, large quantities of data have been generated with time through
various networks. The networks have made the process of data analysis very difficult by …

Random particle swarm optimization (RPSO) based intrusion detection system

R Patel, D Bakhshi, T Arjariya - International Journal of …, 2015 - search.proquest.com
Intrusion detection is a challenging area of research. As now there are several research
work are already done and the result improvement is in progress. In this paper a hybrid …

[PDF][PDF] An approach for efficient intrusion detection for KDD dataset: a survey

N Sharma, B Gaur - International Journal of Advanced Technology …, 2016 - academia.edu
Identifying possible attacks on the network system is a challenging task. There is several
research works are processed in this direction, but the need of improvement is always …

Machine learning based network intrusion detection with hybrid frequent item set mining

M Firat, MG Bakal, A Akbaş - Politeknik Dergisi, 2023 - dergipark.org.tr
With the development and expansion of computer networks day by day and the diversity of
software developed, the damage that possible attacks can cause is increasing beyond the …

[PDF][PDF] Intrusion detection and prevention framework using data mining techniques for financial sector

G Sharma, AK Kapil - Acta Informatica Malaysia, 2021 - actainformaticamalaysia.com
Data mining is being used for the purpose of cleaning, classifying, and examination of a
large amount of network data for correlating common infringement for intrusion detection …