A survey of random forest based methods for intrusion detection systems

PAA Resende, AC Drummond - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
Over the past decades, researchers have been proposing different Intrusion Detection
approaches to deal with the increasing number and complexity of threats for computer …

Employing machine learning and iot for earthquake early warning system in smart cities

MS Abdalzaher, HA Elsayed, MM Fouda, MM Salim - Energies, 2023 - mdpi.com
An earthquake early warning system (EEWS) should be included in smart cities to preserve
human lives by providing a reliable and efficient disaster management system. This system …

Effective intrusion detection system using XGBoost

SS Dhaliwal, AA Nahid, R Abbas - Information, 2018 - mdpi.com
As the world is on the verge of venturing into fifth-generation communication technology and
embracing concepts such as virtualization and cloudification, the most crucial aspect …

Anomaly-based intrusion detection system for IoT application

M Bhavsar, K Roy, J Kelly, O Olusola - Discover Internet of things, 2023 - Springer
Abstract Internet-of-Things (IoT) connects various physical objects through the Internet and it
has a wide application, such as in transportation, military, healthcare, agriculture, and many …

A framework for fast and efficient cyber security network intrusion detection using apache spark

GP Gupta, M Kulariya - Procedia Computer Science, 2016 - Elsevier
Due to increase in internet based services, the size of network traffic data has become so
large and complex that it is very difficult to process with the traditional data processing tools …

Comparative performance assessments of machine-learning methods for artificial seismic sources discrimination

MS Abdalzaher, SSR Moustafa, M Abd-Elnaby… - IEEE …, 2021 - ieeexplore.ieee.org
Mankind is vulnerable to artificial seismic sources and accompanying explosions'
consequences. Recently, seismicity catalog contamination is among the main problems …

Comparative analysis of machine learning algorithms along with classifiers for network intrusion detection

S Choudhury, A Bhowal - 2015 International Conference on …, 2015 - ieeexplore.ieee.org
Intrusion detection is one of the challenging problems encountered by the modern network
security industry. A network has to be continuously monitored for detecting policy violation or …

A comparative analysis of SVM and its stacking with other classification algorithm for intrusion detection

N Chand, P Mishra, CR Krishna… - … on Advances in …, 2016 - ieeexplore.ieee.org
Network attacks have become more pervasive in the cyber world. There are various attacks
such as denial of service, scanning, privilege escalation that is increasing day by day …

A technique for generating a botnet dataset for anomalous activity detection in IoT networks

I Ullah, QH Mahmoud - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
In recent times, the number of Internet of Things (IoT) devices and the applications
developed for these devices has increased; as a result, these IoT devices are targeted by …

[图书][B] Evolutionary algorithms

A Pétrowski, S Ben-Hamida - 2017 - books.google.com
Evolutionary algorithms are bio-inspired algorithms based on Darwin's theory of evolution.
They are expected to provide non-optimal but good quality solutions to problems whose …