Machine learning in cybersecurity: a comprehensive survey

D Dasgupta, Z Akhtar, S Sen - The Journal of Defense …, 2022 - journals.sagepub.com
Today's world is highly network interconnected owing to the pervasiveness of small personal
devices (eg, smartphones) as well as large computing devices or services (eg, cloud …

Machine learning in cybersecurity: A review of threat detection and defense mechanisms

UI Okoli, OC Obi, AO Adewusi… - World Journal of Advanced …, 2024 - wjarr.co.in
The cybersecurity concerns get increasingly intricate as the digital world progresses. In light
of the increasing complexity of cyber threats, it is imperative to develop and implement …

Ensemble classification for intrusion detection via feature extraction based on deep Learning

M Yousefnezhad, J Hamidzadeh, M Aliannejadi - Soft Computing, 2021 - Springer
An intrusion detection system is a security system that aims to detect sabotage and
intrusions on networks to inform experts of the attack and abuse of the network. Different …

Artificial intelligence and cybersecurity within a social media context: Implications and insights for Kuwait

KJ Alrabea, M Alsaffar, MA Alsafran… - Journal of Science and …, 2024 - emerald.com
Purpose By addressing the dearth of literature on the subject of cybersecurity risks and
artificial intelligence (AI), this study aims to close a research gap by concentrating on the …

Applying AI and Machine Learning to Enhance Automated Cybersecurity and Network Threat Identification

F Muheidat, MA Mallouh, O Al-Saleh… - Procedia Computer …, 2024 - Elsevier
Artificial intelligence (AI) is now used in many sectors but its transformative impact on
cybersecurity is unmatched. Cybersecurity is seen to rely heavily on artificial intelligence …

Overview of Cyberattacks Against Radio Access Networks in Long-term Evolution Mobile Networks and Defense Solutions

RH Hsu, O Mumbrekar - Communications of the CCISA, 2021 - cccisa.ccisa.org.tw
Mobile communication standard has been extensively developed to introduce many more
connected devices for the Internet of Things (IoT). However, the vulnerability of radio access …

[PDF][PDF] A Study on Sequential Classifiers Combination using Supervised Machine Learning Approach for Intrusion Detection System

S Phetlasy - 2019 - core.ac.uk
Data classification for intrusion detection system (IDS) is a process to distinguish normal and
malicious traffic. The classifier enables to correctly allow normal users and stop malicious …

An Analysis of Decision Tree Based Intrusion Detection System

YY Aung, MM Min - meral.edu.mm
Intrusion detection is the process called indentifying intrusions. The action of entering to a
system without permission is called intrusion. With the improving advanced technology of …

[HENVISNING][C] WINDOWS OS VULNERABILITY CLASSIFICATION USING MACHINE LEARNING TECHNIQUES

NAH AL-SARRAY - 2024