[HTML][HTML] Navigating the nexus: a systematic review of the symbiotic relationship between the metaverse and gaming

SY Mohammed, M Aljanabi, TR Gadekallu - International Journal of …, 2024 - Elsevier
The advent of the metaverse has sparked profound interest in its integration within the
gaming domain. Games, being intrinsic components of the metaverse, have attracted …

Intrusion detection in wireless sensor network using enhanced empirical based component analysis

L Zhiqiang, G Mohiuddin, Z Jiangbin, M Asim… - Future Generation …, 2022 - Elsevier
Nowadays, several kinds of attacks exist in cyberspace, and hence comprehensive research
has been implemented to overcome these drawbacks. One such method to provide security …

[PDF][PDF] MapReduce-iterative support vector machine classifier: novel fraud detection systems in healthcare insurance industry

JM Arockiam, ACS Pushpanathan - International Journal of Electrical …, 2023 - academia.edu
Fraud in healthcare insurance claims is one of the significant research challenges that affect
the growth of the healthcare services. The healthcare frauds are happening through …

Big data classification based on improved parallel k-nearest neighbor

AH Ali, MA Mohammed, RA Hasan… - TELKOMNIKA …, 2023 - telkomnika.uad.ac.id
In response to the rapid growth of many sorts of information, highway data has continued to
evolve in the direction of big data in terms of scale, type, and structure, exhibiting …

[HTML][HTML] Systematic literature review on intrusion detection systems: Research trends, algorithms, methods, datasets, and limitations

MM Issa, M Aljanabi, HM Muhialdeen - Journal of Intelligent Systems, 2024 - degruyter.com
Abstract Machine learning (ML) and deep learning (DL) techniques have demonstrated
significant potential in the development of effective intrusion detection systems. This study …

K-Means clustering-based semi-supervised for DDoS attacks classification

MN Jasim, MT Gaata - Bulletin of Electrical Engineering and Informatics, 2022 - beei.org
Network attacks of the distributed denial of service (DDoS) form are used to disrupt server
replies and services. It is popular because it is easy to set up and challenging to detect. We …

Efficient model for detecting application layer distributed denial of service attacks

MK Kareem, OD Aborisade, SA Onashoga… - Bulletin of Electrical …, 2023 - beei.org
The increasing advancement of technologies and communication infrastructures has been
posing threats to the internet services. One of the most powerful attack weapons for …

[HTML][HTML] Optimizing intrusion detection using intelligent feature selection with machine learning model

NO Aljehane, HA Mengash, SBH Hassine… - Alexandria Engineering …, 2024 - Elsevier
Network security is a critical aspect of information technology, targeting to safeguard the
confidentiality, integrity, and availability of data transmitted across computer networks …

Distributed denial of service attack defense system-based auto machine learning algorithm

M Aljanabi, R Hayder, S Talib, AH Ali… - Bulletin of Electrical …, 2023 - beei.org
The use of network-connected gadgets is rising quickly in the internet age, which is
escalating the number of cyberattacks. The detection of distributed denial of service (DDoS) …

The effectiveness of big data classification control based on principal component analysis

MA Mohammed, MM Akawee, ZH Saleh… - Bulletin of Electrical …, 2023 - beei.org
Large-scale datasets are becoming more common, yet they can be challenging to
understand and interpret. When dealing with big datasets, principal component analysis …