eXtreme gradient boosting algorithm with machine learning: A review

ZA Ali, ZH Abduljabbar, HA Tahir, AB Sallow… - Academic Journal of …, 2023 - cir.nii.ac.jp
< jats: p> The primary task of machine learning is to extract valuable information from the
data that is generated every day, process it to learn from it, and take useful actions. Original …

Defense mechanisms against DDoS attacks in a cloud computing environment: State-of-the-art and research challenges

N Agrawal, S Tapaswi - IEEE Communications Surveys & …, 2019 - ieeexplore.ieee.org
The salient features of cloud computing (such as on-demand self-service, resource pooling,
broad network access, rapid elasticity, and measured service) are being exploited by …

Approximating XGBoost with an interpretable decision tree

O Sagi, L Rokach - Information sciences, 2021 - Elsevier
The increasing usage of machine-learning models in critical domains has recently stressed
the necessity of interpretable machine-learning models. In areas like healthcare, finary–the …

An evolutionary SVM model for DDOS attack detection in software defined networks

KS Sahoo, BK Tripathy, K Naik… - IEEE …, 2020 - ieeexplore.ieee.org
Software-Defined Network (SDN) has become a promising network architecture in current
days that provide network operators more control over the network infrastructure. The …

[PDF][PDF] An intrusion detection system for sdn using machine learning

G Logeswari, S Bose, T Anitha - Intelligent Automation & …, 2023 - pdfs.semanticscholar.org
Software Defined Networking (SDN) has emerged as a promising and exciting option for the
future growth of the internet. SDN has increased the flexibility and transparency of the …

A tree-based stacking ensemble technique with feature selection for network intrusion detection

M Rashid, J Kamruzzaman, T Imam, S Wibowo… - Applied …, 2022 - Springer
Several studies have used machine learning algorithms to develop intrusion systems (IDS),
which differentiate anomalous behaviours from the normal activities of network systems. Due …

An efficient XGBoost–DNN-based classification model for network intrusion detection system

P Devan, N Khare - Neural Computing and Applications, 2020 - Springer
There is a steep rise in the trend of the utility of Internet technology day by day. This
tremendous increase ushers in a massive amount of data generated and handled. For …

Detection of illicit accounts over the Ethereum blockchain

S Farrugia, J Ellul, G Azzopardi - Expert Systems with Applications, 2020 - Elsevier
The recent technological advent of cryptocurrencies and their respective benefits have been
shrouded with a number of illegal activities operating over the network such as money …

Security threats, defense mechanisms, challenges, and future directions in cloud computing

S El Kafhali, I El Mir, M Hanini - Archives of Computational Methods in …, 2022 - Springer
Several new technologies such as the smart cities, the Internet of Things (IoT), and 5G
Internet need services offered by cloud computing for processing and storing more …

A secure ai-driven architecture for automated insurance systems: Fraud detection and risk measurement

N Dhieb, H Ghazzai, H Besbes, Y Massoud - IEEE Access, 2020 - ieeexplore.ieee.org
The private insurance sector is recognized as one of the fastest-growing industries. This
rapid growth has fueled incredible transformations over the past decade. Nowadays, there …