Machine learning-based botnet detection in software-defined network: A systematic review

K Shinan, K Alsubhi, A Alzahrani, MU Ashraf - Symmetry, 2021 - mdpi.com
In recent decades, the internet has grown and changed the world tremendously, and this, in
turn, has brought about many cyberattacks. Cybersecurity represents one of the most …

APT beaconing detection: A systematic review

MA Talib, Q Nasir, AB Nassif, T Mokhamed… - Computers & …, 2022 - Elsevier
Abstract Advanced Persistent Threat (APT) is a type of threat that has grabbed the attention
of researchers, particularly in the industrial security field. APTs are cyber intrusions carried …

A two-fold machine learning approach to prevent and detect IoT botnet attacks

F Hussain, SG Abbas, IM Pires, S Tanveer… - Ieee …, 2021 - ieeexplore.ieee.org
The botnet attack is a multi-stage and the most prevalent cyber-attack in the Internet of
Things (IoT) environment that initiates with scanning activity and ends at the distributed …

Real-time botnet detection on large network bandwidths using machine learning

J Velasco-Mata, V González-Castro, E Fidalgo… - Scientific Reports, 2023 - nature.com
Botnets are one of the most harmful cyberthreats, that can perform many types of
cyberattacks and cause billionaire losses to the global economy. Nowadays, vast amounts …

A survey on botnets: Incentives, evolution, detection and current trends

SN Thanh Vu, M Stege, PI El-Habr, J Bang, N Dragoni - Future Internet, 2021 - mdpi.com
Botnets, groups of malware-infected hosts controlled by malicious actors, have gained
prominence in an era of pervasive computing and the Internet of Things. Botnets have …

An aggregated mutual information based feature selection with machine learning methods for enhancing IoT botnet attack detection

M Al-Sarem, F Saeed, EH Alkhammash, NS Alghamdi - Sensors, 2021 - mdpi.com
Due to the wide availability and usage of connected devices in Internet of Things (IoT)
networks, the number of attacks on these networks is continually increasing. A particularly …

Botnet detection using negative selection algorithm, convolution neural network and classification methods

S Hosseini, AE Nezhad, H Seilani - Evolving Systems, 2022 - Springer
Botnet is a network and internet risk. It is necessary to detect botnet by analyzing and
monitoring in order to quickly prevent them. Most approaches are proposed to detect bots …

AI-based botnet attack classification and detection in IoT devices

V Puri, A Kataria, VK Solanki… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
End-user Internet of Things (IoT) devices, including security cameras, smart appliances,
home monitors, and thermostats, are becoming more prevalent in households. Additionally …

[PDF][PDF] Detection of autism spectrum disorder using a 1-dimensional convolutional neural network

AK Kareem, MM AL-Ani, AA Nafea - Baghdad Science Journal, 2023 - iasj.net
Abstract Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease
that impairs speech, social interaction, and behavior. Machine learning is a field of artificial …

DEMD-IoT: a deep ensemble model for IoT malware detection using CNNs and network traffic

M Nobakht, R Javidan, A Pourebrahimi - Evolving Systems, 2023 - Springer
Malware detection has recently emerged as a significant challenge on the Internet of Things
(IoT) security domain. Due to the increasing complexity and variety of malware, the demand …