Results 51 to 60 of about 1,396 (174)

Robust and Noise-Resilient Botnet Detection Framework Using Heterogeneous Radial Basis Function Neural Network

Applied Sciences
The rapid evolution of botnet attacks poses a critical challenge facing cybersecurity, necessitating the development of intrusion detection models that are both highly accurate and computationally efficient.
Lama Awad, Sherenaz Al-Haj Baddar, Azzam Sleit   +2 more
doaj   +1 more source

Abnormal Traffic Detection Method for Multi-stage Attacks of Internet of Things Botnets [PDF]

Jisuanji kexue
To address the problem of how to efficiently detect multi-stage attack behavior of IoT botnet from massive network traffic data,an IoT botnet attack detection method based on multi-scale hybrid residual network(IBAD-MHRN)is proposed.Firstly,in order to ...
CHEN Liang, LI Zhihua
doaj   +1 more source

IoT Botnet Attack Detection Based on Optimized Extreme Gradient Boosting and Feature Selection

Sensors, 2020
Nowadays, Internet of Things (IoT) technology has various network applications and has attracted the interest of many research and industrial communities.
Mnahi Alqahtani, Hassan Mathkour, Mohamed Maher Ben Ismail   +2 more
doaj   +1 more source

Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García, Diego López Abril, Javier Bermejo Higuera, Víctor Gonzalez Llorente, Miguel Angel Sicilia Urbán   +4 more
wiley   +1 more source

Botnet Campaign Detection on Twitter

CoRR, 2018
This is an approach to detecting a subset of bots on Twitter, that at best is under-researched. This approach will be generic enough to be adaptable to most, if not all social networks. The subset of bots this focuses on are those that can evade most, if not all current detection methods.
openaire   +2 more sources

Deep Learning-Based Intrusion Detection System for Detecting IoT Botnet Attacks: A Review

IEEE Access
The proliferation of Internet of Things (IoT) devices has brought about an increased threat of botnet attacks, necessitating robust security measures. In response to this evolving landscape, deep learning (DL)-based intrusion detection systems (IDS) have
Tamara Al-Shurbaji, Mohammed Anbar, Selvakumar Manickam, Iznan H Hasbullah, Nadia Alfriehat, Basim Ahmad Alabsi, Ahmad Reda Alzighaibi, Hasan Hashim   +7 more
doaj   +1 more source

HSL‐CFS: Hybrid stacked learning with cooperative feature selection for cyberattack detection in smart grids

Energy Conversion and Economics, Volume 7, Issue 3, Page 207-220, June 2026.
Abstract An effective method for detecting cyberattacks is essential to the security of smart grids (SGs). In SGs, data from both cyber and physical domains can support attack detection. However, existing works insufficiently consider the heterogeneity, high dimensionality, and cross‐domain correlations of multi‐source data, affecting model ...
Qize Gao, Qiuyu Lu, June Li, Zhao Peng, Guo Shen, Ming Ni   +5 more
wiley   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 447-463, April 2026.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

BotCloud: Detecting botnets using MapReduce [PDF]

2011 IEEE International Workshop on Information Forensics and Security, 2011
Botnets are a major threat of the current Internet. Understanding the novel generation of botnets relying on peer-to-peer networks is crucial for mitigating this threat. Nowadays, botnet traffic is mixed with a huge volume of benign traffic due to almost ubiquitous high speed networks.
Jérôme François, Shaonan Wang, Walter Bronzi, Radu State, Thomas Engel 0001   +4 more
openaire   +1 more source

Understanding the Autonomous Electric Vehicle Cyber Threat Landscape: A Focus on Infrastructure, Threats and Ontology‐Based Modelling

Energy Internet, Volume 3, Issue 1, Page 39-51, April 2026.
ABSTRACT The development of autonomous electric vehicles (AEVs) represents the convergence of two simultaneous automotive revolutions: electric vehicles (EVs) and autonomous vehicles (AVs). AVs require sensors, decision‐making systems and actuation systems to achieve autonomous driving, whereas EVs require intelligent management and real‐time ...
Ohud Alsadi, Abdulrahman Almijlad, Trinadh Pamulapati, Rajiv Ranjan, Devki Jha, Tejal Shah   +5 more
wiley   +1 more source