Results 51 to 60 of about 306 (121)

Profiling IoT-Based Botnet Traffic Using DNS [PDF]

2019 IEEE Global Communications Conference (GLOBECOM), 2019
Internet-wide security and resilience have traditionally been subject to large-scale DDoS attacks initiated by various types of botnets. Since the Mirai outbreak in 2016 myriads of Mirai-alike IoT-based botnets have emerged. Such botnets rely on Mirai's base malware code and they infiltrate vulnerable IoT devices on an Internet-wide scale such as to ...
Owen P. Dwyer, Angelos K. Marnerides, Vasileios Giotsas, Troy Mursch   +3 more
openaire   +2 more sources

Comparative Analysis of IoT Botnet Datasets

Computer Science, 2022
Günümüzde IoT teknolojilerinin kullanımının yaygınlaşması birçok güvenlik sorunlarını da beraberinde getirmiştir. IoT cihazları çeşitli saldırıların hedefi haline gelmiştir. Bu saldırılarda en sık karşılaşılan tür botnet saldırılarıdır. IoT cihazlarda bu saldırıların sürekli çeşitlenerek gelişmesi ve donanımlarının kısıtlı olması sebebiyle geleneksel ...
ÖLMEZ, Esin Gül, İNCE, Kenan
openaire   +2 more sources

Pragmatic Study of Botnet Attack Detection In An IoT Environment [PDF]

E3S Web of Conferences
A comprehensive search for primary research published between 2014 and 2023 was carried across several databases. Studies that describe the application of machine learning (ML) and deep learning techniques for if they was carried out across several ...
Vennapureddy Rajasree, Srinivasulu T.
doaj   +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

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

An Overview of Deep Learning Techniques for Big Data IoT Applications

International Journal of Communication Systems, Volume 39, Issue 4, 10 March 2026.
Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur, Vipin Balyan, Sindhu Hak Gupta   +2 more
wiley   +1 more source

Neutrosophic Set and Machine Learning Model for Identifying Botnet Attacks on IoT Effectively [PDF]

Neutrosophic Sets and Systems
Botnet attacks, in which attackers utilize reciprocal communications between IoT devices to undertake extensive harmful actions, are one of the most significant risks in WSNs.
Wasal S AL-Bash AL-Azzawi, Hassan W. Hilou, Nawfal H. warush, Hasan Meslmani, Ahmed A El-Douh, Ahmed Abdelhafeez   +5 more
doaj   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, Volume 14, Issue 3, Page 1431-1455, March 2026.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation

Complex & Intelligent Systems
The exponential growth of the Internet of Things (IoT) has introduced new security vulnerabilities, particularly from botnet attacks that exploit the heterogeneity and limited processing capabilities of IoT devices.
Md. Alamgir Hossain, Sadman Saif, Md. Saiful Islam   +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