Results 41 to 50 of about 306 (121)
Analysis of Botnet Countermeasures in IoT Systems
Central Ukrainian Scientific Bulletin. Technical Sciences, 2022 The article analyzes the methods of countering botnets in IoT systems. Today, the Internet of Things has become a popular term to describe scenarios in which Internet connectivity and computing power are spread across a multitude of objects, devices, sensors, etc.
Viktoria Germak, Roman Minailenko
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Explainable artificial intelligence for botnet detection in internet of things
Scientific ReportsThe proliferation of internet of things (IoT) devices has led to unprecedented connectivity and convenience. However, this increased interconnectivity has also introduced significant security challenges, particularly concerning the detection and ...
Mohamed Saied, Shawkat Guirguis
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Design of Universal Botnet Experimental Platform [PDF]
Jisuanji gongcheng, 2018 Botnet research in open networks has many drawbacks,such as uncontrollable process,difficult to scale,and unable to repeat experiments.In order to solve this problem,the requirement and design principle of the universal botnet experimental platform with ...
LI Dawei
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
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Autonomous machine learning for early bot detection in the internet of things
Digital Communications and Networks, 2023 The high costs incurred due to attacks and the increasing number of different devices in the Internet of Things (IoT) highlight the necessity of the early detection of botnets (i.e., a network of infected devices) to gain an advantage against attacks ...
Alex Medeiros Araujo +2 more
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Semantic Evolution and Consistency Learning for Robust Malicious Network Traffic Detection
Engineering Reports, Volume 8, Issue 6, June 2026.This paper proposes a semantic evolution and consistency network (SECN) for malicious traffic detection, modeling attack behaviors as temporally evolving semantics. By integrating dual‐level temporal representation and semantic consistency constraints, SECN achieves robust detection and strong generalization under encrypted, cross‐dataset, and unknown ...
Jing Yang, Wei Tan
wiley +1 more source
Examination of Traditional Botnet Detection on IoT-Based Bots
SensorsA botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their ...
Ashley Woodiss-Field +2 more
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Intelligent Detection of IoT Botnets Using Machine Learning and Deep Learning
Applied Sciences, 2020 As the number of Internet of Things (IoT) devices connected to the network rapidly increases, network attacks such as flooding and Denial of Service (DoS) are also increasing.
Jiyeon Kim +4 more
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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 +4 more
wiley +1 more source
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 +5 more
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