Results 71 to 80 of about 11,129 (248)
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
La régulation du cybercrime comme alternative à la judiciarisation : le cas des botnets
Criminologie, 2014 Les botnets, ou réseaux d’ordinateurs compromis par des pirates informatiques, représentent à l’heure actuelle la menace criminelle la plus sérieuse, servant de support à la fraude bancaire, aux attaques distribuées par déni de service (DDoS), ou encore ...
Benoît Dupont
doaj +1 more source
Analysis of the Infection and the Injection Phases of the Telnet Botnets [PDF]
Journal of Universal Computer Science, 2019 With the number of Internet of Things devices increasing, also the number of vulnerable devices connected to the Internet increases. These devices can become part of botnets and cause damage to the Internet infrastructure.
Tomáš Bajtoš +4 more
doaj +3 more sources
Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System
Sensors, 2022 Malicious botnets such as Mirai are a major threat to IoT networks regarding cyber security. The Botnet Defense System (BDS) is a network security system based on the concept of “fight fire with fire”, and it uses white-hat botnets to fight against ...
Xiangnan Pan, Shingo Yamaguchi
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 +4 more
wiley +1 more source
Data-driven Curation, Learning and Analysis for Inferring Evolving IoT Botnets in the Wild
ARES, 2019 The insecurity of the Internet-of-Things (IoT) paradigm continues to wreak havoc in consumer and critical infrastructure realms. Several challenges impede addressing IoT security at large, including, the lack of IoT-centric data that can be collected ...
Morteza Safaei Pour +7 more
semanticscholar +1 more source
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 +4 more
wiley +1 more source
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 +5 more
wiley +1 more source
International Conference on Internet of Things, Big Data and Security, 2017 The Internet of Things (IoT), a platform and phenomenon allowing everything to process information and communicate data, is populated by ‘things’ which are introducing a multitude of new security vulnerabilities to the cyber-ecosystem.
Roger A. Hallman +4 more
semanticscholar +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 +2 more
wiley +1 more source