Intrusion Detection based on Federated Learning: a systematic review
JL Hernandez-Ramos, G Karopoulos… - arXiv preprint arXiv …, 2023 - arxiv.org
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
SIDS: A federated learning approach for intrusion detection in IoT using Social Internet of Things
Abstract The Internet of Things (IoT) ecosystem needs Intrusion Detection Systems (IDS) to
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …
[HTML][HTML] The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research
B Ramos-Cruz, J Andreu-Perez, L Martínez - Neurocomputing, 2024 - Elsevier
In today's world, it is vital to have strong cybersecurity measures in place. To combat the
ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to …
ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to …
A modular ice cream factory dataset on anomalies in sensors to support machine learning research in manufacturing systems
A small deviation in manufacturing systems can cause huge economic losses, and all
components and sensors in the system must be continuously monitored to provide an …
components and sensors in the system must be continuously monitored to provide an …
A privacy awareness framework for NFT avatars in the metaverse
Metaverse is a platform that offers unique user experiences. Users join the virtual worlds by
using a virtual representation called an avatar. There is increasing use of NonFungible …
using a virtual representation called an avatar. There is increasing use of NonFungible …
A collaborative ensemble construction method for federated random forest
PAE Lim, CH Park - Expert Systems with Applications, 2024 - Elsevier
Random forests are considered a cornerstone in machine learning for their robustness and
versatility. Despite these strengths, their conventional centralized training is ill-suited for the …
versatility. Despite these strengths, their conventional centralized training is ill-suited for the …
Enhanced simulation environment to support research in modular manufacturing systems
Modular automation provides a challenge for traditional physics simulators, especially if they
are used as a simulator in the loop of a development or research project looking at behavior …
are used as a simulator in the loop of a development or research project looking at behavior …
Feature encoding with autoencoder and differential evolution for network intrusion detection using machine learning
With the increasing use of computer networks and distributed systems, network security and
data privacy are becoming major concerns for our society. In this paper, we present an …
data privacy are becoming major concerns for our society. In this paper, we present an …
Random forest with differential privacy in federated learning framework for network attack detection and classification
Communication networks are crucial components of the underlying digital infrastructure in
any smart city setup. The increasing usage of computer networks brings additional cyber …
any smart city setup. The increasing usage of computer networks brings additional cyber …
[HTML][HTML] Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science
B Ghasemkhani, O Varliklar, Y Dogan, S Utku… - Animals, 2024 - mdpi.com
Simple Summary This study addresses the classification task in animal science, which helps
organize and analyze complex data, essential for making informed decisions. It introduces …
organize and analyze complex data, essential for making informed decisions. It introduces …