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 …

SIDS: A federated learning approach for intrusion detection in IoT using Social Internet of Things

M Amiri-Zarandi, RA Dara, X Lin - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT) ecosystem needs Intrusion Detection Systems (IDS) to
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 …

A modular ice cream factory dataset on anomalies in sensors to support machine learning research in manufacturing systems

T Markovic, M Leon, B Leander, S Punnekkat - IEEE Access, 2023 - ieeexplore.ieee.org
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 …

A privacy awareness framework for NFT avatars in the metaverse

D Zelenyanszki, Z Hóu, K Biswas… - 2023 International …, 2023 - ieeexplore.ieee.org
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 …

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 …

Enhanced simulation environment to support research in modular manufacturing systems

B Leander, T Marković, M León - IECON 2023-49th Annual …, 2023 - ieeexplore.ieee.org
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 …

Feature encoding with autoencoder and differential evolution for network intrusion detection using machine learning

M Leon, T Markovic, S Punnekkat - Proceedings of the Genetic and …, 2022 - dl.acm.org
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 …

Random forest with differential privacy in federated learning framework for network attack detection and classification

T Markovic, M Leon, D Buffoni, S Punnekkat - Applied Intelligence, 2024 - Springer
Communication networks are crucial components of the underlying digital infrastructure in
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 …