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Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning

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Bibliographic Details
Published in:International Journal of Wireless and Microwave Technologies
Format: Online Article RSS Article
Published: 2026
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container_title International Journal of Wireless and Microwave Technologies
description
discipline_display Electronics
discipline_facet Electronics
format Online Article
RSS Article
genre Journal Article
id rss_article:74304
institution FRELIP
journal_source_facet International Journal of Wireless and Microwave Technologies
last_indexed 2026-06-20T21:31:51.751Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
Electronics
General
Electronics
sub_discipline_display General
sub_discipline_facet General
subject_display Electronics
General
Electronics
subject_facet Electronics
General
Electronics
title Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_alt Detección de intrusiones energéticamente eficiente y preservadora de la privacidad en redes basadas en el borde mediante aprendizaje autosupervisado federado
Détection d'intrusion économe en énergie et respectueuse de la vie privée dans les réseaux basés sur la périphérie à l'aide de l'apprentissage auto-supervisé fédéré
Detecção de Intrusão com Eficiência Energética e Preservação de Privacidade em Redes Baseadas em Borda Usando Aprendizado Auto-Supervisionado Federado
title_auth Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_es_txt Detección de intrusiones energéticamente eficiente y preservadora de la privacidad en redes basadas en el borde mediante aprendizaje autosupervisado federado
title_fr_txt Détection d'intrusion économe en énergie et respectueuse de la vie privée dans les réseaux basés sur la périphérie à l'aide de l'apprentissage auto-supervisé fédéré
title_full Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_fullStr Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_full_unstemmed Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_pt_txt Detecção de Intrusão com Eficiência Energética e Preservação de Privacidade em Redes Baseadas em Borda Usando Aprendizado Auto-Supervisionado Federado
title_short Energy-Efficient and Privacy-Preserving Intrusion Detection in Edge-Based Networks Using Federated Self-Supervised Learning
title_sort energy-efficient and privacy-preserving intrusion detection in edge-based networks using federated self-supervised learning
topic Electronics
General
Electronics
url https://www.mecs-press.org/ijwmt/ijwmt-v16-n3/v16n3-17.html