Enhancing Intrusion Detection in IoT Networks Through Federated Learning

被引：0

作者：

Dhakal, Raju ^{[1
]}

Raza, Waleed ^{[1
]}

Tummala, Vijayanth ^{[2
]}

Niure Kandel, Laxima ^{[1
]}

机构：

[1] Embry-Riddle Aeronautical University, Department of Electrical Engineering and Computer Science, Daytona Beach,FL,32114, United States

[2] Embry-Riddle Aeronautical University, Faculty of Security Studies and International Affairs, Department of Security Studies and International Affairs, Daytona Beach,FL,32114, United States

来源：

IEEE Access | 2024年 / 12卷

关键词：

Compendex;

D O I：

10.1109/ACCESS.2024.3495702

中图分类号：

学科分类号：

摘要：

Adversarial machine learning - Bot (Internet) - Botnet - Contrastive Learning - Cybersecurity - Differential privacy - Intrusion detection - Network intrusion - Risk assessment

引用

页码：167168 / 167182

共 50 条

[1] Federated Deep Learning for Intrusion Detection in IoT Networks
Belarbi, Othmane
Spyridopoulos, Theodoros
Anthi, Eirini
Mavromatis, Ioannis
Carnelli, Pietro
Khan, Aftab
[J]. IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 237 - 242
[2] Federated Learning for IoT Intrusion Detection
Lazzarini, Riccardo
Tianfield, Huaglory
Charissis, Vassilis
[J]. AI, 2023, 4 (03) : 509 - 530
[3] Secure and Efficient Federated Learning for Robust Intrusion Detection in IoT Networks
Abou El Houda, Zakaria
Moudoud, Hajar
Khoukhi, Lyes
[J]. IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 2668 - 2673
[4] Federated Deep Learning-based Intrusion Detection Approach for Enhancing Privacy in Fog-IoT Networks
Radjaa, Bensaid
Nabila, Labraoui
Salameh, Haythem Bany
[J]. 2023 10TH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS: SYSTEMS, MANAGEMENT AND SECURITY, IOTSMS, 2023, : 156 - 160
[5] Enhancing Privacy-Preserving Intrusion Detection through Federated Learning
Alazab, Ammar
Khraisat, Ansam
Singh, Sarabjot
Jan, Tony
[J]. ELECTRONICS, 2023, 12 (16)
[6] Improving Privacy in Federated Learning-Based Intrusion Detection for IoT Networks
Syne, Lamine
Caballero-Gil, Pino
Hernandez-Goya, Candelaria
[J]. 39TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2024, 2024, : 580 - 582
[7] A federated learning approach to network intrusion detection using residual networks in industrial IoT networks
Chaurasia, Nisha
Ram, Munna
Verma, Priyanka
Mehta, Nakul
Bharot, Nitesh
[J]. JOURNAL OF SUPERCOMPUTING, 2024, 80 (13): : 18325 - 18346
[8] Enhancing Industrial IoT Security: Utilizing BlockchainAssisted Deep Federated Learning for Collaborative Intrusion Detection
Govindaram, Anitha
Jegatheesan, A.
[J]. JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (02) : 1345 - 1363
[9] Federated Learning for IoT Networks: Enhancing Efficiency and Privacy
Zahri, Sofia
Bennouri, Hajar
Chehri, Abdellah
Abdelmoniem, Ahmed M.
[J]. 2023 IEEE 9TH WORLD FORUM ON INTERNET OF THINGS, WF-IOT, 2023,
[10] Temporal Partitioned Federated Learning for IoT Intrusion Detection Systems
Abu Issa, Mohannad
Ibnkahla, Mohamed
Matrawy, Ashraf
Eldosouky, Abdelrahman
[J]. 2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,

← 1 2 3 4 5 →