Copertina

Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Atitallah, Safa Ben, Driss, Maha, Boulila, Wadii, Koubaa, Anis
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Cryptography and Security Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhancing Internet of Things Security throughSelf-Supervised Graph Neural Networks
di: Atitallah, Safa Ben, et al.
Pubblicazione: (2024)

Enhancing Early Alzheimer Disease Detection through Big Data and Ensemble Few-Shot Learning
di: Atitallah, Safa Ben, et al.
Pubblicazione: (2025)

FedMicro-IDA: A Federated Learning and Microservices-based Framework for IoT Data Analytics
di: Atitallah, Safa Ben, et al.
Pubblicazione: (2025)

Exploring Graph Mamba: A Comprehensive Survey on State-Space Models for Graph Learning
di: Atitallah, Safa Ben, et al.
Pubblicazione: (2024)

Self-Supervised Learning for Graph-Structured Data in Healthcare Applications: A Comprehensive Review
di: Atitallah, Safa Ben, et al.
Pubblicazione: (2024)

Feature Fusion for Improved Classification: Combining Dempster-Shafer Theory and Multiple CNN Architectures
di: Alzahem, Ayyub, et al.
Pubblicazione: (2024)

Hybrid Machine Learning Models for Intrusion Detection in IoT: Leveraging a Real-World IoT Dataset
di: Akif, Md Ahnaf, et al.
Pubblicazione: (2025)

Enhancing Intrusion Detection in IoT Environments: An Advanced Ensemble Approach Using Kolmogorov-Arnold Networks
di: Amouri, Amar, et al.
Pubblicazione: (2024)

Open Set Dandelion Network for IoT Intrusion Detection
di: Wu, Jiashu, et al.
Pubblicazione: (2023)

Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
di: Wulnye, Fortunatus Aabangbio, et al.
Pubblicazione: (2026)

An Investigation into the Performance of Non-Contrastive Self-Supervised Learning Methods for Network Intrusion Detection
di: Fard, Hamed, et al.
Pubblicazione: (2025)

Binary and Multi-Class Intrusion Detection in IoT Using Standalone and Hybrid Machine and Deep Learning Models
di: Akif, Md Ahnaf
Pubblicazione: (2025)

Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
di: Gueriani, Afrah, et al.
Pubblicazione: (2024)

MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library
di: Islam, Md Shamimul, et al.
Pubblicazione: (2026)

OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
di: Elouardi, Saida, et al.
Pubblicazione: (2025)

Targeted Adversarial Traffic Generation : Black-box Approach to Evade Intrusion Detection Systems in IoT Networks
di: Debicha, Islam, et al.
Pubblicazione: (2026)

Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
di: Al-Hammouri, Mohammad F., et al.
Pubblicazione: (2025)

Efficient IoT Intrusion Detection with an Improved Attention-Based CNN-BiLSTM Architecture
di: Naeem, Amna, et al.
Pubblicazione: (2025)

Gotham Dataset 2025: A Reproducible Large-Scale IoT Network Dataset for Intrusion Detection and Security Research
di: Belarbi, Othmane, et al.
Pubblicazione: (2025)

MI$^2$DAS: A Multi-Layer Intrusion Detection Framework with Incremental Learning for Securing Industrial IoT Networks
di: Lian, Wei, et al.
Pubblicazione: (2026)

Enhancing Autonomous Online Intrusion Detection for IoT with Balanced Learning, Reliable Pseudo-Labels, and Lightweight Architectures
di: Afzaal, Hanzala, et al.
Pubblicazione: (2026)

Leveraging Machine Learning for Botnet Attack Detection in Edge-Computing Assisted IoT Networks
di: Rupanetti, Dulana, et al.
Pubblicazione: (2025)

RESTRAIN: Reinforcement Learning-Based Secure Framework for Trigger-Action IoT Environment
di: Alam, Md Morshed, et al.
Pubblicazione: (2025)

LEMDA: A Novel Feature Engineering Method for Intrusion Detection in IoT Systems
di: Ghubaish, Ali, et al.
Pubblicazione: (2024)

MixGAN: A Hybrid Semi-Supervised and Generative Approach for DDoS Detection in Cloud-Integrated IoT Networks
di: Wu, Tongxi, et al.
Pubblicazione: (2025)

A Life-long Learning Intrusion Detection System for 6G-Enabled IoV
di: korba, Abdelaziz Amara, et al.
Pubblicazione: (2024)

Multiple-Input Auto-Encoder Guided Feature Selection for IoT Intrusion Detection Systems
di: Dinh, Phai Vu, et al.
Pubblicazione: (2024)

Trust-SSL: Additive-Residual Selective Invariance for Robust Aerial Self-Supervised Learning
di: Boulila, Wadii, et al.
Pubblicazione: (2026)

Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection
di: Guerra-Manzanares, Alejandro, et al.
Pubblicazione: (2026)

Multi-agent Reinforcement Learning-based Network Intrusion Detection System
di: Tellache, Amine, et al.
Pubblicazione: (2024)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
di: Yang, Wanrong, et al.
Pubblicazione: (2024)

Explainability-Aware Evaluation of Transfer Learning Models for IoT DDoS Detection Under Resource Constraints
di: Elsayed, Nelly
Pubblicazione: (2026)

Proactive Detection of Physical Inter-rule Vulnerabilities in IoT Services Using a Deep Learning Approach
di: Huang, Bing, et al.
Pubblicazione: (2024)

Beyond Detection: Leveraging Large Language Models for Cyber Attack Prediction in IoT Networks
di: Diaf, Alaeddine, et al.
Pubblicazione: (2024)

A Cutting-Edge Deep Learning Method For Enhancing IoT Security
di: Ansar, Nadia, et al.
Pubblicazione: (2024)

XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT
di: Aslam, Ambreen, et al.
Pubblicazione: (2026)

Towards Adapting Federated & Quantum Machine Learning for Network Intrusion Detection: A Survey
di: Chaudhary, Devashish, et al.
Pubblicazione: (2025)

Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study
di: Friji, Hamdi, et al.
Pubblicazione: (2024)

Evaluating Language Models For Threat Detection in IoT Security Logs
di: Tejero-Fernández, Jorge J., et al.
Pubblicazione: (2025)

A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
di: Arazzi, Marco, et al.
Pubblicazione: (2024)