Imagen de Portada

MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Islam, Md Shamimul, Jaimes, Luis G., Dina, Ayesha S.
Formato:	Preprint
Publicado:	2026
Materias:	Cryptography and Security Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

An Optimized Decision Tree-Based Framework for Explainable IoT Anomaly Detection
por: Ashikuzzaman, et al.
Publicado: (2026)

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

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

Deep learning based intelligent IDS for Large-scale IoT networks
por: Andrade, Isha, et al.
Publicado: (2026)

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

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

Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning
por: Atitallah, Safa Ben, et al.
Publicado: (2024)

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

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

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

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

CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data
por: Zeng, Yifan
Publicado: (2025)

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

ThreatFormer-IDS: Robust Transformer Intrusion Detection with Zero-Day Generalization and Explainable Attribution
por: Nayak, Srikumar
Publicado: (2026)

A Robust Cross-Domain IDS using BiGRU-LSTM-Attention for Medical and Industrial IoT Security
por: Gueriani, Afrah, et al.
Publicado: (2025)

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

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

LLM-based Multi-class Attack Analysis and Mitigation Framework in IoT/IIoT Networks
por: Ikbarieh, Seif, et al.
Publicado: (2025)

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

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

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

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

Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data
por: Haque, Md. Ehsanul, et al.
Publicado: (2025)

FAST-IDS: A Fast Two-Stage Intrusion Detection System with Hybrid Compression for Real-Time Threat Detection in Connected and Autonomous Vehicles
por: S, Devika, et al.
Publicado: (2025)

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data
por: Shahzad, Muhammad Khuram, et al.
Publicado: (2026)

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

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

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

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

AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)
por: Guerra, Lorenzo, et al.
Publicado: (2024)

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

3D-IDS: Doubly Disentangled Dynamic Intrusion Detection
por: Qiu, Chenyang, et al.
Publicado: (2023)

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

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

Think Fast: Real-Time IoT Intrusion Reasoning Using IDS and LLMs at the Edge Gateway
por: Jamshidi, Saeid, et al.
Publicado: (2025)

IRSDA: An Agent-Orchestrated Framework for Enterprise Intrusion Response
por: Panigrahi, Damodar, et al.
Publicado: (2025)

Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis
por: Zhan, Zhonghao, et al.
Publicado: (2025)

CANGuard: A Spatio-Temporal CNN-GRU-Attention Hybrid Architecture for Intrusion Detection in In-Vehicle CAN Networks
por: Sajib, Rakib Hossain, et al.
Publicado: (2026)