Copertina

Intrusion Detection in IoT Networks Using Hyperdimensional Computing: A Case Study on the NSL-KDD Dataset

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ghajari, Ghazal, Ghajari, Elaheh, Mohammadi, Hossein, Amsaad, Fathi
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Network Anomaly Detection for IoT Using Hyperdimensional Computing on NSL-KDD
di: Ghajari, Ghazal, et al.
Pubblicazione: (2025)

Enhancing Cybersecurity in Critical Infrastructure with LLM-Assisted Explainable IoT Systems
di: Ghimire, Ashutosh, et al.
Pubblicazione: (2025)

Blockchain-Driven AI-Enhanced Post-Quantum Multivariate Identity-based Signature and Privacy-Preserving Data Aggregation Scheme for Fog-enabled Flying Ad-Hoc Networks
di: majmaie, Sufian Al, et al.
Pubblicazione: (2026)

Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification
di: Ghajari, Ghazal, et al.
Pubblicazione: (2024)

Adaptive Intrusion Detection for Evolving RPL IoT Attacks Using Incremental Learning
di: Bas, Sumeyye, et al.
Pubblicazione: (2025)

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

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
di: Panopoulos, Ioannis, et al.
Pubblicazione: (2025)

Optimized IoT Intrusion Detection using Machine Learning Technique
di: Mahmud, Muhammad Zawad, et al.
Pubblicazione: (2024)

A Conditional Tabular GAN-Enhanced Intrusion Detection System for Rare Attacks in IoT Networks
di: Menssouri, Safaa, et al.
Pubblicazione: (2025)

A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation
di: Panopoulos, Ioannis, et al.
Pubblicazione: (2026)

FLARE: Feature-based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection
di: Boswell, Bradley, et al.
Pubblicazione: (2025)

Efficient Network Traffic Feature Sets for IoT Intrusion Detection
di: Silva, Miguel, et al.
Pubblicazione: (2024)

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

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

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

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

Optimizing IoT Threat Detection with Kolmogorov-Arnold Networks (KANs)
di: Emelianova, Natalia, et al.
Pubblicazione: (2025)

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

Hybrid Deep Learning-Federated Learning Powered Intrusion Detection System for IoT/5G Advanced Edge Computing Network
di: Baidar, Rasil, 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)

Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing
di: Mainuddin, Md, et al.
Pubblicazione: (2024)

Enhancing Cybersecurity in IoT Networks: A Deep Learning Approach to Anomaly Detection
di: Pang, Yining, et al.
Pubblicazione: (2024)

A Comparative Analysis of Machine Learning Models for DDoS Detection in IoT Networks
di: Shakya, Sushil, et al.
Pubblicazione: (2024)

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

SD-CGAN: Conditional Sinkhorn Divergence GAN for DDoS Anomaly Detection in IoT Networks
di: Onyeka, Henry, et al.
Pubblicazione: (2025)

In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis
di: Chaudhary, Devashish, et al.
Pubblicazione: (2026)

On-Device Interpretable Tsetlin Machine-Based Intrusion Detection for Secure IoMT
di: Jaiswal, Rahul, et al.
Pubblicazione: (2026)

Explainable Threat Attribution for IoT Networks Using Conditional SHAP and Flow Behavior Modelling
di: Ozechi, Samuel, et al.
Pubblicazione: (2026)

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)

Enhancing IoT Security: A Novel Feature Engineering Approach for ML-Based Intrusion Detection Systems
di: Mahanipour, Afsaneh, et al.
Pubblicazione: (2024)

Shift Detection and Adaptation for Network Intrusion Detection
di: Mousavipour, Ehssan, et al.
Pubblicazione: (2025)

Feature Selection for Network Intrusion Detection
di: Westphal, Charles, et al.
Pubblicazione: (2024)

A Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security
di: Jaiswal, Rahul, et al.
Pubblicazione: (2026)

Evasion of IoT Malware Detection via Dummy Code Injection
di: Zargarzadeh, Sahar, et al.
Pubblicazione: (2026)

Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway
di: Palmese, Fabio, et al.
Pubblicazione: (2025)

IoT-based Android Malware Detection Using Graph Neural Network With Adversarial Defense
di: Yumlembam, Rahul, et al.
Pubblicazione: (2025)

Uncovering and Understanding FPR Manipulation Attack in Industrial IoT Networks
di: Ahsan, Mohammad Shamim, et al.
Pubblicazione: (2026)

Towards Efficient Machine Learning Method for IoT DDoS Attack Detection
di: Modi, P
Pubblicazione: (2024)

Unsupervised Anomaly Detection for Smart IoT Devices: Performance and Resource Comparison
di: Sami, Md. Sad Abdullah, et al.
Pubblicazione: (2025)

Binary Anomaly Detection in Streaming IoT Traffic under Concept Drift
di: Carnier, Rodrigo Matos, et al.
Pubblicazione: (2025)