Saved in:
| Main Authors: | Silva, Miguel, Vitorino, João, Maia, Eva, Praça, Isabel |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.08042 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2024)
by: Vitorino, João, et al.
Published: (2024)
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2023)
by: Vitorino, João, et al.
Published: (2023)
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection
by: Vitorino, João, et al.
Published: (2024)
by: Vitorino, João, et al.
Published: (2024)
Revisiting Network Traffic Analysis: Compatible network flows for ML models
by: Vitorino, João, et al.
Published: (2025)
by: Vitorino, João, et al.
Published: (2025)
IoT Network Traffic Analysis with Deep Learning
by: Liu, Mei, et al.
Published: (2024)
by: Liu, Mei, et al.
Published: (2024)
A Transfer Learning Framework for Anomaly Detection in Multivariate IoT Traffic Data
by: Rezakhani, Mahshid, et al.
Published: (2025)
by: Rezakhani, Mahshid, et al.
Published: (2025)
Hybrid Deep Learning-Federated Learning Powered Intrusion Detection System for IoT/5G Advanced Edge Computing Network
by: Baidar, Rasil, et al.
Published: (2025)
by: Baidar, Rasil, et al.
Published: (2025)
PCAP-Backdoor: Backdoor Poisoning Generator for Network Traffic in CPS/IoT Environments
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey
by: Kalwar, Jawad Hussain, et al.
Published: (2024)
by: Kalwar, Jawad Hussain, et al.
Published: (2024)
How the Graph Construction Technique Shapes Performance in IoT Botnet Detection
by: Wasswa, Hassan, et al.
Published: (2026)
by: Wasswa, Hassan, et al.
Published: (2026)
Federated Learning-Driven Cybersecurity Framework for IoT Networks with Privacy-Preserving and Real-Time Threat Detection Capabilities
by: Rahmati, Milad
Published: (2025)
by: Rahmati, Milad
Published: (2025)
On the Cross-Dataset Generalization of Machine Learning for Network Intrusion Detection
by: Cantone, Marco, et al.
Published: (2024)
by: Cantone, Marco, et al.
Published: (2024)
Generative Active Adaptation for Drifting and Imbalanced Network Intrusion Detection
by: Gupta, Ragini, et al.
Published: (2025)
by: Gupta, Ragini, et al.
Published: (2025)
Backdoor Attacks on Contrastive Continual Learning for IoT Systems
by: Tim, Alfous, et al.
Published: (2026)
by: Tim, Alfous, et al.
Published: (2026)
Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems
by: Luay, Majed, et al.
Published: (2025)
by: Luay, Majed, et al.
Published: (2025)
IoT-AMLHP: Aligned Multimodal Learning of Header-Payload Representations for Resource-Efficient Malicious IoT Traffic Classification
by: Nie, Fengyuan, et al.
Published: (2025)
by: Nie, Fengyuan, et al.
Published: (2025)
BRIDGE and TCH-Net: Heterogeneous Benchmark and Multi-Branch Baseline for Cross-Domain IoT Botnet Detection
by: Bhilwarawala, Ammar, et al.
Published: (2026)
by: Bhilwarawala, Ammar, et al.
Published: (2026)
A Blockchain Solution for Collaborative Machine Learning over IoT
by: Beis-Penedo, Carlos, et al.
Published: (2023)
by: Beis-Penedo, Carlos, et al.
Published: (2023)
Sequential Binary Classification for Intrusion Detection
by: Vasudevan, Shrihari, et al.
Published: (2024)
by: Vasudevan, Shrihari, et al.
Published: (2024)
FedMADE: Robust Federated Learning for Intrusion Detection in IoT Networks Using a Dynamic Aggregation Method
by: Sun, Shihua, et al.
Published: (2024)
by: Sun, Shihua, et al.
Published: (2024)
SecureDyn-FL: A Robust Privacy-Preserving Federated Learning Framework for Intrusion Detection in IoT Networks
by: Soomro, Imtiaz Ali, et al.
Published: (2026)
by: Soomro, Imtiaz Ali, et al.
Published: (2026)
Design and implementation of intelligent packet filtering in IoT microcontroller-based devices
by: Bertoli, Gustavo de Carvalho, et al.
Published: (2023)
by: Bertoli, Gustavo de Carvalho, et al.
Published: (2023)
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
by: Kostas, Kahraman, et al.
Published: (2023)
by: Kostas, Kahraman, et al.
Published: (2023)
LPUF-AuthNet: A Lightweight PUF-Based IoT Authentication via Tandem Neural Networks and Split Learning
by: Mefgouda, Brahim, et al.
Published: (2024)
by: Mefgouda, Brahim, et al.
Published: (2024)
ZEST: Attention-based Zero-Shot Learning for Unseen IoT Device Classification
by: Wu, Binghui, et al.
Published: (2023)
by: Wu, Binghui, et al.
Published: (2023)
Hyperparameter Tuning-Based Optimized Performance Analysis of Machine Learning Algorithms for Network Intrusion Detection
by: Tripathy, Sudhanshu Sekhar, et al.
Published: (2025)
by: Tripathy, Sudhanshu Sekhar, et al.
Published: (2025)
Sdn Intrusion Detection Using Machine Learning Method
by: Mahmud, Muhammad Zawad, et al.
Published: (2024)
by: Mahmud, Muhammad Zawad, et al.
Published: (2024)
A Novel Open Set Energy-based Flow Classifier for Network Intrusion Detection
by: Souza, Manuela M. C., et al.
Published: (2021)
by: Souza, Manuela M. C., et al.
Published: (2021)
Online Self-Supervised Deep Learning for Intrusion Detection Systems
by: Nakıp, Mert, et al.
Published: (2023)
by: Nakıp, Mert, et al.
Published: (2023)
Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining
by: Vitale, Francesco, et al.
Published: (2026)
by: Vitale, Francesco, et al.
Published: (2026)
FetFIDS: A Feature Embedding Attention based Federated Network Intrusion Detection Algorithm
by: Ghosh, Shreya, et al.
Published: (2025)
by: Ghosh, Shreya, et al.
Published: (2025)
Evasion Adversarial Attacks Remain Impractical Against ML-based Network Intrusion Detection Systems, Especially Dynamic Ones
by: elShehaby, Mohamed, et al.
Published: (2023)
by: elShehaby, Mohamed, et al.
Published: (2023)
Multi-Agent Collaborative Intrusion Detection for Low-Altitude Economy IoT: An LLM-Enhanced Agentic AI Framework
by: Li, Hongjuan, et al.
Published: (2026)
by: Li, Hongjuan, et al.
Published: (2026)
Analyzing Unsolicited Internet Traffic: Measuring IoT Security Threats via Network Telescopes
by: Ismail, Shereen, et al.
Published: (2026)
by: Ismail, Shereen, et al.
Published: (2026)
Flow Exporter Impact on Intelligent Intrusion Detection Systems
by: Pinto, Daniela, et al.
Published: (2024)
by: Pinto, Daniela, et al.
Published: (2024)
Intelligent Green Efficiency for Intrusion Detection
by: Pereira, Pedro, et al.
Published: (2024)
by: Pereira, Pedro, et al.
Published: (2024)
Locality Sensitive Hashing for Network Traffic Fingerprinting
by: Mashnoor, Nowfel, et al.
Published: (2024)
by: Mashnoor, Nowfel, et al.
Published: (2024)
Developing a Transferable Federated Network Intrusion Detection System
by: Jameel, Abu Shafin Mohammad Mahdee, et al.
Published: (2025)
by: Jameel, Abu Shafin Mohammad Mahdee, et al.
Published: (2025)
Hiding in Plain Sight: An IoT Traffic Camouflage Framework for Enhanced Privacy
by: Worae, Daniel Adu, et al.
Published: (2025)
by: Worae, Daniel Adu, et al.
Published: (2025)
Enhancing Resilience for IoE: A Perspective of Networking-Level Safeguard
by: Yang, Guan-Yan, et al.
Published: (2025)
by: Yang, Guan-Yan, et al.
Published: (2025)
Similar Items
-
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2024) -
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2023) -
Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection
by: Vitorino, João, et al.
Published: (2024) -
Revisiting Network Traffic Analysis: Compatible network flows for ML models
by: Vitorino, João, et al.
Published: (2025) -
IoT Network Traffic Analysis with Deep Learning
by: Liu, Mei, et al.
Published: (2024)