CNN-based IoT Device Identification: A Comparative Study on Payload vs. Fingerprint
Fuente:
arXiv
Saved in:
| Main Author: | Kostas, Kahraman |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
IoT Device Identification with Machine Learning: Common Pitfalls and Best Practices
by: Kostas, Kahraman, et al.
Published: (2026)
by: Kostas, Kahraman, et al.
Published: (2026)
GeMID: Generalizable Models for IoT Device Identification
by: Kostas, Kahraman, et al.
Published: (2024)
by: Kostas, Kahraman, et al.
Published: (2024)
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
by: Kostas, Kahraman, et al.
Published: (2023)
by: Kostas, Kahraman, et al.
Published: (2023)
Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
by: Gueriani, Afrah, et al.
Published: (2024)
by: Gueriani, Afrah, et al.
Published: (2024)
RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT
by: Celdrán, Alberto Huertas, et al.
Published: (2022)
by: Celdrán, Alberto Huertas, et al.
Published: (2022)
LLM-Driven Auto Configuration for Transient IoT Device Collaboration
by: Shastri, Hetvi, et al.
Published: (2025)
by: Shastri, Hetvi, et al.
Published: (2025)
Optimized Ensemble Model Towards Secured Industrial IoT Devices
by: Injadat, MohammadNoor
Published: (2024)
by: Injadat, MohammadNoor
Published: (2024)
Efficient IoT Intrusion Detection with an Improved Attention-Based CNN-BiLSTM Architecture
by: Naeem, Amna, et al.
Published: (2025)
by: Naeem, Amna, et al.
Published: (2025)
Towards Sustainable IoT: Challenges, Solutions, and Future Directions for Device Longevity
by: Shirvani, Ghazaleh, et al.
Published: (2024)
by: Shirvani, Ghazaleh, et al.
Published: (2024)
There Are No Silly Questions: Evaluation of Offline LLM Capabilities from a Turkish Perspective
by: Yilmaz, Edibe, et al.
Published: (2026)
by: Yilmaz, Edibe, et al.
Published: (2026)
Memory-Efficient and Secure DNN Inference on TrustZone-enabled Consumer IoT Devices
by: Xie, Xueshuo, et al.
Published: (2024)
by: Xie, Xueshuo, et al.
Published: (2024)
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices
by: Zhang, Han, et al.
Published: (2024)
by: Zhang, Han, et al.
Published: (2024)
Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices
by: Ferrag, Mohamed Amine, et al.
Published: (2023)
by: Ferrag, Mohamed Amine, et al.
Published: (2023)
Graph-Based Floor Separation Using Node Embeddings and Clustering of WiFi Trajectories
by: Kostas, Rabia Yasa, et al.
Published: (2025)
by: Kostas, Rabia Yasa, et al.
Published: (2025)
Hybrid Machine Learning Models for Intrusion Detection in IoT: Leveraging a Real-World IoT Dataset
by: Akif, Md Ahnaf, et al.
Published: (2025)
by: Akif, Md Ahnaf, et al.
Published: (2025)
Threat Modeling for Enhancing Security of IoT Audio Classification Devices under a Secure Protocols Framework
by: Benlloch-Lopez, Sergio, et al.
Published: (2025)
by: Benlloch-Lopez, Sergio, et al.
Published: (2025)
Securing Healthcare with Deep Learning: A CNN-Based Model for medical IoT Threat Detection
by: Mohamadi, Alireza, et al.
Published: (2024)
by: Mohamadi, Alireza, et al.
Published: (2024)
Deep learning based intelligent IDS for Large-scale IoT networks
by: Andrade, Isha, et al.
Published: (2026)
by: Andrade, Isha, et al.
Published: (2026)
Adversarial-Resilient RF Fingerprinting: A CNN-GAN Framework for Rogue Transmitter Detection
by: Dhakal, Raju, et al.
Published: (2025)
by: Dhakal, Raju, et al.
Published: (2025)
Security Risks Concerns of Generative AI in the IoT
by: Xu, Honghui, et al.
Published: (2024)
by: Xu, Honghui, et al.
Published: (2024)
Dealing with Imbalanced Classes in Bot-IoT Dataset
by: Atuhurra, Jesse, et al.
Published: (2024)
by: Atuhurra, Jesse, et al.
Published: (2024)
Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection
by: Kostas, Kahraman, et al.
Published: (2024)
by: Kostas, Kahraman, et al.
Published: (2024)
LLM-based Multi-class Attack Analysis and Mitigation Framework in IoT/IIoT Networks
by: Ikbarieh, Seif, et al.
Published: (2025)
by: Ikbarieh, Seif, et al.
Published: (2025)
Edge AI-based Radio Frequency Fingerprinting for IoT Networks
by: Hussain, Ahmed Mohamed, et al.
Published: (2024)
by: Hussain, Ahmed Mohamed, et al.
Published: (2024)
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them
by: Liu, Chao, et al.
Published: (2024)
by: Liu, Chao, et al.
Published: (2024)
Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study
by: Friji, Hamdi, et al.
Published: (2024)
by: Friji, Hamdi, et al.
Published: (2024)
A Cutting-Edge Deep Learning Method For Enhancing IoT Security
by: Ansar, Nadia, et al.
Published: (2024)
by: Ansar, Nadia, et al.
Published: (2024)
Evaluating Language Models For Threat Detection in IoT Security Logs
by: Tejero-Fernández, Jorge J., et al.
Published: (2025)
by: Tejero-Fernández, Jorge J., et al.
Published: (2025)
UTF:Undertrained Tokens as Fingerprints A Novel Approach to LLM Identification
by: Cai, Jiacheng, et al.
Published: (2024)
by: Cai, Jiacheng, et al.
Published: (2024)
A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
An Optimized Decision Tree-Based Framework for Explainable IoT Anomaly Detection
by: Ashikuzzaman, et al.
Published: (2026)
by: Ashikuzzaman, et al.
Published: (2026)
Cracking IoT Security: Can LLMs Outsmart Static Analysis Tools?
by: Quantrill, Jason, et al.
Published: (2026)
by: Quantrill, Jason, et al.
Published: (2026)
BARTPredict: Empowering IoT Security with LLM-Driven Cyber Threat Prediction
by: Diaf, Alaeddine, et al.
Published: (2025)
by: Diaf, Alaeddine, et al.
Published: (2025)
An Approach To Enhance IoT Security In 6G Networks Through Explainable AI
by: Kaur, Navneet, et al.
Published: (2024)
by: Kaur, Navneet, et al.
Published: (2024)
RESTRAIN: Reinforcement Learning-Based Secure Framework for Trigger-Action IoT Environment
by: Alam, Md Morshed, et al.
Published: (2025)
by: Alam, Md Morshed, et al.
Published: (2025)
From Hardware Fingerprint to Access Token: Enhancing the Authentication on IoT Devices
by: Xiao, Yue, et al.
Published: (2024)
by: Xiao, Yue, et al.
Published: (2024)
Real-time ML-based Defense Against Malicious Payload in Reconfigurable Embedded Systems
by: Stahle-Smith, Rye, et al.
Published: (2025)
by: Stahle-Smith, Rye, et al.
Published: (2025)
Optimized detection of cyber-attacks on IoT networks via hybrid deep learning models
by: Bensaoud, Ahmed, et al.
Published: (2025)
by: Bensaoud, Ahmed, et al.
Published: (2025)
Beyond Detection: Leveraging Large Language Models for Cyber Attack Prediction in IoT Networks
by: Diaf, Alaeddine, et al.
Published: (2024)
by: Diaf, Alaeddine, et al.
Published: (2024)
PrivLLMSwarm: Privacy-Preserving LLM-Driven UAV Swarms for Secure IoT Surveillance
by: Ayana, Jifar Wakuma, et al.
Published: (2025)
by: Ayana, Jifar Wakuma, et al.
Published: (2025)
Similar Items
-
IoT Device Identification with Machine Learning: Common Pitfalls and Best Practices
by: Kostas, Kahraman, et al.
Published: (2026) -
GeMID: Generalizable Models for IoT Device Identification
by: Kostas, Kahraman, et al.
Published: (2024) -
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
by: Kostas, Kahraman, et al.
Published: (2023) -
Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
by: Gueriani, Afrah, et al.
Published: (2024) -
RL and Fingerprinting to Select Moving Target Defense Mechanisms for Zero-day Attacks in IoT
by: Celdrán, Alberto Huertas, et al.
Published: (2022)