Saved in:
| Main Authors: | Tripathy, Sudhanshu Sekhar, Behera, Bichitrananda |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.02438 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
A comprehensive survey of cybercrimes in India over the last decade
by: Tripathy, Sudhanshu Sekhar
Published: (2025)
by: Tripathy, Sudhanshu Sekhar
Published: (2025)
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System
by: Lin, Zong-Zhi, et al.
Published: (2022)
by: Lin, Zong-Zhi, et al.
Published: (2022)
Impacts of Data Preprocessing and Hyperparameter Optimization on the Performance of Machine Learning Models Applied to Intrusion Detection Systems
by: Lima, Mateus Guimarães, et al.
Published: (2024)
by: Lima, Mateus Guimarães, et al.
Published: (2024)
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
by: Ige, Tosin, et al.
Published: (2024)
by: Ige, Tosin, et al.
Published: (2024)
C-RADAR: A Centralized Deep Learning System for Intrusion Detection in Software Defined Networks
by: Mustafa, Osama, et al.
Published: (2024)
by: Mustafa, Osama, et al.
Published: (2024)
AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)
by: Guerra, Lorenzo, et al.
Published: (2024)
by: Guerra, Lorenzo, et al.
Published: (2024)
LEMDA: A Novel Feature Engineering Method for Intrusion Detection in IoT Systems
by: Ghubaish, Ali, et al.
Published: (2024)
by: Ghubaish, Ali, et al.
Published: (2024)
Continual Learning with Strategic Selection and Forgetting for Network Intrusion Detection
by: Zhang, Xinchen, et al.
Published: (2024)
by: Zhang, Xinchen, et al.
Published: (2024)
Automated and Explainable Denial of Service Analysis for AI-Driven Intrusion Detection Systems
by: Yakubu, Paul Badu, et al.
Published: (2025)
by: Yakubu, Paul Badu, et al.
Published: (2025)
Diffusion-based Adversarial Purification for Intrusion Detection
by: Merzouk, Mohamed Amine, et al.
Published: (2024)
by: Merzouk, Mohamed Amine, et al.
Published: (2024)
OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
by: Elouardi, Saida, et al.
Published: (2025)
by: Elouardi, Saida, et al.
Published: (2025)
Clustering-Enhanced Domain Adaptation for Cross-Domain Intrusion Detection in Industrial Control Systems
by: Wang, Luyao
Published: (2026)
by: Wang, Luyao
Published: (2026)
Multiple-Input Auto-Encoder Guided Feature Selection for IoT Intrusion Detection Systems
by: Dinh, Phai Vu, et al.
Published: (2024)
by: Dinh, Phai Vu, et al.
Published: (2024)
Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems
by: Ables, Jesse, et al.
Published: (2024)
by: Ables, Jesse, et al.
Published: (2024)
A Comprehensive Comparative Study of Individual ML Models and Ensemble Strategies for Network Intrusion Detection Systems
by: Bibers, Ismail, et al.
Published: (2024)
by: Bibers, Ismail, et al.
Published: (2024)
A Study on the Importance of Features in Detecting Advanced Persistent Threats Using Machine Learning
by: Hallaji, Ehsan, et al.
Published: (2025)
by: Hallaji, Ehsan, et al.
Published: (2025)
Open Set Dandelion Network for IoT Intrusion Detection
by: Wu, Jiashu, et al.
Published: (2023)
by: Wu, Jiashu, et al.
Published: (2023)
Explainable AI for Comparative Analysis of Intrusion Detection Models
by: Corea, Pap M., et al.
Published: (2024)
by: Corea, Pap M., et al.
Published: (2024)
Trustworthy Intrusion Detection: Confidence Estimation Using Latent Space
by: Pitsiorlas, Ioannis, et al.
Published: (2024)
by: Pitsiorlas, Ioannis, et al.
Published: (2024)
Privacy-Preserving Intrusion Detection using Convolutional Neural Networks
by: Kodys, Martin, et al.
Published: (2024)
by: Kodys, Martin, et al.
Published: (2024)
Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries
by: Çolhak, Furkan, et al.
Published: (2025)
by: Çolhak, Furkan, et al.
Published: (2025)
ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks
by: Sheikhi, Saeid, et al.
Published: (2026)
by: Sheikhi, Saeid, et al.
Published: (2026)
Detecting and Eliminating Neural Network Backdoors Through Active Paths with Application to Intrusion Detection
by: Høyheim, Eirik, et al.
Published: (2026)
by: Høyheim, Eirik, et al.
Published: (2026)
Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection
by: Zhang, Han, et al.
Published: (2024)
by: Zhang, Han, et al.
Published: (2024)
Enhancing Autonomous Online Intrusion Detection for IoT with Balanced Learning, Reliable Pseudo-Labels, and Lightweight Architectures
by: Afzaal, Hanzala, et al.
Published: (2026)
by: Afzaal, Hanzala, et al.
Published: (2026)
Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection
by: Guerra-Manzanares, Alejandro, et al.
Published: (2026)
by: Guerra-Manzanares, Alejandro, et al.
Published: (2026)
MI$^2$DAS: A Multi-Layer Intrusion Detection Framework with Incremental Learning for Securing Industrial IoT Networks
by: Lian, Wei, et al.
Published: (2026)
by: Lian, Wei, et al.
Published: (2026)
Hybrid LLM-Enhanced Intrusion Detection for Zero-Day Threats in IoT Networks
by: Al-Hammouri, Mohammad F., et al.
Published: (2025)
by: Al-Hammouri, Mohammad F., et al.
Published: (2025)
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection
by: Chaudhary, Devashish, et al.
Published: (2026)
by: Chaudhary, Devashish, et al.
Published: (2026)
A Novel Unified Lightweight Temporal-Spatial Transformer Approach for Intrusion Detection in Drone Networks
by: Biswas, Tarun Kumar, et al.
Published: (2025)
by: Biswas, Tarun Kumar, et al.
Published: (2025)
Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data
by: Shahzad, Muhammad Khuram, et al.
Published: (2026)
by: Shahzad, Muhammad Khuram, et al.
Published: (2026)
IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense
by: Panigrahi, Damodar, et al.
Published: (2024)
by: Panigrahi, Damodar, et al.
Published: (2024)
Machine Learning Transferability for Malware Detection
by: Vieira, César, et al.
Published: (2026)
by: Vieira, César, et al.
Published: (2026)
HybridGuard: Enhancing Minority-Class Intrusion Detection in Dew-Enabled Edge-of-Things Networks
by: Kara, Binayak, et al.
Published: (2025)
by: Kara, Binayak, et al.
Published: (2025)
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
by: Gluch, Greg, et al.
Published: (2025)
by: Gluch, Greg, et al.
Published: (2025)
XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT
by: Aslam, Ambreen, et al.
Published: (2026)
by: Aslam, Ambreen, et al.
Published: (2026)
StatAvg: Mitigating Data Heterogeneity in Federated Learning for Intrusion Detection Systems
by: Bouzinis, Pavlos S., et al.
Published: (2024)
by: Bouzinis, Pavlos S., et al.
Published: (2024)
Machine Learning-Based Security Policy Analysis
by: Jain, Krish, et al.
Published: (2024)
by: Jain, Krish, et al.
Published: (2024)
ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection
by: Khan, Irfan, et al.
Published: (2023)
by: Khan, Irfan, et al.
Published: (2023)
Similar Items
-
Hyperparameter Tuning-Based Optimized Performance Analysis of Machine Learning Algorithms for Network Intrusion Detection
by: Tripathy, Sudhanshu Sekhar, et al.
Published: (2025) -
A comprehensive survey of cybercrimes in India over the last decade
by: Tripathy, Sudhanshu Sekhar
Published: (2025) -
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System
by: Lin, Zong-Zhi, et al.
Published: (2022) -
Impacts of Data Preprocessing and Hyperparameter Optimization on the Performance of Machine Learning Models Applied to Intrusion Detection Systems
by: Lima, Mateus Guimarães, et al.
Published: (2024) -
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
by: Ige, Tosin, et al.
Published: (2024)