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A Novel Two-Stage Deep Learning Structure for Network Flow Anomaly Detection
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-981-16-9423-3_67openalex-snapshot
Research on Intrusion Detection Method Based on Deep Convolutional Neural Network
inferredcites →https://doi.org/10.1007/978-981-16-9885-9_37openalex-snapshot
EIDIMA: Edge-based Intrusion Detection of IoT Malware Attacks using Decision Tree-based Boosting Algorithms
inferredcites →https://doi.org/10.1016/j.knosys.2019.105124openalex-snapshot
Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues
inferredcites →https://doi.org/10.1049/iet-net.2018.5080openalex-snapshot
Towards an efficient anomaly‐based intrusion detection for software‐defined networks
inferredcites →https://doi.org/10.1088/1742-6596/2161/1/012043openalex-snapshot
Network intrusion detection: a comparative study of four classifiers using the NSL-KDD and KDD’99 datasets
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/access.2017.2762418openalex-snapshot
A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/access.2018.2863036openalex-snapshot
Enhanced Network Anomaly Detection Based on Deep Neural Networks
inferredcites →https://doi.org/10.1109/access.2018.2869577openalex-snapshot
Deep Learning Approach Combining Sparse Autoencoder With SVM for Network Intrusion Detection
inferredcites →https://doi.org/10.1109/cisda.2009.5356528openalex-snapshot
A detailed analysis of the KDD CUP 99 data set
inferredcites →https://doi.org/10.1109/cscloud.2017.39openalex-snapshot
Network Anomaly Detection with Stochastically Improved Autoencoder Based Models
inferredcites →https://doi.org/10.1109/ias.2009.124openalex-snapshot
Intrusion Detection Based on One-class SVM and SNMP MIB Data
inferredcites →https://doi.org/10.1109/icces45898.2019.9002221openalex-snapshot
A Network Intrusion Detection Approach Using Variant of Convolution Neural Network
inferredcites →https://doi.org/10.1109/wincom.2016.7777224openalex-snapshot
Deep learning approach for Network Intrusion Detection in Software Defined Networking
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
Reducing the Dimensionality of Data with Neural Networks
inferredcites →https://doi.org/10.1145/1390156.1390294openalex-snapshot
Extracting and composing robust features with denoising autoencoders
inferredcites →https://doi.org/10.3115/v1/d14-1179openalex-snapshot
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.3115/v1/d14-1181openalex-snapshot
Convolutional Neural Networks for Sentence Classification
inferredcites →https://doi.org/10.4108/eai.3-12-2015.2262516openalex-snapshot
A Deep Learning Approach for Network Intrusion Detection System
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-99-3010-4_49openalex-snapshot
AI with Deep Learning Model-Based Network Flow Anomaly Cyberattack Detection and Classification Model
inferred← citeshttps://doi.org/10.1007/s12083-025-01935-8openalex-snapshot
A hybrid software-defined networking approach for enhancing IoT cybersecurity with deep learning and blockchain in smart cities
inferred← citeshttps://doi.org/10.1007/s13042-025-02853-0openalex-snapshot
Raw binary data usage with deep learning for advanced persistent threat attacks early stage detection
inferred← citeshttps://doi.org/10.1007/s13132-024-01946-5openalex-snapshot
RETRACTED ARTICLE: Integrating Deep Learning and Reinforcement Learning for Enhanced Financial Risk Forecasting in Supply Chain Management
inferred← citeshttps://doi.org/10.1016/j.entcom.2026.101231openalex-snapshot
Semi-supervised deep learning for anomaly detection and audience sentiment analysis in entertainment news dissemination
inferred← citeshttps://doi.org/10.1016/j.jnca.2023.103760openalex-snapshot
Deep transfer learning for intrusion detection in industrial control networks: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.procs.2023.03.013openalex-snapshot
Anomaly-Based Intrusion Detection System using One-Dimensional Convolutional Neural Network
inferred← citeshttps://doi.org/10.1038/s41598-023-42618-9openalex-snapshot
Malicious traffic detection on sampled network flow data with novelty-detection-based models
inferred← citeshttps://doi.org/10.1038/s41598-026-35879-7openalex-snapshot
Novel transformer-based model for NID in fog computing environment
inferred← citeshttps://doi.org/10.1049/ise2/7990749openalex-snapshot
Anomaly Detection in an Open Set Environment Using Reinforcement Learning
inferred← citeshttps://doi.org/10.1051/e3sconf/202341201106openalex-snapshot
Anomaly-Based Intrusion Detection System To Detect Advanced Persistent Threats: Environmental Sustainability
inferred← citeshttps://doi.org/10.1109/access.2024.3389096openalex-snapshot
A Comparative Study of Using Deep Learning Algorithms in Network Intrusion Detection
inferred← citeshttps://doi.org/10.1109/icsintesa68165.2025.11413814openalex-snapshot
Deep Learning System for Network Anomaly Detection based Attention Mechanism and Sparse Autoencoder
inferred← citeshttps://doi.org/10.1109/icspc57692.2023.10125858openalex-snapshot
A Robust Deep Learning-based Approach for Network Traffic Classification using CNNs and RNNs
inferred← citeshttps://doi.org/10.3390/a18020069openalex-snapshot
Enhanced Hybrid Deep Learning Models-Based Anomaly Detection Method for Two-Stage Binary and Multi-Class Classification of Attacks in Intrusion Detection Systems
inferred← citeshttps://doi.org/10.3390/en15113951openalex-snapshot
Heuristic Intrusion Detection Based on Traffic Flow Statistical Analysis
inferred← citeshttps://doi.org/10.3390/jcp2030037openalex-snapshot
Generic Patterns for Intrusion Detection Systems in Service-Oriented Automotive and Medical Architectures
inferred← citeshttps://doi.org/10.7717/peerj-cs.2472openalex-snapshot
An optimized ensemble model with advanced feature selection for network intrusion detection
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