On the public citation graph

DBSCAN SMOTE LSTM: Effective Strategies for Distributed Denial of Service Detection in Imbalanced Network Environments

0 signed · 63 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

1 of the 52 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s11042-024-18744-5 (notice 2026-04-15).

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-75123-4_7openalex-snapshot

An Efficient Supervised Machine Learning Technique for Forecasting Stock Market Trends

inferredcites →https://doi.org/10.1007/978-3-030-77939-9_18openalex-snapshot

Playing First-Person Perspective Games with Deep Reinforcement Learning Using the State-of-the-Art Game-AI Research Platforms

inferredcites →https://doi.org/10.1007/978-3-031-78412-5_3openalex-snapshot

Anomaly Detection of Distributed Denial of Service (DDoS) in IoT Network Using Machine Learning

inferredcites →https://doi.org/10.1007/978-3-319-54978-1_17openalex-snapshot

Advanced Machine Language Approach to Detect DDoS Attack Using DBSCAN Clustering Technology with Entropy

inferredcites →https://doi.org/10.1007/s11042-021-11298-wopenalex-snapshot

An efficient deep learning technique for facial emotion recognition

inferredcites →https://doi.org/10.1007/s11042-024-18744-5openalex-snapshot

RETRACTED ARTICLE: An evolutionary KNN model for DDoS assault detection using genetic algorithm based optimization

inferredcites →https://doi.org/10.1007/s11280-012-0178-0openalex-snapshot

Effective detection of sophisticated online banking fraud on extremely imbalanced data

inferredcites →https://doi.org/10.1007/s12083-023-01460-6openalex-snapshot

An efficient DDoS attack detection and categorization using adolescent identity search-based weighted SVM model

inferredcites →https://doi.org/10.1007/s13748-016-0094-0openalex-snapshot

Learning from imbalanced data: open challenges and future directions

inferredcites →https://doi.org/10.1007/s13755-018-0051-3openalex-snapshot

The effects of varying class distribution on learner behavior for medicare fraud detection with imbalanced big data

inferredcites →https://doi.org/10.1016/j.comnet.2004.08.014openalex-snapshot

Real-time detection of distributed denial-of-service attacks using RBF networks and statistical features

inferredcites →https://doi.org/10.1016/j.eswa.2020.114520openalex-snapshot

Detection of DDoS attacks with feed forward based deep neural network model

inferredcites →https://doi.org/10.1016/j.gexplo.2024.107393openalex-snapshot

Intelligent mapping of geochemical anomalies: Adaptation of DBSCAN and mean-shift clustering approaches

inferredcites →https://doi.org/10.1016/j.jocs.2022.101614openalex-snapshot

Weighted Ensemble with one-class Classification and Over-sampling and Instance selection (WECOI): An approach for learning from imbalanced data streams

inferredcites →https://doi.org/10.1016/j.knosys.2022.108217openalex-snapshot

Two density-based sampling approaches for imbalanced and overlapping data

inferredcites →https://doi.org/10.1016/j.neucom.2022.05.017openalex-snapshot

PF-SMOTE: A novel parameter-free SMOTE for imbalanced datasets

inferredcites →https://doi.org/10.1016/j.neunet.2018.07.011openalex-snapshot

A systematic study of the class imbalance problem in convolutional neural networks

inferredcites →https://doi.org/10.1016/j.procs.2021.05.025openalex-snapshot

Network Intrusion Detection System using Deep Learning

inferredcites →https://doi.org/10.1016/j.teler.2023.100053openalex-snapshot

DCNNBiLSTM: An Efficient Hybrid Deep Learning-Based Intrusion Detection System

inferredcites →https://doi.org/10.1023/a:1007452223027openalex-snapshot

Machine Learning for the Detection of Oil Spills in Satellite Radar Images

inferredcites →https://doi.org/10.1049/cps2.12013openalex-snapshot

Network intrusion detection using machine learning approaches: Addressing data imbalance

inferredcites →https://doi.org/10.1080/23742917.2023.2264435openalex-snapshot

Modeling DDOS attacks in sdn and detection using random forest classifier

inferredcites →https://doi.org/10.1109/access.2020.2987842openalex-snapshot

Classification of Poetry Text Into the Emotional States Using Deep Learning Technique

inferredcites →https://doi.org/10.1109/access.2020.3009733openalex-snapshot

An Evolutionary SVM Model for DDOS Attack Detection in Software Defined Networks

inferredcites →https://doi.org/10.1109/access.2022.3172304openalex-snapshot

Cyber Threats Detection in Smart Environments Using SDN-Enabled DNN-LSTM Hybrid Framework

inferredcites →https://doi.org/10.1109/access.2023.3328951openalex-snapshot

Enhancing the Efficiency of Gaussian Naïve Bayes Machine Learning Classifier in the Detection of DDOS in Cloud Computing

inferredcites →https://doi.org/10.1109/aimla59606.2024.10531330openalex-snapshot

Hybrid SVM Approach for Enhanced DDoS Attack Detection Using Machine Learning in Cloud Environment

inferredcites →https://doi.org/10.1109/globecom38437.2019.9013892openalex-snapshot

Tree-Based Intelligent Intrusion Detection System in Internet of Vehicles

inferredcites →https://doi.org/10.1109/icacci.2017.8126031openalex-snapshot

Detection of distributed denial of service attacks using machine learning algorithms in software defined networks

inferredcites →https://doi.org/10.1109/icmla.2018.00125openalex-snapshot

An Empirical Study on Class Rarity in Big Data

inferredcites →https://doi.org/10.1109/jiot.2021.3084796openalex-snapshot

MTH-IDS: A Multitiered Hybrid Intrusion Detection System for Internet of Vehicles

inferredcites →https://doi.org/10.1109/jiot.2022.3196942openalex-snapshot

An Efficient Hybrid-DNN for DDoS Detection and Classification in Software-Defined IIoT Networks

inferredcites →https://doi.org/10.1109/mipr.2018.00027openalex-snapshot

Dynamic Sampling in Convolutional Neural Networks for Imbalanced Data Classification

inferredcites →https://doi.org/10.1109/ntict.2017.7976107openalex-snapshot

A modified DBSCAN clustering algorithm for proactive detection of DDoS attacks

inferredcites →https://doi.org/10.1109/smarttechcon57526.2023.10391376openalex-snapshot

Machine Learning Approaches for DDoS Attack Detection: Naive Bayes vs Logistic Regression

inferredcites →https://doi.org/10.1109/tnnls.2021.3136503openalex-snapshot

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

inferredcites →https://doi.org/10.1145/1147234.1147236openalex-snapshot

Data mining for improved cardiac care

inferredcites →https://doi.org/10.1145/3440749.3442606openalex-snapshot

Real-Time DDoS flood Attack Monitoring and Detection (RT-AMD) Model for Cloud Computing

inferredcites →https://doi.org/10.1155/2022/6473507openalex-snapshot

Intrusion Detection System for IoT Based on Deep Learning and Modified Reptile Search Algorithm

inferredcites →https://doi.org/10.1186/s40537-018-0138-3openalex-snapshot

Big Data fraud detection using multiple medicare data sources

inferredcites →https://doi.org/10.1186/s40537-019-0192-5openalex-snapshot

Survey on deep learning with class imbalance

inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot

SMOTE: Synthetic Minority Over-sampling Technique

inferredcites →https://doi.org/10.23919/indiacom49435.2020.9083716openalex-snapshot

Detection of DDoS Attacks using Machine Learning Algorithms

inferredcites →https://doi.org/10.32604/cmc.2020.06177openalex-snapshot

DDoS Attack Detection via Multi-scale Convolutional Neural Network

inferredcites →https://doi.org/10.3390/app11115213openalex-snapshot

Detection of Unknown DDoS Attacks with Deep Learning and Gaussian Mixture Model

inferredcites →https://doi.org/10.3390/app112411634openalex-snapshot

Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection

inferredcites →https://doi.org/10.3390/app13137872openalex-snapshot

Real-Time Detection of DDoS Attacks Based on Random Forest in SDN

inferredcites →https://doi.org/10.3390/electronics12143103openalex-snapshot

DDoS Attack Detection in IoT-Based Networks Using Machine Learning Models: A Survey and Research Directions

inferredcites →https://doi.org/10.3390/electronics9030413openalex-snapshot

A DDoS Attack Mitigation Scheme in ISP Networks Using Machine Learning Based on SDN

inferredcites →https://doi.org/10.3390/math12091294openalex-snapshot

Improvement of Distributed Denial of Service Attack Detection through Machine Learning and Data Processing

inferredcites →https://doi.org/10.3390/proceedings2020063051openalex-snapshot

A Machine Learning Approach for DDoS (Distributed Denial of Service) Attack Detection Using Multiple Linear Regression

inferredcites →https://doi.org/10.3390/su12031035openalex-snapshot

Detecting DDoS Attacks in Software-Defined Networks Through Feature Selection Methods and Machine Learning Models

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-23314-1_20openalex-snapshot

Accurate Hybrid Intrusion Detection Model for IoT Networks Using MCA, DBSCAN, and XGBoost

inferred← citeshttps://doi.org/10.1007/s41870-025-02977-0openalex-snapshot

Permission-level risk profiling and anomaly detection in IoT using machine learning

inferred← citeshttps://doi.org/10.1038/s41598-025-91300-9openalex-snapshot

Predictive methods for CO2 emissions and energy use in vehicles at intersections

inferred← citeshttps://doi.org/10.1109/access.2025.3531659openalex-snapshot

TCN-Based DDoS Detection and Mitigation in 5G Healthcare-IoT: A Frequency Monitoring and Dynamic Threshold Approach

inferred← citeshttps://doi.org/10.1109/icast68191.2025.11300066openalex-snapshot

Hybrid DBSCAN-SMOTE with Attention-Augmented MLP for Detecting Low-Frequency DDoS Attacks in Imbalanced Network Traffic

inferred← citeshttps://doi.org/10.1109/icetics69505.2026.11651082openalex-snapshot

Performance of Feature Reduction Techniques for Efficient Intrusion Detection System

inferred← citeshttps://doi.org/10.1109/idicaihei65991.2025.11379345openalex-snapshot

Enhancing Cloud Cybersecurity with AI-Driven Big Data for DDoS Attacks Threat Prediction

inferred← citeshttps://doi.org/10.1109/siml65326.2025.11081135openalex-snapshot

Fraud Detection in Indonesian Administrative Health Records Using Cluster-Based Oversampling Methods

inferred← citeshttps://doi.org/10.22214/ijraset.2025.69784openalex-snapshot

Distributed Denial of Service Attack Detection Model for Peer to Peer (P2P) Networks

inferred← citeshttps://doi.org/10.3844/jcssp.2025.146.157openalex-snapshot

The Optimized Extreme Learning Machine (GA-OELM) for DDoS Attack Detection in Cloud Environment

inferred← citeshttps://doi.org/10.48084/etasr.9909openalex-snapshot

Optimizing Neural Network Architecture for Detecting DDOS Attacks using ANN and XGBoost in Imbalanced Networks

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.