On the public citation graph

Collaborative Federated Learning-Based Model for Alert Correlation and Attack Scenario Recognition

https://doi.org/10.3390/electronics12214509

0 signed · 50 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.

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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-981-15-9129-7_36openalex-snapshot

Detecting Advanced Persistent Threat in Edge Computing via Federated Learning

inferredcites →https://doi.org/10.1007/s10207-022-00631-5openalex-snapshot

A novel approach for detection of APT malware using multi-dimensional hybrid Bayesian belief network

inferredcites →https://doi.org/10.1007/s11036-020-01586-4openalex-snapshot

FedMEC: Improving Efficiency of Differentially Private Federated Learning via Mobile Edge Computing

inferredcites →https://doi.org/10.1016/j.comnet.2022.109116openalex-snapshot

Which open-source IDS? Snort, Suricata or Zeek

inferredcites →https://doi.org/10.1016/j.compind.2022.103692openalex-snapshot

Light-weight federated learning-based anomaly detection for time-series data in industrial control systems

inferredcites →https://doi.org/10.1016/j.compind.2022.103741openalex-snapshot

Multi-step attack detection in industrial control systems using causal analysis

inferredcites →https://doi.org/10.1016/j.cosrev.2021.100379openalex-snapshot

A survey on deep learning and its applications

inferredcites →https://doi.org/10.1016/j.future.2018.06.055openalex-snapshot

Detection of advanced persistent threat using machine-learning correlation analysis

inferredcites →https://doi.org/10.1016/j.future.2019.01.056openalex-snapshot

A semantic-based correlation approach for detecting hybrid and low-level APTs

inferredcites →https://doi.org/10.1016/j.procs.2020.04.070openalex-snapshot

Shallow and Deep Learning Approaches for Network Intrusion Alert Prediction

inferredcites →https://doi.org/10.1016/j.procs.2022.12.227openalex-snapshot

Federated Learning as a Privacy Solution - An Overview

inferredcites →https://doi.org/10.1109/access.2020.3021499openalex-snapshot

Alerts Correlation and Causal Analysis for APT Based Cyber Attack Detection

inferredcites →https://doi.org/10.1109/access.2020.3041793openalex-snapshot

Intrusion Detection for Wireless Edge Networks Based on Federated Learning

inferredcites →https://doi.org/10.1109/access.2022.3165809openalex-snapshot

Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning

inferredcites →https://doi.org/10.1109/access.2022.3206367openalex-snapshot

Anomaly Detection Based on CNN and Regularization Techniques Against Zero-Day Attacks in IoT Networks

inferredcites →https://doi.org/10.1109/icc.2016.7511197openalex-snapshot

Detection of command and control in advanced persistent threat based on independent access

inferredcites →https://doi.org/10.1109/icosp.2006.345752openalex-snapshot

Classification of Imbalanced Data by Using the SMOTE Algorithm and Locally Linear Embedding

inferredcites →https://doi.org/10.1109/ipccc55026.2022.9894354openalex-snapshot

An Abnormal Traffic Detection Method for IoT Devices Based on Federated Learning and Depthwise Separable Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/iscit55906.2022.9931222openalex-snapshot

Federated Learning-Based Cyber Threat Hunting for APT Attack Detection in SDN-Enabled Networks

inferredcites →https://doi.org/10.1109/milcis.2015.7348942openalex-snapshot

UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)

inferredcites →https://doi.org/10.1109/mnet.011.2000286openalex-snapshot

Internet of Things Intrusion Detection: Centralized, On-Device, or Federated Learning?

inferredcites →https://doi.org/10.1145/2939672.2939783openalex-snapshot

Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs

inferredcites →https://doi.org/10.1145/3474374.3486918openalex-snapshot

Multi-Stage Attack Detection via Kill Chain State Machines

inferredcites →https://doi.org/10.1186/s40537-020-00379-6openalex-snapshot

Performance Analysis of Intrusion Detection Systems Using a Feature Selection Method on the UNSW-NB15 Dataset

inferredcites →https://doi.org/10.1186/s40537-023-00694-8openalex-snapshot

IGRF-RFE: a hybrid feature selection method for MLP-based network intrusion detection on UNSW-NB15 dataset

inferredcites →https://doi.org/10.1371/journal.pone.0166017openalex-snapshot

Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

inferredcites →https://doi.org/10.3389/fonc.2023.1230434openalex-snapshot

Using deep DenseNet with cyclical learning rate to classify leukocytes for leukemia identification

inferredcites →https://doi.org/10.3390/a10020039openalex-snapshot

From Intrusion Detection to an Intrusion Response System: Fundamentals, Requirements, and Future Directions

inferredcites →https://doi.org/10.3390/app12136816openalex-snapshot

APT-Attack Detection Based on Multi-Stage Autoencoders

inferredcites →https://doi.org/10.3390/app13031252openalex-snapshot

Explainable Artificial Intelligence (XAI) for Intrusion Detection and Mitigation in Intelligent Connected Vehicles: A Review

inferredcites →https://doi.org/10.3390/app8122663openalex-snapshot

Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study

inferredcites →https://doi.org/10.3390/app9204396openalex-snapshot

Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey

inferredcites →https://doi.org/10.3390/biomedicines10112971openalex-snapshot

A Hybrid Workflow of Residual Convolutional Transformer Encoder for Breast Cancer Classification Using Digital X-ray Mammograms

inferredcites →https://doi.org/10.3390/diagnostics13010089openalex-snapshot

ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images

inferredcites →https://doi.org/10.3390/electronics11213571openalex-snapshot

Performance Investigation of Principal Component Analysis for Intrusion Detection System Using Different Support Vector Machine Kernels

inferredcites →https://doi.org/10.3390/electronics9020219openalex-snapshot

A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU

inferredcites →https://doi.org/10.3390/jpm12101584openalex-snapshot

Comparative Analysis between Individual, Centralized, and Federated Learning for Smartwatch Based Stress Detection

inferredcites →https://doi.org/10.3390/sym14020195openalex-snapshot

Applying Federated Learning in Software-Defined Networks: A Survey

What points at this work

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

inferred← citeshttps://doi.org/10.1007/s10586-024-05070-6openalex-snapshot

Navigating the fusion of federated learning and big data: a systematic review for the AI landscape

inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104009openalex-snapshot

MA_BiRAE - Malware analysis and detection technique using adversarial learning and deep learning

inferred← citeshttps://doi.org/10.1038/s41598-025-96527-0openalex-snapshot

A hybrid explainable federated-based vision transformer framework for breast cancer prediction via risk factors

inferred← citeshttps://doi.org/10.1109/icaase64542.2024.10851089openalex-snapshot

Privacy-Preserving in Agricultural IoT: Intrusion Detection Using Federated Learning and CNN

inferred← citeshttps://doi.org/10.1109/icacrs67045.2025.11324159openalex-snapshot

Exploring the Potential of Ensemble and XAI for Effective IoT Multiclass Malware Detection

inferred← citeshttps://doi.org/10.1109/iconstem65670.2025.11374875openalex-snapshot

Federated Learning Framework for Risk Diagnosis in Enterprise Information Security model

inferred← citeshttps://doi.org/10.1109/ojvt.2025.3576366openalex-snapshot

Explainable Federated Framework for Enhanced Security and Privacy in Connected Vehicles Against Advanced Persistent Threats

inferred← citeshttps://doi.org/10.3390/bdcc9070185openalex-snapshot

Adaptive, Privacy-Enhanced Real-Time Fraud Detection in Banking Networks Through Federated Learning and VAE-QLSTM Fusion

inferred← citeshttps://doi.org/10.3390/electronics13061106openalex-snapshot

Advanced Persistent Threat Group Correlation Analysis via Attack Behavior Patterns and Rough Sets

inferred← citeshttps://doi.org/10.3390/electronics14020261openalex-snapshot

Optimization Scheme of Collaborative Intrusion Detection System Based on Blockchain Technology

inferred← citeshttps://doi.org/10.58496/mjcs/2025/068openalex-snapshot

Enhancing Advanced Persistent Threat Detection with Federated Learning and Neural Networks for Secure Cloud Computer Environment

inferred← citeshttps://doi.org/10.7753/ijcatr1301.1003openalex-snapshot

Alert Correlation Model Based on Hybrid Machine Learning Techniques to Enhance the Performance of NIDS

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.