On the public citation graph
A Systematic Review of Machine Learning Approaches for Intrusion Detection: Insights from Logistic Regression
0 signed · 16 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10586-020-03082-6openalex-snapshot
FCM–SVM based intrusion detection system for cloud computing environment
inferredcites →https://doi.org/10.1007/s11277-022-10030-7openalex-snapshot
An Optimal Cluster Based Intrusion Detection System for Defence Against Attack in Web and Cloud Computing Environments
inferredcites →https://doi.org/10.1016/j.dajour.2024.100478openalex-snapshot
A comparative assessment of machine learning algorithms in the IoT-based network intrusion detection systems
inferredcites →https://doi.org/10.1016/j.future.2019.03.043openalex-snapshot
A deep learning approach for proactive multi-cloud cooperative intrusion detection system
inferredcites →https://doi.org/10.1016/s1353-4858(20)30056-8openalex-snapshot
Hybrid intrusion detection system using machine learning
inferredcites →https://doi.org/10.1109/access.2017.2782159openalex-snapshot
Cloud-Based Cyber-Physical Intrusion Detection for Vehicles Using Deep Learning
inferredcites →https://doi.org/10.1109/access.2023.3289405openalex-snapshot
An Improved Design for a Cloud Intrusion Detection System Using Hybrid Features Selection Approach With ML Classifier
inferredcites →https://doi.org/10.1109/access.2024.3389096openalex-snapshot
A Comparative Study of Using Deep Learning Algorithms in Network Intrusion Detection
inferredcites →https://doi.org/10.1109/cetic4.2018.8530912openalex-snapshot
Machine Learning Based Intrusion Detection for Virtualized Infrastructures
inferredcites →https://doi.org/10.1109/sera.2019.8886794openalex-snapshot
Hybrid Intrusion Detection System Using Machine Learning Techniques in Cloud Computing Environments
inferredcites →https://doi.org/10.1145/3485557.3485562openalex-snapshot
Cloud-based Network Intrusion Detection System using Deep Learning
inferredcites →https://doi.org/10.1186/s13677-022-00329-yopenalex-snapshot
Cloud-based multiclass anomaly detection and categorization using ensemble learning
inferredcites →https://doi.org/10.1186/s13677-023-00509-4openalex-snapshot
Intelligent intrusion detection framework for multi-clouds – IoT environment using swarm-based deep learning classifier
inferredcites →https://doi.org/10.26599/bdma.2022.9020038openalex-snapshot
Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques
inferredcites →https://doi.org/10.3233/mgs-220360openalex-snapshot
Hybrid machine learning approach based intrusion detection in cloud: A metaheuristic assisted model
inferredcites →https://doi.org/10.3390/app13179588openalex-snapshot
Towards an Intelligent Intrusion Detection System to Detect Malicious Activities in Cloud Computing
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.