On the public citation graph

Quantum-Enhanced Machine Learning for Cybersecurity: Evaluating Malicious URL Detection

https://doi.org/10.3390/electronics14091827

0 signed · 59 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-3-319-46298-1_30openalex-snapshot

Detecting Malicious URLs Using Lexical Analysis

inferredcites →https://doi.org/10.1007/s11276-024-03700-wopenalex-snapshot

Detection of malicious URLs using machine learning

inferredcites →https://doi.org/10.1007/s11416-022-00435-0openalex-snapshot

Security intrusion detection using quantum machine learning techniques

inferredcites →https://doi.org/10.1007/s12652-018-0798-zopenalex-snapshot

A machine learning based approach for phishing detection using hyperlinks information

inferredcites →https://doi.org/10.1016/0020-0255(94)00095-sopenalex-snapshot

On quantum neural computing

inferredcites →https://doi.org/10.1016/j.asoc.2019.105662openalex-snapshot

An empirical comparison and evaluation of minority oversampling techniques on a large number of imbalanced datasets

inferredcites →https://doi.org/10.1016/j.dib.2020.106304openalex-snapshot

Malicious and Benign Webpages Dataset

inferredcites →https://doi.org/10.1016/j.eswa.2016.12.035openalex-snapshot

Learning from class-imbalanced data: Review of methods and applications

inferredcites →https://doi.org/10.1016/j.ijinfomgt.2024.102776openalex-snapshot

How could quantum computing shape information systems research – An editorial perspective and future research directions

inferredcites →https://doi.org/10.1016/j.neucom.2019.10.118openalex-snapshot

A comprehensive survey on support vector machine classification: Applications, challenges and trends

inferredcites →https://doi.org/10.1016/j.patcog.2020.107262openalex-snapshot

Radial-Based Undersampling for imbalanced data classification

inferredcites →https://doi.org/10.1038/s41598-022-10841-5openalex-snapshot

An effective detection approach for phishing websites using URL and HTML features

inferredcites →https://doi.org/10.1103/physreva.107.062417openalex-snapshot

Numerical evidence against advantage with quantum fidelity kernels on classical data

inferredcites →https://doi.org/10.1103/physrevlett.114.140504openalex-snapshot

Experimental Realization of a Quantum Support Vector Machine

inferredcites →https://doi.org/10.1109/acait60137.2023.10528600openalex-snapshot

A Review of Data-Driven Approaches for Malicious Website Detection

inferredcites →https://doi.org/10.1109/access.2022.3222307openalex-snapshot

Detecting Malicious URLs Using Machine Learning Techniques: Review and Research Directions

inferredcites →https://doi.org/10.1109/access.2024.3462434openalex-snapshot

When to Use Standardization and Normalization: Empirical Evidence From Machine Learning Models and XAI

inferredcites →https://doi.org/10.1109/coins51742.2021.9524269openalex-snapshot

Malicious URL Detection using Logistic Regression

inferredcites →https://doi.org/10.1109/ebiss.2009.5138008openalex-snapshot

Malicious Web Pages Detection Based on Abnormal Visibility Recognition

inferredcites →https://doi.org/10.1109/iccit52419.2022.9711614openalex-snapshot

A Systematic Approach for Malware URL Recognition

inferredcites →https://doi.org/10.1109/infcom.2010.5462216openalex-snapshot

PhishNet: Predictive Blacklisting to Detect Phishing Attacks

inferredcites →https://doi.org/10.1145/1314389.1314391openalex-snapshot

A framework for detection and measurement of phishing attacks

inferredcites →https://doi.org/10.1145/2063176.2063197openalex-snapshot

The state of phishing attacks

inferredcites →https://doi.org/10.1145/3308558.3316498openalex-snapshot

Domain Generation Algorithms detection through deep neural network and ensemble

inferredcites →https://doi.org/10.1155/2022/3241216openalex-snapshot

An Assessment of Lexical, Network, and Content-Based Features for Detecting Malicious URLs Using Machine Learning and Deep Learning Models

inferredcites →https://doi.org/10.18293/seke2015-182openalex-snapshot

Combining Feature Subset Selection and Data Sampling for Coping with Highly Imbalanced Software Data

inferredcites →https://doi.org/10.3390/app122312025openalex-snapshot

Towards Explainable Quantum Machine Learning for Mobile Malware Detection and Classification

inferredcites →https://doi.org/10.3390/e24111656openalex-snapshot

A Preprocessing Perspective for Quantum Machine Learning Classification Advantage in Finance Using NISQ Algorithms

inferredcites →https://doi.org/10.3390/electronics10121492openalex-snapshot

Deep Character-Level Anomaly Detection Based on a Convolutional Autoencoder for Zero-Day Phishing URL Detection

inferredcites →https://doi.org/10.3390/electronics12214423openalex-snapshot

Stratified Sampling-Based Deep Learning Approach to Increase Prediction Accuracy of Unbalanced Dataset

inferredcites →https://doi.org/10.3390/info14010054openalex-snapshot

A Comparison of Undersampling, Oversampling, and SMOTE Methods for Dealing with Imbalanced Classification in Educational Data Mining

inferredcites →https://doi.org/10.3390/jcp1010011openalex-snapshot

Enhancing Machine Learning Prediction in Cybersecurity Using Dynamic Feature Selector

inferredcites →https://doi.org/10.3390/s23146439openalex-snapshot

Novel ANOVA-Statistic-Reduced Deep Fully Connected Neural Network for the Damage Grade Prediction of Post-Earthquake Buildings

inferredcites →https://doi.org/10.4103/picr.picr_87_17openalex-snapshot

Common pitfalls in statistical analysis: Logistic regression

What points at this work

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

inferred← citeshttps://doi.org/10.1002/ett.70439openalex-snapshot

Quantum ML , Generative AI , and Information Fusion for Cloud Security in IoT ‐Enabled Sustainable Smart Cities: Innovation, Approaches, and Challenges

inferred← citeshttps://doi.org/10.1002/spe.70106openalex-snapshot

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

inferred← citeshttps://doi.org/10.1007/978-3-032-22917-5_9openalex-snapshot

Quantum-Driven Digital Forensics: Evidence Acquisition, Intrusion Detection, Cybercrime Simulation, and DNA Profiling

inferred← citeshttps://doi.org/10.1007/s10586-026-06579-8openalex-snapshot

A hybrid framework for malware detection leveraging abstract syntax trees, L-moments, and multi-dimensional graphs with quantum-inspired neural networks

inferred← citeshttps://doi.org/10.1007/s11227-026-08300-3openalex-snapshot

Quantum kernel anomaly detection: a fidelity-based framework for robust behavioral biometric authentication

inferred← citeshttps://doi.org/10.1007/s40998-026-01109-zopenalex-snapshot

A Privacy-Preserving Quantum Learning Framework for Intrusion Detection using Electric Eel Brown-Bear Algorithm based Deep Learning

inferred← citeshttps://doi.org/10.1007/s42979-026-05194-zopenalex-snapshot

Novel Quantum-Classical Hybrid Circuits for Adaptive Hardware-Based Machine Learning

inferred← citeshttps://doi.org/10.1038/s41598-026-44851-4openalex-snapshot

A scalable hybrid computational intelligence framework with bio inspired optimization for high dimensional malicious URL inference

inferred← citeshttps://doi.org/10.1093/comjnl/bxag020openalex-snapshot

A study on malicious URL detection based on BiGruCNN-MHA-FTW

inferred← citeshttps://doi.org/10.1109/cins67018.2025.11412140openalex-snapshot

QML-IDS: Quantum Machine Learning Approaches for Intrusion Detection Systems in IoT devices

inferred← citeshttps://doi.org/10.1109/iccmrai67732.2026.11723509openalex-snapshot

Data-Driven Quantum-Inspired Deep Learning Model for Cyber Threat Identification in Imbalanced Security Datasets

inferred← citeshttps://doi.org/10.1109/iccvbic71195.2026.11689364openalex-snapshot

Hybrid Quantum Classical Deep Learning Model for Encrypted HTTPS Traffic Classification

inferred← citeshttps://doi.org/10.1109/icetci71772.2026.11710737openalex-snapshot

Q-MIRNET: A Quantum-Classical Hybrid Deep Learning Framework for High-Fidelity Medical Image Reconstruction

inferred← citeshttps://doi.org/10.1109/icngcs64900.2025.11182700openalex-snapshot

Quantum Machine Learning-Based Anomaly Detection for Cybersecurity Systems

inferred← citeshttps://doi.org/10.1109/iconscept66142.2025.11436605openalex-snapshot

Adaptive Edge Intrusion Prevention via Quantum Neural Networks and Digital Twin Simulation

inferred← citeshttps://doi.org/10.1109/icsccc69031.2026.11600317openalex-snapshot

Quantum Artificial Intelligence Techniques for Advanced Threat Detection and Mitigation in Cybersecurity Systems

inferred← citeshttps://doi.org/10.1109/mosicom67153.2025.11398253openalex-snapshot

Examining the Factors Influencing Generative AI's Impact on Quantum Cybersecurity: A Thematic Analysis

inferred← citeshttps://doi.org/10.1109/qpain69676.2026.11546403openalex-snapshot

Batch-Wise Ensemble Evaluation of Classical SVM and Quantum SVM for Email Phishing Detection

inferred← citeshttps://doi.org/10.3390/app16073243openalex-snapshot

Sensitivity Analysis of Variational Quantum Classifiers for Identifying Dummy Power Traces in Side-Channel Analysis

inferred← citeshttps://doi.org/10.3390/computers14080331openalex-snapshot

Parameterised Quantum SVM with Data-Driven Entanglement for Zero-Day Exploit Detection

inferred← citeshttps://doi.org/10.3390/jsan15040067openalex-snapshot

Evaluation of Variational Quantum Classifiers (VQC) for Cyberattack Detection in the NISQ Era

inferred← citeshttps://doi.org/10.3390/make8040086openalex-snapshot

Quantum Machine Learning for Phishing Detection: A Systematic Review of Current Techniques, Challenges, and Future Directions

inferred← citeshttps://doi.org/10.4018/979-8-3373-3551-3.ch007openalex-snapshot

Quantum-Enhanced Machine Learning for Next-Gen Cyber Defense

inferred← citeshttps://doi.org/10.4018/979-8-3373-7488-8.ch011openalex-snapshot

Quantum-Enhanced Security for Smart Cities

inferred← citeshttps://doi.org/10.4018/979-8-3373-9549-4.ch016openalex-snapshot

AI-Driven Intelligence Firewalls

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.