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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A real-time IoT-based botnet detection method using a novel two-step feature selection technique and the support vector machine classifier
Yosef Masoudi-Sobhanzadeh, Shabnam Emami-Moghaddam
Computer Networks (2022) Vol. 217, pp. 109365-109365
Closed Access | Times Cited: 24

Showing 24 citing articles:

A novel hybrid feature selection and ensemble-based machine learning approach for botnet detection
Md. Alamgir Hossain, Md. Saiful Islam
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 22
A novel feature selection-driven ensemble learning approach for accurate botnet attack detection
Md. Alamgir Hossain, Md. Saiful Islam
Alexandria Engineering Journal (2025) Vol. 118, pp. 261-277
Closed Access | Times Cited: 1
Ensemble Machine Learning Techniques for Accurate and Efficient Detection of Botnet Attacks in Connected Computers
Stephen Afrifa, V. Vijayakumar, Peter Appiahene, et al.
Eng—Advances in Engineering (2023) Vol. 4, Iss. 1, pp. 650-664
Open Access | Times Cited: 21
Reviewing various feature selection techniques in machine learning‐based botnet detection
Sangita Baruah, Dhruba Jyoti Borah, Vaskar Deka
Concurrency and Computation Practice and Experience (2024) Vol. 36, Iss. 12
Closed Access | Times Cited: 4
Machine learning pipelines for IoT botnet detection and behavior characterization in heavily imbalanced settings
Djordje Jovanović, Pavle Vuletić
Signal Image and Video Processing (2025) Vol. 19, Iss. 3
Closed Access
Review of filtering based feature selection for Botnet detection in the Internet of Things
Mohamed Saied, Shawkat K. Guirguis, Magda M. Madbouly
Artificial Intelligence Review (2025) Vol. 58, Iss. 4
Open Access
HoleMal: A lightweight IoT malware detection framework based on efficient host-level traffic processing
Ziqian Chen, Wei Xia, Zhen Li, et al.
Computers & Security (2025), pp. 104360-104360
Closed Access
Joint IoT/ML Platforms for Smart Societies and Environments: A Review on Multimodal Information-Based Learning for Safety and Security
Hani Attar
Journal of Data and Information Quality (2023) Vol. 15, Iss. 3, pp. 1-26
Closed Access | Times Cited: 11
Efficient traffic-based IoT device identification using a feature selection approach with Lévy flight-based sine chaotic sub-swarm binary honey badger algorithm
Boxiong Wang, Hui Kang, Geng Sun, et al.
Applied Soft Computing (2024) Vol. 155, pp. 111455-111455
Closed Access | Times Cited: 4
Modeling of Botnet Detection Using Chaotic Binary Pelican Optimization Algorithm With Deep Learning on Internet of Things Environment
Fadwa Alrowais, Majdy M. Eltahir, Sumayh S. Aljameel, et al.
IEEE Access (2023) Vol. 11, pp. 130618-130626
Open Access | Times Cited: 7
IMTIBOT: An Intelligent Mitigation Technique for IoT Botnets
Umang Garg, Santosh Kumar, Aniket Mahanti
Future Internet (2024) Vol. 16, Iss. 6, pp. 212-212
Open Access | Times Cited: 2
Feature selection for IoT botnet detection using equilibrium and Battle Royale Optimization
Qanita Bani Baker, Alaa Samarneh
Computers & Security (2024) Vol. 147, pp. 104060-104060
Closed Access | Times Cited: 2
A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach
Ahmed Bahaa, Abdalla Sayed, Laila Elfangary, et al.
PLoS ONE (2022) Vol. 17, Iss. 12, pp. e0278493-e0278493
Open Access | Times Cited: 9
Analyzing and detecting Botnet Attacks using Anomaly Detection with Machine Learning
R. Barath Ramesh, S. John Justin Thangaraj
2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA) (2023), pp. 911-915
Closed Access | Times Cited: 4
Support Vector Machine Classification using Proximity Authentication and Surveillance System in IoT Industrial Network

Tehnicki vjesnik - Technical Gazette (2024) Vol. 31, Iss. 1
Open Access | Times Cited: 1
Review for Prevention of Botnet Attack Using Various Detection Techniques in IoT and IIoT
Mohit Goyal, Sangeeta Mittal
(2024), pp. 259-264
Closed Access | Times Cited: 1
An Optimized Approach to Deep Learning for Botnet Detection and Classification for Cybersecurity in Internet of Things Environment
Abdulrahman Alzahrani
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 80, Iss. 2, pp. 2331-2349
Open Access | Times Cited: 1
IoT-Botnet Detection Using Deep Learning Techniques
Soundes Belkacem
Lecture notes in networks and systems (2024), pp. 239-249
Closed Access
A Survey of Intrusion Detection Systems Based On Deep Learning for IoT Data
Mehrnaz Moudi, Ali Soleimani, A. Nia
Journal of Information Systems and Telecommunication (JIST) (2024) Vol. 12, Iss. 47, pp. 197-207
Closed Access
Enabling IoT Service Classification: A Machine Learning-Based Approach for Handling Classification Issues in Heterogeneous IoT Services
Mohammad Asad Abbasi, Yen‐Lin Chen, Abdullah Ayub Khan, et al.
IEEE Access (2023) Vol. 11, pp. 89024-89037
Open Access | Times Cited: 1
A Review on Optimization and Feature Selection Techniques for Data Security in IoT
Jisha Jose, J. E. Judith
(2023), pp. 1290-1294
Closed Access | Times Cited: 1
Improving Botnet Detection with a Generative Adversarial Network-Based Technique
Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, et al.
2022 19th International Bhurban Conference on Applied Sciences and Technology (IBCAST) (2023), pp. 564-569
Closed Access | Times Cited: 1
Bonet Detection Mechanism Using Graph Neural Network
Aleksander Maksimoski, Isaac Woungang, Issa Traoré, et al.
Lecture notes in networks and systems (2023), pp. 247-257
Closed Access
Detection of IoT Botnet Based on Convolutional Neural Network and Linear Support Vector Machine
Changping Lai, Yinan Yao, Yuzhong Chen, et al.
(2023), pp. 222-226
Closed Access
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