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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:

Evaluating neural networks using Bi-Directional LSTM for network IDS (intrusion detection systems) in cyber security
Pooja TS, Purohit Shrinivasacharya
Global Transitions Proceedings (2021) Vol. 2, Iss. 2, pp. 448-454
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Design and Development of RNN Anomaly Detection Model for IoT Networks
Imtiaz Ullah, Qusay H. Mahmoud
IEEE Access (2022) Vol. 10, pp. 62722-62750
Open Access | Times Cited: 134
An optimized ensemble prediction model using AutoML based on soft voting classifier for network intrusion detection
Murad Khan, Naeem Iqbal, Imran Imran, et al.
Journal of Network and Computer Applications (2022) Vol. 212, pp. 103560-103560
Closed Access | Times Cited: 69
Analysis of Intrusion Detection Systems in UNSW-NB15 and NSL-KDD Datasets with Machine Learning Algorithms
F. J. Turk
Bitlis Eren Üniversitesi Fen Bilimleri Dergisi (2023) Vol. 12, Iss. 2, pp. 465-477
Open Access | Times Cited: 24
Fusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System
Ankit Thakkar, Nandish Kikani, Rebakah Geddam
Applied Soft Computing (2024) Vol. 154, pp. 111378-111378
Closed Access | Times Cited: 15
Deep learning-based network anomaly detection and classification in an imbalanced cloud environment
Amol D. Vibhute, Vikram Nakum
Procedia Computer Science (2024) Vol. 232, pp. 1636-1645
Open Access | Times Cited: 8
A novel methodology for malicious traffic detection in smart devices using BI-LSTM–CNN-dependent deep learning methodology
T. Anitha, S. Aanjankumar, S. Poonkuntran, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 27, pp. 20319-20338
Closed Access | Times Cited: 18
Enhancing network intrusion detection: a dual-ensemble approach with CTGAN-balanced data and weak classifiers
Mohammad Reza Abbaszadeh Bavil Soflaei, Arash Salehpour, Karim Samadzamini
The Journal of Supercomputing (2024) Vol. 80, Iss. 11, pp. 16301-16333
Closed Access | Times Cited: 7
An LSTM‐based novel near‐real‐time multiclass network intrusion detection system for complex cloud environments
Amol D. Vibhute, Minhaj Khan, Anuradha Kanade, et al.
Concurrency and Computation Practice and Experience (2024) Vol. 36, Iss. 11
Closed Access | Times Cited: 5
Long short-term memory-based intrusion detection system using hybrid grid search and sequential chimp optimization algorithm-based hyperparameter tuning
Najah Kalifah Almazmomi
Intelligent Decision Technologies (2025)
Closed Access
Malicious Behavior Identification using Dual Attention based Dense Bi-Directional Gated Recurrent Network in the Cloud Computing Environment
Nandita Goyal, Kanika Taneja, Shivani Agarwal, et al.
Computers & Security (2025), pp. 104418-104418
Closed Access
Network security based combined CNN-RNN models for IoT intrusion detection system
Rahma Jablaoui, Noureddine Liouane
Peer-to-Peer Networking and Applications (2025) Vol. 18, Iss. 3
Closed Access
Explainable AI supported hybrid deep learnig method for layer 2 intrusion detection
Ilhan Firat Kilinçer
Egyptian Informatics Journal (2025) Vol. 30, pp. 100669-100669
Closed Access
Efficacy of CNN-Bidirectional LSTM Hybrid Model for Network-Based Anomaly Detection
Toya Acharya, A. Annamalai, Mohamed Chouikha
(2023)
Closed Access | Times Cited: 9
Efficacy of Bidirectional LSTM Model for Network-Based Anomaly Detection
Toya Acharya, A. Annamalai, Mohamed Chouikha
(2023)
Closed Access | Times Cited: 9
A novel data-driven integrated detection method for network intrusion classification based on multi-feature imbalanced data
Chia‐Hung Wang, Qing Ye, J. Cai, et al.
Journal of Intelligent & Fuzzy Systems (2024) Vol. 46, Iss. 3, pp. 5893-5910
Closed Access | Times Cited: 3
Explainable and Data-Efficient Deep Learning for Enhanced Attack Detection in IIoT Ecosystem
Danish Attique, Hao Wang, Ping Wang, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 24, pp. 38976-38986
Closed Access | Times Cited: 3
Benchmarking Deep Learning Methods for Behaviour-Based Network Intrusion Detection
Mário Antunes, Luís Oliveira, Afonso Seguro, et al.
Informatics (2022) Vol. 9, Iss. 1, pp. 29-29
Open Access | Times Cited: 15
Optimized intrusion detection in IoT and fog computing using ensemble learning and advanced feature selection
Mohammed Tawfik
PLoS ONE (2024) Vol. 19, Iss. 8, pp. e0304082-e0304082
Open Access | Times Cited: 2
Improving the Reliability of Network Intrusion Detection Systems Through Dataset Integration
Roberto Magán-Carrión, Daniel Urda, Ignacio Díaz-Cano, et al.
IEEE Transactions on Emerging Topics in Computing (2022) Vol. 10, Iss. 4, pp. 1717-1732
Closed Access | Times Cited: 12
Enhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
Toya Acharya, A. Annamalai, Mohamed Chouikha
Advances in Science Technology and Engineering Systems Journal (2024) Vol. 9, Iss. 1, pp. 67-78
Open Access | Times Cited: 1
A Comprehensive Security Framework for Asymmetrical IoT Network Environments to Monitor and Classify Cyberattack via Machine Learning
Ali Alqahtani, Abdulaziz A. Alsulami, Nayef Alqahtani, et al.
Symmetry (2024) Vol. 16, Iss. 9, pp. 1121-1121
Open Access | Times Cited: 1
Assessing the detection of lateral movement through unsupervised learning techniques
Christos Smiliotopoulos, Georgios Kambourakis, Constantinos Kolias, et al.
Computers & Security (2024) Vol. 149, pp. 104190-104190
Closed Access | Times Cited: 1
Solar Power Generation Forecasting in Smart Cities and Explanation Based on Explainable AI
Ovanes Petrosian, Yuyi Zhang
Smart Cities (2024) Vol. 7, Iss. 6, pp. 3388-3411
Open Access | Times Cited: 1
Intelligent parameter-based in-network IDS for IoT using UNSW-NB15 and BoT-IoT datasets
Muhammad Luqman, Muhammad Zeeshan, Qaiser Riaz, et al.
Journal of the Franklin Institute (2024), pp. 107440-107440
Closed Access | Times Cited: 1
DCNN: a novel binary and multi-class network intrusion detection model via deep convolutional neural network
Ahmed Shebl, E. I. Elsedimy, Amr Ismail, et al.
EURASIP Journal on Information Security (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 1
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