Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 novel deep learning-based intrusion detection system for IoT DDoS security
Selman Hızal, Ünal Çavuşoğlu, Devrim Akgün
Internet of Things (2024) Vol. 28, pp. 101336-101336
Closed Access | Times Cited: 10

Showing 10 citing articles:

Optimized detection of cyber-attacks on IoT networks via hybrid deep learning models
Ahmed Bensaoud, Jugal Kalita
Ad Hoc Networks (2025) Vol. 170, pp. 103770-103770
Open Access | Times Cited: 1
nNFST: A single-model approach for multiclass novelty detection in network intrusion detection systems
Xuan-Ha Nguyen, Kim-Hung Le
Journal of Network and Computer Applications (2025) Vol. 236, pp. 104128-104128
Closed Access
A Heterogeneity-Aware Semi-Decentralized Model for a Lightweight Intrusion Detection System for IoT Networks Based on Federated Learning and BiLSTM
Shuroog Alsaleh, Mohamed El Bachir Menaï, Saad Al-Ahmadi
Sensors (2025) Vol. 25, Iss. 4, pp. 1039-1039
Open Access
Hybrid Neural Network-Based Intrusion Detection System: Leveraging LightGBM and MobileNetV2 for IoT Security
Yeh-Fen Yang, Ko-Chin Chang, Jia-Ning Luo
Symmetry (2025) Vol. 17, Iss. 3, pp. 314-314
Open Access
Securing IoT Networks Against DDoS Attacks: A Hybrid Deep Learning Approach
Noor Ul Ain, Muhammad Sardaraz, Muhammad Tahir, et al.
Sensors (2025) Vol. 25, Iss. 5, pp. 1346-1346
Open Access
Deep Learning-Based Intrusion Detection for IoT Networks: A Scalable and Efficient Approach
Md. Alamgir Hossain
Research Square (Research Square) (2025)
Closed Access
The role of machine and deep learning in modern intrusion detection systems: A comprehensive review
Uday Chandra Akuthota, Lava Bhargava
Computers & Electrical Engineering (2025) Vol. 124, pp. 110318-110318
Closed Access
Hybrid Deep Learning Model-Based Intrusion Detection System to Improve Artificial Internet of Things Against Cyber Attacks
Shayma Wail Nourildean, Wafa Mefteh, Ali Frihida
Lecture notes on data engineering and communications technologies (2025), pp. 270-280
Closed Access
ARLHNIDS-IoT: An Accurate and Robust Lightweight Hybrid-NIDS for IoT Network Security
Arpita Srivastava, Ditipriya Sinha
Computers & Security (2025), pp. 104515-104515
Closed Access
Analysis of deep learning-based intrusion detection systems in IoT environments
Abdeslem Blali, Souhayla Dargaoui, Mourade Azrour, et al.
EDPACS (2025), pp. 1-35
Closed Access
Research on Optimization of Network Attack Detection Model Based on Imbalanced Data
思瑶 杨
Computer Science and Application (2024) Vol. 14, Iss. 11, pp. 1-10
Closed Access
Optimizing Intrusion Detection for DoS, DDoS, and Mirai Attacks Subtypes Using Hierarchical Feature Selection and CatBoost on the CICIoT2023 Dataset
Abdulkader Hajjouz, Elena Аvksentieva
Data & Metadata (2024) Vol. 3, pp. 577-577
Closed Access
Page 1

Scroll to top