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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:

An Explainable Deep Learning Framework for Resilient Intrusion Detection in IoT-Enabled Transportation Networks
Ayodeji Oseni, Nour Moustafa, Gideon Creech, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 24, Iss. 1, pp. 1000-1014
Closed Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

Explainable Artificial Intelligence (XAI) for Intrusion Detection and Mitigation in Intelligent Connected Vehicles: A Review
Cosmas Ifeanyi Nwakanma, Love Allen Chijioke Ahakonye, Judith Nkechinyere Njoku, et al.
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1252-1252
Open Access | Times Cited: 90
Blockchain Intelligence for Internet of Vehicles: Challenges and Solutions
Xiaojie Wang, Hailin Zhu, Zhaolong Ning, et al.
IEEE Communications Surveys & Tutorials (2023) Vol. 25, Iss. 4, pp. 2325-2355
Closed Access | Times Cited: 50
A metaheuristic-based ensemble feature selection framework for cyber threat detection in IoT-enabled networks
Arun Kumar Dey, Govind P. Gupta, Satya Prakash Sahu
Decision Analytics Journal (2023) Vol. 7, pp. 100206-100206
Open Access | Times Cited: 40
Deep learning enabled intrusion detection system for Industrial IOT environment
Himanshu Nandanwar, Rahul Katarya
Expert Systems with Applications (2024) Vol. 249, pp. 123808-123808
Closed Access | Times Cited: 27
Digital Twins-enabled Zero Touch Network: A smart contract and explainable AI integrated cybersecurity framework
Randhir Kumar, Ahamed Aljuhani, Danish Javeed, et al.
Future Generation Computer Systems (2024) Vol. 156, pp. 191-205
Open Access | Times Cited: 24
Machine Learning and Deep Learning Techniques for Internet of Things Network Anomaly Detection—Current Research Trends
Saida Hafsa Rafique, Amira Mahamat Abdallah, Nura Shifa Musa, et al.
Sensors (2024) Vol. 24, Iss. 6, pp. 1968-1968
Open Access | Times Cited: 17
Advanced Learning Technologies for Intelligent Transportation Systems: Prospects and Challenges
Ruhul Amin Khalil, Ziad Safelnasr, Naod Yemane, et al.
IEEE Open Journal of Vehicular Technology (2024) Vol. 5, pp. 397-427
Open Access | Times Cited: 16
Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy
Xinyu Zhang, LI Jun-xian, Jingyi Zhou, et al.
Automotive Innovation (2025)
Open Access | Times Cited: 1
Securing a Smart Home with a Transformer-Based IoT Intrusion Detection System
Minxiao Wang, Ning Yang, Ning Weng
Electronics (2023) Vol. 12, Iss. 9, pp. 2100-2100
Open Access | Times Cited: 25
A Deep Learning Methodology for Predicting Cybersecurity Attacks on the Internet of Things
Omar Azib Alkhudaydi, Moez Krichen, Ans D. Alghamdi
Information (2023) Vol. 14, Iss. 10, pp. 550-550
Open Access | Times Cited: 23
Deep Q-network-based heuristic intrusion detection against edge-based SIoT zero-day attacks
Shigen Shen, Chenpeng Cai, Zhenwei Li, et al.
Applied Soft Computing (2023) Vol. 150, pp. 111080-111080
Closed Access | Times Cited: 23
Anomaly diagnosis of connected autonomous vehicles: A survey
Yukun Fang, Haigen Min, Xia Wu, et al.
Information Fusion (2024) Vol. 105, pp. 102223-102223
Closed Access | Times Cited: 10
A survey on IoT application layer protocols, security challenges, and the role of explainable AI in IoT (XAIoT)
Vagner E. Quincozes, Silvio E. Quincozes, Juliano F. Kazienko, et al.
International Journal of Information Security (2024) Vol. 23, Iss. 3, pp. 1975-2002
Open Access | Times Cited: 8
XAI-ADS: An Explainable Artificial Intelligence Framework for Enhancing Anomaly Detection in Autonomous Driving Systems
Sazid Nazat, Lingxi Li, Mustafa Abdallah
IEEE Access (2024) Vol. 12, pp. 48583-48607
Open Access | Times Cited: 8
Exploring Local Explanation of Practical Industrial AI Applications: A Systematic Literature Review
Thi-Thu-Huong Le, Aji Teguh Prihatno, Yustus Eko Oktian, et al.
Applied Sciences (2023) Vol. 13, Iss. 9, pp. 5809-5809
Open Access | Times Cited: 20
An Explainable Ensemble Deep Learning Approach for Intrusion Detection in Industrial Internet of Things
Mousa'B Mohammad Shtayat, Mohammad Kamrul Hasan, Rossilawati Sulaiman, et al.
IEEE Access (2023) Vol. 11, pp. 115047-115061
Open Access | Times Cited: 20
Blockchain-Based Authentication and Explainable AI for Securing Consumer IoT Applications
Randhir Kumar, Danish Javeed, Ahamed Aljuhani, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 1145-1154
Closed Access | Times Cited: 19
VANET Network Traffic Anomaly Detection Using GRU-Based Deep Learning Model
Ghayth AlMahadin, Yassine Aoudni, Mohammad Shabaz, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 4548-4555
Closed Access | Times Cited: 16
Blockchain and explainable AI for enhanced decision making in cyber threat detection
Prabhat Kumar, Danish Javeed, Randhir Kumar, et al.
Software Practice and Experience (2024) Vol. 54, Iss. 8, pp. 1337-1360
Open Access | Times Cited: 7
Robust integration of blockchain and explainable federated learning for automated credit scoring
Zorka Jovanovic, Zhé Hóu, Kamanashis Biswas, et al.
Computer Networks (2024) Vol. 243, pp. 110303-110303
Open Access | Times Cited: 6
Explainable AI in Manufacturing and Industrial Cyber–Physical Systems: A Survey
Sajad Moosavi, Maryam Farajzadeh-Zanjani, Roozbeh Razavi–Far, et al.
Electronics (2024) Vol. 13, Iss. 17, pp. 3497-3497
Open Access | Times Cited: 5
Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning
Emrullah Şahin, Naciye Nur Arslan, Durmuş Özdemir
Neural Computing and Applications (2024)
Closed Access | Times Cited: 5
IoT security using heuristic aided symmetric convolution-based deep temporal convolution network for intrusion detection by extracting multi-cascaded deep attention features
R. Latha, S. John Justin Thangaraj
Expert Systems with Applications (2025), pp. 126363-126363
Closed Access
Explainable artificial intelligence models in intrusion detection systems
Samed Al, Şeref Sağıroğlu
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110145-110145
Closed Access
Revealing the built environment impacts on truck emissions using interpretable machine learning
Tongtong Shi, Meiting Tu, Ye Li, et al.
Transportation Research Part D Transport and Environment (2025) Vol. 141, pp. 104662-104662
Closed Access
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