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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 Comparative Study of Deep Learning-Based Vulnerability Detection System
Zhen Li, Deqing Zou, Jing Tang, et al.
IEEE Access (2019) Vol. 7, pp. 103184-103197
Open Access | Times Cited: 84

Showing 1-25 of 84 citing articles:

Deep Learning Based Vulnerability Detection: Are We There Yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding, et al.
IEEE Transactions on Software Engineering (2021) Vol. 48, Iss. 9, pp. 3280-3296
Open Access | Times Cited: 367
The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches
Hazim Hanif, Mohd Hairul Nizam Md Nasir, Mohd Faizal Ab Razak, et al.
Journal of Network and Computer Applications (2021) Vol. 179, pp. 103009-103009
Closed Access | Times Cited: 98
The Threat of Offensive AI to Organizations
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, et al.
Computers & Security (2022) Vol. 124, pp. 103006-103006
Open Access | Times Cited: 47
Deep Learning for Software Vulnerabilities Detection Using Code Metrics
Mohammed Zagane, Mustapha Kamel Abdi, Mamdouh Alenezi
IEEE Access (2020) Vol. 8, pp. 74562-74570
Open Access | Times Cited: 50
Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features
Canan Batur Şahin, Özlem BATUR DİNLER, Laith Abualigah
Applied Intelligence (2021) Vol. 51, Iss. 11, pp. 8271-8287
Closed Access | Times Cited: 43
DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning
Triet Huynh Minh Le, David Hin, Roland Croft, et al.
2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) (2021), pp. 717-729
Closed Access | Times Cited: 43
xFuzz: Machine Learning Guided Cross-Contract Fuzzing
Yinxing Xue, Jiaming Ye, Wei Zhang, et al.
IEEE Transactions on Dependable and Secure Computing (2022) Vol. 21, Iss. 2, pp. 515-529
Open Access | Times Cited: 36
Optimizing software vulnerability detection using RoBERTa and machine learning
Cho Do Xuan, Nguyen Trong Luu, Phuong Thi Lan Nguyen
Automated Software Engineering (2024) Vol. 31, Iss. 2
Closed Access | Times Cited: 6
The impact factors on the performance of machine learning-based vulnerability detection: A comparative study
Wei Zheng, Jialiang Gao, Xiaoxue Wu, et al.
Journal of Systems and Software (2020) Vol. 168, pp. 110659-110659
Closed Access | Times Cited: 42
Automated city shuttles: Mapping the key challenges in cybersecurity, privacy and standards to future developments
Meriem Benyahya, Anastasija Collen, Sotiria Kechagia, et al.
Computers & Security (2022) Vol. 122, pp. 102904-102904
Open Access | Times Cited: 25
A Code Centric Evaluation of C/C++ Vulnerability Datasets for Deep Learning Based Vulnerability Detection Techniques
Ridhi Jain, Nicole Gervasoni, Mthandazo Ndhlovu, et al.
(2023), pp. 1-10
Closed Access | Times Cited: 15
A novel approach for software vulnerability detection based on intelligent cognitive computing
Cho Do Xuan, Dao Hoang, Ma Cong Thanh, et al.
The Journal of Supercomputing (2023) Vol. 79, Iss. 15, pp. 17042-17078
Closed Access | Times Cited: 13
A survey on machine learning techniques applied to source code
Tushar Sharma, Maria Kechagia, Stefanos Georgiou, et al.
Journal of Systems and Software (2023) Vol. 209, pp. 111934-111934
Open Access | Times Cited: 13
Automated Software Vulnerability Detection Based on Hybrid Neural Network
Xin Li, Lu Wang, Yang Xin, et al.
Applied Sciences (2021) Vol. 11, Iss. 7, pp. 3201-3201
Open Access | Times Cited: 27
A New Framework for Software Vulnerability Detection Based on an Advanced Computing
Bùi Văn Cong, Cho Do Xuan
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 3, pp. 3699-3723
Open Access | Times Cited: 4
An Automated Cyber Intrusion Prediction Model Using Deep Learning to Resilient in Cyber Threat for the Royal Thai Air Force

Information Technology Journal (2025) Vol. 21, Iss. 1, pp. 44-56
Closed Access
Predicting Vulnerabilities in Computer Source Code Using Non-Investigated Software Metrics
Francis Kwadzo Agbenyegah, Jinfu Chen, Micheal Asante, et al.
Software Quality Journal (2025) Vol. 33, Iss. 1
Closed Access
Neural software vulnerability analysis using rich intermediate graph representations of programs
Seyed Mohammad Ghaffarian, Hamid Reza Shahriari
Information Sciences (2020) Vol. 553, pp. 189-207
Closed Access | Times Cited: 28
A deep learning‐based approach for software vulnerability detection using code metrics
Fazli Subhan, Xiaoxue Wu, Lili Bo, et al.
IET Software (2022) Vol. 16, Iss. 5, pp. 516-526
Open Access | Times Cited: 18
A survey on robustness attacks for deep code models
Yubin Qu, Song Huang, Yongming Yao
Automated Software Engineering (2024) Vol. 31, Iss. 2
Closed Access | Times Cited: 3
Exploring the Effectiveness of Web Crawlers in Detecting Security Vulnerabilities in Computer Software Applications
Biao Wan
IJIIS International Journal of Informatics and Information Systems (2023) Vol. 6, Iss. 2, pp. 56-65
Open Access | Times Cited: 8
A new approach to software vulnerability detection based on CPG analysis
Cho Do Xuan
Cogent Engineering (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 8
Automatically Detect Software Security Vulnerabilities Based on Natural Language Processing Techniques and Machine Learning Algorithms
Cho Do Xuan, Vu Ngoc Son, Duong Tuan Duc
Journal of ICT Research and Applications (2022) Vol. 16, Iss. 1, pp. 70-87
Open Access | Times Cited: 13
A Comparative Study of Neural Network Techniques for Automatic Software Vulnerability Detection
Gaigai Tang, Lianxiao Meng, Huiqiang Wang, et al.
(2020), pp. 1-8
Open Access | Times Cited: 18
The application of neural network for software vulnerability detection: a review
Yuhui Zhu, Guanjun Lin, Lipeng Song, et al.
Neural Computing and Applications (2022) Vol. 35, Iss. 2, pp. 1279-1301
Closed Access | Times Cited: 11
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