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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 ensemble framework of anomaly detection using hybridized feature selection approach (HFSA)
Nutan Farah Haq, Abdur Rahman Onik, Faisal Muhammad Shah
(2015), pp. 989-995
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Machine Learning for Anomaly Detection: A Systematic Review
Ali Bou Nassif, Manar Abu Talib, Qassim Nasir, et al.
IEEE Access (2021) Vol. 9, pp. 78658-78700
Open Access | Times Cited: 350
A survey of intrusion detection systems based on ensemble and hybrid classifiers
Abdulla Amin Aburomman, Mamun Bin Ibne Reaz
Computers & Security (2016) Vol. 65, pp. 135-152
Closed Access | Times Cited: 219
A novel ensemble learning-based model for network intrusion detection
Ngamba Thockchom, Moirangthem Marjit Singh, Utpal Nandi
Complex & Intelligent Systems (2023) Vol. 9, Iss. 5, pp. 5693-5714
Open Access | Times Cited: 46
Improving performance of intrusion detection system using ensemble methods and feature selection
Ngoc Tu Pham, Ernest Foo, Suriadi Suriadi, et al.
Proceedings of the Australasian Computer Science Week Multiconference (2018), pp. 1-6
Closed Access | Times Cited: 143
Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques
Md. Mamunur Rashid, Joarder Kamruzzaman, Mohammad Mehedi Hassan, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 24, pp. 9347-9347
Open Access | Times Cited: 124
Employee Turnover Prediction with Machine Learning: A Reliable Approach
Yue Zhao, Maciej K. Hryniewicki, Francesca Cheng, et al.
Advances in intelligent systems and computing (2018), pp. 737-758
Closed Access | Times Cited: 122
Data Mining Techniques in Intrusion Detection Systems: A Systematic Literature Review
Fadi Salo, MohammadNoor Injadat, Ali Bou Nassif, et al.
IEEE Access (2018) Vol. 6, pp. 56046-56058
Open Access | Times Cited: 119
DDoS Intrusion Detection Through Machine Learning Ensemble
Saikat Das, Ahmed M. Mahfouz, Deepak Venugopal, et al.
(2019), pp. 471-477
Closed Access | Times Cited: 79
A Comprehensive Survey on the Process, Methods, Evaluation, and Challenges of Feature Selection
Md. Rashedul Islam, Aklima Akter Lima, Sujoy Chandra Das, et al.
IEEE Access (2022) Vol. 10, pp. 99595-99632
Open Access | Times Cited: 38
Intrusion Detection System using Machine Learning Techniques: A Review
Usman Shuaibu Musa, Megha Chhabra, Aniso Ali, et al.
2020 International Conference on Smart Electronics and Communication (ICOSEC) (2020), pp. 149-155
Closed Access | Times Cited: 60
Detection of Low-Frequency and Multi-Stage Attacks in Industrial Internet of Things
Xinghua Li, Mengfan Xu, Pandi Vijayakumar, et al.
IEEE Transactions on Vehicular Technology (2020) Vol. 69, Iss. 8, pp. 8820-8831
Closed Access | Times Cited: 58
MLEsIDSs: machine learning-based ensembles for intrusion detection systems—a review
Gulshan Kumar, Kutub Thakur, Maruthi Rohit Ayyagari
The Journal of Supercomputing (2020) Vol. 76, Iss. 11, pp. 8938-8971
Closed Access | Times Cited: 56
Detection of Anomaly using Machine Learning: A Comprehensive Survey
Deepak Mane, Sunil Sangve, Gopal D. Upadhye, et al.
International Journal of Emerging Technology and Advanced Engineering (2022) Vol. 12, Iss. 11, pp. 134-152
Open Access | Times Cited: 36
A Review on Feature Selection and Ensemble Techniques for Intrusion Detection System
Majid Torabi, Nur Izura Udzir, Mohd Taufik Abdullah, et al.
International Journal of Advanced Computer Science and Applications (2021) Vol. 12, Iss. 5
Open Access | Times Cited: 32
Network Intrusion Detection with Two-Phased Hybrid Ensemble Learning and Automatic Feature Selection
Asanka Kavinda Mananayaka, Sun Sunnie Chung
IEEE Access (2023) Vol. 11, pp. 45154-45167
Open Access | Times Cited: 15
A Network Intrusion Detection Framework based on Bayesian Network using Wrapper Approach
Md Reazul, Abdur Rahman, Tanvir Samad
International Journal of Computer Applications (2017) Vol. 166, Iss. 4, pp. 13-17
Open Access | Times Cited: 40
Network anomaly detection via similarity-aware ensemble learning with ADSim
Wenqi Chen, Zhiliang Wang, Liyuan Chang, et al.
Computer Networks (2024) Vol. 247, pp. 110423-110423
Closed Access | Times Cited: 3
Survey of learning methods in intrusion detection systems
Abdulla Amin Aburomman, Mamun Bin Ibne Reaz
(2016), pp. 362-365
Closed Access | Times Cited: 33
Sustainable Ensemble Learning Driving Intrusion Detection Model
Xinghua Li, Mengyao Zhu, Laurence T. Yang, et al.
IEEE Transactions on Dependable and Secure Computing (2021), pp. 1-1
Closed Access | Times Cited: 25
Evaluating the impact of filter-based feature selection in intrusion detection systems
Houssam Zouhri, Ali Idri, Ahmed Ratnani
International Journal of Information Security (2023) Vol. 23, Iss. 2, pp. 759-785
Closed Access | Times Cited: 9
Feature selection based intrusion detection system using the combination of DBSCAN, K-Mean++ and SMO algorithms
Vandana Shakya, Rajni Ranjan Singh Makwana
2017 International Conference on Trends in Electronics and Informatics (ICEI) (2017), pp. 928-932
Closed Access | Times Cited: 28
Building an Ensemble Learning Based Algorithm for Improving Intrusion Detection System
M.S. Abirami, Umaretiya Yash, Sonal Singh
Advances in intelligent systems and computing (2020), pp. 635-649
Closed Access | Times Cited: 15
A Powerful Ensemble Learning Approach for Improving Network Intrusion Detection System (NIDS)
Sabrine Ennaji, Nabil El Akkad, Khalid Haddouch
(2021), pp. 1-6
Closed Access | Times Cited: 13
A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks
Thiago José Lucas, Inaê Soares de Figueiredo, Carlos Alexandre Carvalho Tojeiro, et al.
IEEE Access (2023) Vol. 11, pp. 122638-122676
Open Access | Times Cited: 4
Ensemble Learning Approach for Flow-based Intrusion Detection System
Skhumbuzo Zwane, Paul Tarwireyi, Matthew O. Adigun
(2019), pp. 1-8
Closed Access | Times Cited: 11
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