| A survey of deep learning and its applications: a new paradigm to machine learning S Dargan, M Kumar, MR Ayyagari, G Kumar Archives of Computational Methods in Engineering 27 (4), 1071-1092, 2020 | 920 | 2020 |
| Applications of Generative Adversarial Networks (GANs): An Updated Review H Alqahtani, M Kavakli-Thorne, G Kumar Archives of Computational Methods in Engineering, 1-28, 2019 | 264 | 2019 |
| The use of artificial intelligence based techniques for intrusion detection: a review G Kumar, K Kumar, M Sachdeva Artificial Intelligence Review 34 (4), 369-387, 2010 | 207 | 2010 |
| Evaluation Metrics for Intrusion Detection Systems-A Study G Kumar International Journal of Computer Science and Mobile Applications, II 11, 2014 | 117 | 2014 |
| Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges G Kocher, G Kumar Soft Computing 25 (15), 9731–9763, 2021 | 87 | 2021 |
| Cybercrimes: A Proposed Taxonomy and Challenges HB Singh, G Kumar Journal of Computer Networks and Communications 2018 (2018), 1-11, 2018 | 78* | 2018 |
| Survey on Data Mining Techniques in Intrusion Detection A Chauhan, G Mishra, G Kumar International journal of Scientific & Engineering Research 2 (7), 2011 | 70 | 2011 |
| MLEsIDSs: machine learning-based ensembles for intrusion detection systems—a review G Kumar, K Thakur, MR Ayyagari The Journal of Supercomputing 76, 8938–8971, 2020 | 61 | 2020 |
| A hybrid deep learning based intrusion detection system using spatial-temporal representation of in-vehicle network traffic W Lo, H Alqahtani, K Thakur, A Almadhor, S Chander, G Kumar Vehicular Communications 35, 100471, 2022 | 57 | 2022 |
| The use of artificial-intelligence-based ensembles for intrusion detection: a review G Kumar, K Kumar Applied Computational Intelligence and Soft Computing 2012, 21, 2012 | 53 | 2012 |
| Design of an evolutionary approach for intrusion detection G Kumar, K Kumar The Scientific World Journal 2013 (Article ID 962185, http://dx.doi.org/10 …, 2013 | 50 | 2013 |
| An improved ensemble approach for effective intrusion detection G Kumar The Journal of Supercomputing 76 (1), 275–291, 2020 | 40 | 2020 |
| Network security–an updated perspective G Kumar, K Kumar Systems Science & Control Engineering: An Open Access Journal 2 (1), 325-334, 2014 | 39 | 2014 |
| Denial of service attacks–an updated perspective G Kumar Systems Science & Control Engineering 4 (1), 285-294, 2016 | 33 | 2016 |
| Analysis of Machine Learning Algorithms with Feature Selection for Intrusion Detection Using UNSW-NB15 Dataset G Kocher, G Kumar Available at SSRN 3784406, 2021 | 29 | 2021 |
| Feature Selection Approach for Intrusion Detection System K Kumar, G Kumar, Y Kumar 2nd International Conference on Computing, Engineering and Information …, 2013 | 28 | 2013 |
| An information theoretic approach for feature selection G Kumar, K Kumar Security and Communication Networks 5 (2), 178-185, 2012 | 28 | 2012 |
| The Use of Multi-Objective Genetic Algorithm Based Approach to Create Ensemble of ANN for Intrusion Detection G Kumar, K Kumar International Journal of Intelligence Science 2 (24), 115-127, 2012 | 22 | 2012 |
| AI based supervised classifiers: an analysis for intrusion detection G Kumar, K Kumar Proceedings of the International Conference on Advances in Computing and …, 2011 | 22 | 2011 |
| Machine learning for enhancing transportation security: A comprehensive analysis of electric and flying vehicle systems H Alqahtani, G Kumar Engineering Applications of Artificial Intelligence 129 (107667), 2024 | 21 | 2024 |
HAMED ALQAHTANIAssistant Professor @ King Khalid UniversityVerified email at kku.edu.sa
