| Practical convolutional neural networks: implement advanced deep learning models using Python M Sewak, MR Karim, P Pujari Packt Publishing Ltd, 2018 | 220 | 2018 |
| Deep reinforcement learning M Sewak Springer Singapore, 2019 | 182 | 2019 |
| Malware Detection Using Machine Learning and Deep Learning H Rathore, S Agarwal, SK Sahay, M Sewak | 151 | 2019 |
| Comparison of deep learning and the classical machine learning algorithm for the malware detection M Sewak, SK Sahay, H Rathore 2018 19th IEEE/ACIS international conference on software engineering …, 2018 | 107 | 2018 |
| Deep q network (dqn), double dqn, and dueling dqn: A step towards general artificial intelligence M Sewak, M Sewak Deep reinforcement learning: frontiers of artificial intelligence, 95-108, 2019 | 103 | 2019 |
| An overview of deep learning architecture of deep neural networks and autoencoders M Sewak, SK Sahay, H Rathore Journal of Computational and Theoretical Nanoscience 17 (1), 182-188, 2020 | 85 | 2020 |
| Winning in the Era of Serverless Computing and Function as a Service M Sewak, S Singh 2018 3rd International Conference for Convergence in Technology (I2CT), 1-5, 2018 | 68 | 2018 |
| Robust android malware detection system against adversarial attacks using q-learning H Rathore, SK Sahay, P Nikam, M Sewak Information Systems Frontiers 23, 867-882, 2021 | 65 | 2021 |
| An investigation of a deep learning based malware detection system M Sewak, SK Sahay, H Rathore Proceedings of the 13th International Conference on Availability …, 2018 | 60 | 2018 |
| Identification of significant permissions for efficient android malware detection H Rathore, SK Sahay, R Rajvanshi, M Sewak International conference on broadband communications, networks and systems …, 2020 | 29 | 2020 |
| IoT and distributed machine learning powered optimal state recommender solution M Sewak, S Singh 2016 International Conference on Internet of Things and Applications (IOTA …, 2016 | 25 | 2016 |
| Detection of malicious android applications: Classical machine learning vs. deep neural network integrated with clustering H Rathore, SK Sahay, S Thukral, M Sewak International conference on broadband communications, networks and systems …, 2020 | 21 | 2020 |
| DOOM: A Novel Adversarial-DRL-Based Op-Code Level Metamorphic Malware Obfuscator for the Enhancement of IDS M Sewak, SK Sahay, H Rathore Proceedings of the 2020 ACM International Joint Conference on Pervasive and …, 2020 | 20 | 2020 |
| Deep reinforcement learning for cybersecurity threat detection and protection: A review M Sewak, SK Sahay, H Rathore International Conference On Secure Knowledge Management In Artificial …, 2021 | 19 | 2021 |
| Robust malware detection models: learning from adversarial attacks and defenses H Rathore, A Samavedhi, SK Sahay, M Sewak Forensic Science International: Digital Investigation 37, 301183, 2021 | 19 | 2021 |
| DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture M Sewak, SK Sahay, H Rathore 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile …, 2020 | 19 | 2020 |
| Android Malicious Application Classification Using Clustering H Rathore, SK Sahay, P Chaturvedi, M Sewak | 18 | 2019 |
| Policy-based reinforcement learning approaches: Stochastic policy gradient and the REINFORCE algorithm M Sewak, M Sewak Deep Reinforcement Learning: Frontiers of Artificial Intelligence, 127-140, 2019 | 18 | 2019 |
| Deep reinforcement learning in the advanced cybersecurity threat detection and protection M Sewak, SK Sahay, H Rathore Information Systems Frontiers 25 (2), 589-611, 2023 | 17 | 2023 |
| DRLDO: A Novel DRL based De obfuscation System for Defense Against Metamorphic Malware M Sewak, SK Sahay, H Rathore Defence Science Journal 71 (1), 55-65, 2021 | 17 | 2021 |
Sanjay K. SahayProfessor, Department of Computer Science and Information Systems, BITS, Pilani, GoaVerified email at goa.bits-pilani.ac.in
