| Malware detection using machine learning and deep learning H Rathore, S Agarwal, SK Sahay, M Sewak 6th International Conference on Big Data Analytics (BDA 2018), 402-411, 2018 | 166 | 2018 |
| Comparison of deep learning and the classical machine learning algorithm for the malware detection M Sewak, SK Sahay, H Rathore 19th IEEE/ACIS International Conference on Software Engineering, Artificial …, 2018 | 118 | 2018 |
| 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 | 98 | 2020 |
| 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 | 73 | 2021 |
| Evolution of malware and its detection techniques SK Sahay, A Sharma, H Rathore Information and Communication Technology for Sustainable Development …, 2020 | 62 | 2020 |
| An investigation of a deep learning based malware detection system M Sewak, SK Sahay, H Rathore 13th International Conference on Availability, Reliability and Security …, 2018 | 62 | 2018 |
| 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 | 40 | 2023 |
| Identification of significant permissions for efficient android malware detection H Rathore, SK Sahay, R Rajvanshi, M Sewak 11th International Conference on Broadband Communications, Networks, and …, 2021 | 31 | 2021 |
| 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 | 27 | 2021 |
| 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 | 23 | 2020 |
| 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 | 22 | 2021 |
| Doom: a novel adversarial-drl-based op-code level metamorphic malware obfuscator for the enhancement of ids M Sewak, SK Sahay, H Rathore Adjunct proceedings of the 2020 ACM international joint conference on …, 2020 | 21 | 2020 |
| 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 | 21 | 2020 |
| DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware M Sewak, SK Sahay, H Rathore Defence Science Journal 71 (1), 55--65, 2021 | 19 | 2021 |
| Android malicious application classification using clustering H Rathore, SK Sahay, P Chaturvedi, M Sewak Intelligent Systems Design and Applications: 18th International Conference …, 2020 | 18 | 2020 |
| Value-approximation based deep reinforcement learning techniques: an overview M Sewak, SK Sahay, H Rathore 2020 IEEE 5th international conference on computing communication and …, 2020 | 12 | 2020 |
| Adversarialuscator: An adversarial-drl based obfuscator and metamorphic malware swarm generator M Sewak, SK Sahay, H Rathore 2021 International Joint Conference on Neural Networks (IJCNN), 1-9, 2021 | 11 | 2021 |
| Adversarial superiority in android malware detection: Lessons from reinforcement learning based evasion attacks and defenses H Rathore, A Nandanwar, SK Sahay, M Sewak Forensic Science International: Digital Investigation 44, 301511, 2023 | 9 | 2023 |
| Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS M Sewak, SK Sahay, H Rathore 2020 IEEE REGION 10 CONFERENCE (TENCON), 414-419, 2020 | 9 | 2020 |
| Identification of Adversarial Android Intents using Reinforcement Learning H Rathore, P Nikam, SK Sahay, M Sewak 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 7 | 2021 |
