| 2023 | EMNLP | Making Large Language Models Better Data Creators. | Dong-Ho Lee, Jay Pujara, Mohit Sewak, Ryen White, Sujay Kumar Jauhar |
| 2023 | ICCS | RL-MAGE: Strengthening Malware Detectors Against Smart Adversaries. | Adarsh Nandanwar, Hemant Rathore, Sanjay K. Sahay, Mohit Sewak |
| 2022 | Broadnets | Android Malware Detection Based on Static Analysis and Data Mining Techniques: A Systematic Literature Review. | Hemant Rathore, Soham Chari, Nishant Verma, Sanjay K. Sahay, Mohit Sewak |
| 2022 | Broadnets | MalEfficient10%: A Novel Feature Reduction Approach for Android Malware Detection. | Hemant Rathore, Ajay Kharat, Rashmi T, Adithya Manickavasakam, Sanjay K. Sahay, Mohit Sewak |
| 2022 | Broadnets | Deep CounterStrike: Counter Adversarial Deep Reinforcement Learning for Defense Against Metamorphic Ransomware Swarm Attack. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2022 | INFOCOM | Are Malware Detection Models Adversarial Robust Against Evasion Attack? | Hemant Rathore, Adithya Samavedhi, Sanjay K. Sahay, Mohit Sewak |
| 2022 | PERCOM | X-Swarm: Adversarial DRL for Metamorphic Malware Swarm Generation. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2021 | DSN | Designing Adversarial Attack and Defence for Robust Android Malware Detection Models. | Hemant Rathore, Sanjay K. Sahay, Jasleen Dhillon, Mohit Sewak |
| 2021 | IJCNN | Identification of Adversarial Android Intents using Reinforcement Learning. | Hemant Rathore, Piyush Nikam, Sanjay K. Sahay, Mohit Sewak |
| 2021 | IJCNN | LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2021 | IJCNN | ADVERSARIALuscator: An Adversarial-DRL based Obfuscator and Metamorphic Malware Swarm Generator. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2021 | ISDA | Image-based Android Malware Detection Models using Static and Dynamic Features. | Hemant Rathore, B. Raja Narasimhan, Sanjay K. Sahay, Mohit Sewak |
| 2021 | LCN | DRo: A data-scarce mechanism to revolutionize the performance of DL-based Security Systems. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2021 | SENSYS | Are CNN based Malware Detection Models Robust?: Developing Superior Models using Adversarial Attack and Defense. | Hemant Rathore, Taeeb Bandwala, Sanjay K. Sahay, Mohit Sewak |
| 2020 | Broadnets | Identification of Significant Permissions for Efficient Android Malware Detection. | Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi, Mohit Sewak |
| 2020 | Broadnets | Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering. | Hemant Rathore, Sanjay K. Sahay, Shivin Thukral, Mohit Sewak |
| 2020 | PIMRC | DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2020 | SENSYS | How robust are malware detection models for Android smartphones against adversarial attacks?: poster abstract. | Hemant Rathore, Sanjay K. Sahay, Mohit Sewak |
| 2020 | Tencon | Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |
| 2018 | ISDA | Android Malicious Application Classification Using Clustering. | Hemant Rathore, Sanjay K. Sahay, Palash Chaturvedi, Mohit Sewak |
| 2018 | SNPD | Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection. | Mohit Sewak, Sanjay K. Sahay, Hemant Rathore |