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2020 – today
- 2023
[j9]Hemant Rathore, Adarsh Nandanwar, Sanjay K. Sahay, Mohit Sewak:
Adversarial superiority in android malware detection: Lessons from reinforcement learning based evasion attacks and defenses. Forensic Sci. Int. Digit. Investig. 44(Supplement): 301511 (2023)- [j8]Hemant Rathore, Adithya Samavedhi, Sanjay K. Sahay, Mohit Sewak:
Towards Adversarially Superior Malware Detection Models: An Adversary Aware Proactive Approach using Adversarial Attacks and Defenses. Inf. Syst. Frontiers 25(2): 567-587 (2023) - [j7]Mohit Sewak
, Sanjay K. Sahay, Hemant Rathore:
Deep Reinforcement Learning in the Advanced Cybersecurity Threat Detection and Protection. Inf. Syst. Frontiers 25(2): 589-611 (2023) - [c29]Mohit Sewak, Vamsi Emani, Annam Naresh:
CRUSH: Cybersecurity Research using Universal LLMs and Semantic Hypernetworks. EKG-LLM@CIKM 2023 - [c28]Dong-Ho Lee, Jay Pujara, Mohit Sewak, Ryen White, Sujay Kumar Jauhar:
Making Large Language Models Better Data Creators. EMNLP 2023: 15349-15360 - [c27]Adarsh Nandanwar, Hemant Rathore, Sanjay K. Sahay, Mohit Sewak:
RL-MAGE: Strengthening Malware Detectors Against Smart Adversaries. ICCS (2) 2023: 77-92 - [i16]Dong-Ho Lee, Jay Pujara, Mohit Sewak, Ryen W. White, Sujay Kumar Jauhar:
Making Large Language Models Better Data Creators. CoRR abs/2310.20111 (2023) - 2022
- [j6]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Neural AutoForensics: Comparing Neural Sample Search and Neural Architecture Search for malware detection and forensics. Digit. Investig. 43(Supplement): 301444 (2022) - [j5]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
GreenForensics: Deep hybrid edge-cloud detection and forensics system for battery-performance-balance conscious devices. Digit. Investig. 43(Supplement): 301445 (2022) - [j4]Hemant Rathore, Animesh Sasan, Sanjay K. Sahay, Mohit Sewak:
Defending malware detection models against evasion based adversarial attacks. Pattern Recognit. Lett. 164: 119-125 (2022) - [j3]Hemant Rathore, Sujay C. Sharma, Sanjay K. Sahay, Mohit Sewak:
Are Malware Detection Classifiers Adversarially Vulnerable to Actor-Critic based Evasion Attacks? EAI Endorsed Trans. Scalable Inf. Syst. 10(1): e6 (2022) - [c26]Hemant Rathore, Mohit Sewak:
Malware Analysis and Detection. AIMLSystems 2022: 25:1-25:2 - [c25]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Deep CounterStrike: Counter Adversarial Deep Reinforcement Learning for Defense Against Metamorphic Ransomware Swarm Attack. BROADNETS 2022: 31-50 - [c24]Hemant Rathore, Soham Chari, Nishant Verma, Sanjay K. Sahay, Mohit Sewak:
Android Malware Detection Based on Static Analysis and Data Mining Techniques: A Systematic Literature Review. BROADNETS 2022: 51-71 - [c23]Hemant Rathore, Ajay Kharat, Rashmi T, Adithya Manickavasakam, Sanjay K. Sahay, Mohit Sewak:
MalEfficient10%: A Novel Feature Reduction Approach for Android Malware Detection. BROADNETS 2022: 72-92 - [c22]Hemant Rathore, Adithya Samavedhi, Sanjay K. Sahay, Mohit Sewak:
Are Malware Detection Models Adversarial Robust Against Evasion Attack? INFOCOM Workshops 2022: 1-2 - [c21]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
X-Swarm: Adversarial DRL for Metamorphic Malware Swarm Generation. PerCom Workshops 2022: 169-174 - [i15]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review. CoRR abs/2206.02733 (2022) - 2021
- [j2]Hemant Rathore, Adithya Samavedhi, Sanjay K. Sahay, Mohit Sewak:
Robust Malware Detection Models: Learning from Adversarial Attacks and Defenses. Digit. Investig. 37 Supplement: 301183 (2021) - [j1]Hemant Rathore, Sanjay K. Sahay, Piyush Nikam, Mohit Sewak:
Robust Android Malware Detection System Against Adversarial Attacks Using Q-Learning. Inf. Syst. Frontiers 23(4): 867-882 (2021) - [c20]Hemant Rathore, Sanjay K. Sahay, Jasleen Dhillon, Mohit Sewak:
Designing Adversarial Attack and Defence for Robust Android Malware Detection Models. DSN (Supplements) 2021: 29-32 - [c19]Hemant Rathore, Piyush Nikam, Sanjay K. Sahay, Mohit Sewak:
Identification of Adversarial Android Intents using Reinforcement Learning. IJCNN 2021: 1-8 - [c18]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach. IJCNN 2021: 1-9 - [c17]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
ADVERSARIALuscator: An Adversarial-DRL based Obfuscator and Metamorphic Malware Swarm Generator. IJCNN 2021: 1-9 - [c16]Hemant Rathore, Sanjay K. Sahay, Mohit Sewak:
Are Android Malware Detection Models Adversarially Robust?: Poster Abstract. IPSN 2021: 408-409 - [c15]Hemant Rathore, B. Raja Narasimhan, Sanjay K. Sahay, Mohit Sewak:
Image-based Android Malware Detection Models using Static and Dynamic Features. ISDA 2021: 1292-1305 - [c14]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DRo: A data-scarce mechanism to revolutionize the performance of DL-based Security Systems. LCN 2021: 581-588 - [c13]Hemant Rathore, Taeeb Bandwala, Sanjay K. Sahay, Mohit Sewak:
Are CNN based Malware Detection Models Robust?: Developing Superior Models using Adversarial Attack and Defense. SenSys 2021: 355-356 - [c12]Hemant Rathore, Taeeb Bandwala, Sanjay K. Sahay, Mohit Sewak:
Adversarial Robustness of Image Based Android Malware Detection Models. SKM 2021: 3-22 - [c11]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review. SKM 2021: 51-72 - [i14]Hemant Rathore, Sanjay K. Sahay, Piyush Nikam, Mohit Sewak:
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning. CoRR abs/2101.12031 (2021) - [i13]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware. CoRR abs/2102.00898 (2021) - [i12]Hemant Rathore, Sanjay K. Sahay, Shivin Thukral, Mohit Sewak:
Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering. CoRR abs/2103.00637 (2021) - [i11]Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi, Mohit Sewak:
Identification of Significant Permissions for Efficient Android Malware Detection. CoRR abs/2103.00643 (2021) - [i10]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DRo: A data-scarce mechanism to revolutionize the performance of Deep Learning based Security Systems. CoRR abs/2109.05470 (2021) - [i9]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach. CoRR abs/2109.11500 (2021) - [i8]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
ADVERSARIALuscator: An Adversarial-DRL Based Obfuscator and Metamorphic Malware SwarmGenerator. CoRR abs/2109.11542 (2021) - 2020
- [c10]Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi, Mohit Sewak:
Identification of Significant Permissions for Efficient Android Malware Detection. BROADNETS 2020: 33-52 - [c9]Hemant Rathore, Sanjay K. Sahay, Shivin Thukral, Mohit Sewak:
Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering. BROADNETS 2020: 109-128 - [c8]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DOOM: a novel adversarial-DRL-based op-code level metamorphic malware obfuscator for the enhancement of IDS. UbiComp/ISWC Adjunct 2020: 131-134 - [c7]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture. PIMRC 2020: 1-6 - [c6]Hemant Rathore, Sanjay K. Sahay, Mohit Sewak:
How robust are malware detection models for Android smartphones against adversarial attacks?: poster abstract. SenSys 2020: 683-684 - [c5]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS. TENCON 2020: 414-419 - [i7]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture. CoRR abs/2010.08607 (2020) - [i6]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
DOOM: A Novel Adversarial-DRL-Based Op-Code Level Metamorphic Malware Obfuscator for the Enhancement of IDS. CoRR abs/2010.08608 (2020) - [i5]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS. CoRR abs/2012.14427 (2020)
2010 – 2019
- 2019
- [b1]Mohit Sewak:
Deep Reinforcement Learning - Frontiers of Artificial Intelligence. Springer 2019, ISBN 978-981-13-8284-0, pp. 1-203 - [i4]Hemant Rathore, Swati Agarwal, Sanjay K. Sahay, Mohit Sewak:
Malware Detection using Machine Learning and Deep Learning. CoRR abs/1904.02441 (2019) - [i3]Hemant Rathore, Sanjay K. Sahay, Palash Chaturvedi, Mohit Sewak:
Android Malicious Application Classification Using Clustering. CoRR abs/1904.10142 (2019) - 2018
- [c4]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
An investigation of a deep learning based malware detection system. ARES 2018: 26:1-26:5 - [c3]Hemant Rathore, Swati Agarwal, Sanjay K. Sahay, Mohit Sewak:
Malware Detection Using Machine Learning and Deep Learning. BDA 2018: 402-411 - [c2]Hemant Rathore, Sanjay K. Sahay, Palash Chaturvedi, Mohit Sewak:
Android Malicious Application Classification Using Clustering. ISDA (2) 2018: 659-667 - [c1]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection. SNPD 2018: 293-296 - [i2]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
An investigation of a deep learning based malware detection system. CoRR abs/1809.05888 (2018) - [i1]Mohit Sewak, Sanjay K. Sahay, Hemant Rathore:
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection. CoRR abs/1809.05889 (2018)
Coauthor Index
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