124 citations · 423 across the 12 of their papers we have counts for
7 papers · 1 filter
ADVERSARIALuscator: An Adversarial-DRL Based Obfuscator and Metamorphic Malware SwarmGenerator
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Advanced metamorphic malware and ransomware, by using obfuscation, could alter their internal structure with every attack. If such malware could intrude even into any of the IoT ne…
LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Long-Short-Term-Memory (LSTM) networks have shown great promise in artificial intelligence (AI) based language modeling. Recently, LSTM networks have also become popular for design…
DRo: A data-scarce mechanism to revolutionize the performance of Deep Learning based Security Systems
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Supervised Deep Learning requires plenty of labeled data to converge, and hence perform optimally for task-specific learning. Therefore, we propose a novel mechanism named DRo (for…
Identification of Significant Permissions for Efficient Android Malware Detection
Hemant Rathore, Sanjay K. Sahay, Ritvik Rajvanshi +1
Since Google unveiled Android OS for smartphones, malware are thriving with 3Vs, i.e. volume, velocity, and variety. A recent report indicates that one out of every five business/i…
Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering
Hemant Rathore, Sanjay K. Sahay, Shivin Thukral +1
Today anti-malware community is facing challenges due to the ever-increasing sophistication and volume of malware attacks developed by adversaries. Traditional malware detection me…
DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
In this paper, we propose a novel mechanism to normalize metamorphic and obfuscated malware down at the opcode level and hence create an advanced metamorphic malware de-obfuscation…
Robust Android Malware Detection System against Adversarial Attacks using Q-Learning
Hemant Rathore, Sanjay K. Sahay, Piyush Nikam +1
The current state-of-the-art Android malware detection systems are based on machine learning and deep learning models. Despite having superior performance, these models are suscept…