124 citations · 605 across the 39 of their papers we have counts for
28 papers · 1 filter
Modern Hardware Security: A Review of Attacks and Countermeasures
Jyotiprakash Mishra, Sanjay K. Sahay
With the exponential rise in the use of cloud services, smart devices, and IoT devices, advanced cyber attacks have become increasingly sophisticated and ubiquitous. Furthermore, t…
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
The cybersecurity threat landscape has lately become overly complex. Threat actors leverage weaknesses in the network and endpoint security in a very coordinated manner to perpetua…
Privacy-Preserving Mutual Authentication and Key Agreement Scheme for Multi-Server Healthcare System
Trupil Limbasiya, Sanjay K. Sahay, Bharath Sridharan
The usage of different technologies and smart devices helps people to get medical services remotely for multiple benefits. Thus, critical and sensitive data is exchanged between a…
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…
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Recurrent deep learning language models like the LSTM are often used to provide advanced cyber-defense for high-value assets. The underlying assumption for using LSTM networks for…
DOOM: A Novel Adversarial-DRL-Based Op-Code Level Metamorphic Malware Obfuscator for the Enhancement of IDS
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
We designed and developed DOOM (Adversarial-DRL based Opcode level Obfuscator to generate Metamorphic malware), a novel system that uses adversarial deep reinforcement learning to…
DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
The Intent in Android plays an important role in inter-process and intra-process communications. The implicit Intent that an application could accept are declared in its manifest a…
Secure and Energy-Efficient Key-Agreement Protocol for Multi-Server Architecture
Trupil Limbasiya, Sanjay K. Sahay
Authentication schemes are practised globally to verify the legitimacy of users and servers for the exchange of data in different facilities. Generally, the server verifies a user…
Secure Communication Protocol for Smart Transportation Based on Vehicular Cloud
Trupil Limbasiya, Debasis Das, Sanjay K. Sahay
The pioneering concept of connected vehicles has transformed the way of thinking for researchers and entrepreneurs by collecting relevant data from nearby objects. However, this da…
A Survey on the Detection of Android Malicious Apps
Sanjay K. Sahay, Ashu Sharma
Android-based smart devices are exponentially growing, and due to the ubiquity of the Internet, these devices are globally connected to the different devices/networks. Its populari…
An Efficient Detection of Malware by Naive Bayes Classifier Using GPGPU
Sanjay K. Sahay, Mayank Chaudhari
Due to continuous increase in the number of malware (according to AV-Test institute total ~8 x 10^8 malware are already known, and every day they register ~2.5 x 10^4 malware) and…
Android Malicious Application Classification Using Clustering
Hemant Rathore, Sanjay K. Sahay, Palash Chaturvedi +1
Android malware have been growing at an exponential pace and becomes a serious threat to mobile users. It appears that most of the anti-malware still relies on the signature-based…
Malware Detection using Machine Learning and Deep Learning
Hemant Rathore, Swati Agarwal, Sanjay K. Sahay +1
Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies ha…
Group-wise classification approach to improve Android malicious apps detection accuracy
Ashu Sharma, Sanjay K. Sahay
In the fast-growing smart devices, Android is the most popular OS, and due to its attractive features, mobility, ease of use, these devices hold sensitive information such as perso…
Detection of Advanced Malware by Machine Learning Techniques
Sanjay Sharma, C. Rama Krishna, Sanjay K. Sahay
In today's digital world most of the anti-malware tools are signature based which is ineffective to detect advanced unknown malware viz. metamorphic malware. In this paper, we stud…
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
Recently, Deep Learning has been showing promising results in various Artificial Intelligence applications like image recognition, natural language processing, language modeling, n…
An investigation of a deep learning based malware detection system
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore
We investigate a Deep Learning based system for malware detection. In the investigation, we experiment with different combination of Deep Learning architectures including Auto-Enco…
An investigation of the classifiers to detect android malicious apps
Ashu Sharma, Sanjay K. Sahay
Android devices are growing exponentially and are connected through the internet accessing billion of online websites. The popularity of these devices encourages malware developer…