Sanjay K. Sahay

Affiliations:
  • Goa Campus, BITS, Pilani, India


According to our database1, Sanjay K. Sahay authored at least 73 papers between 2012 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Deep Reinforcement Learning in the Advanced Cybersecurity Threat Detection and Protection.
Inf. Syst. Frontiers, April, 2023

Towards Adversarially Superior Malware Detection Models: An Adversary Aware Proactive Approach using Adversarial Attacks and Defenses.
Inf. Syst. Frontiers, April, 2023

Adversarial superiority in android malware detection: Lessons from reinforcement learning based evasion attacks and defenses.
Forensic Sci. Int. Digit. Investig., March, 2023

An investigation of two-step cascaded CNN for the detection of gravitational wave signal from two different astronomical sources.
Proceedings of the International Neural Network Society Workshop on Deep Learning Innovations and Applications, 2023

Breaking the Anti-malware: EvoAAttack Based on Genetic Algorithm Against Android Malware Detection Systems.
Proceedings of the Computational Science - ICCS 2023, 2023

RL-MAGE: Strengthening Malware Detectors Against Smart Adversaries.
Proceedings of the Computational Science - ICCS 2023, 2023

2022
Are Malware Detection Classifiers Adversarially Vulnerable to Actor-Critic based Evasion Attacks?
EAI Endorsed Trans. Scalable Inf. Syst., 2022

Defending malware detection models against evasion based adversarial attacks.
Pattern Recognit. Lett., 2022

SAMPARK: Secure and lightweight communication protocols for smart parking management.
J. Inf. Secur. Appl., 2022

GreenForensics: Deep hybrid edge-cloud detection and forensics system for battery-performance-balance conscious devices.
Digit. Investig., 2022

Neural AutoForensics: Comparing Neural Sample Search and Neural Architecture Search for malware detection and forensics.
Digit. Investig., 2022

X-Swarm: Adversarial DRL for Metamorphic Malware Swarm Generation.
Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

Are Malware Detection Models Adversarial Robust Against Evasion Attack?
Proceedings of the IEEE INFOCOM 2022, 2022

Deep CounterStrike: Counter Adversarial Deep Reinforcement Learning for Defense Against Metamorphic Ransomware Swarm Attack.
Proceedings of the Broadband Communications, Networks, and Systems, 2022

MalEfficient10%: A Novel Feature Reduction Approach for Android Malware Detection.
Proceedings of the Broadband Communications, Networks, and Systems, 2022

Android Malware Detection Based on Static Analysis and Data Mining Techniques: A Systematic Literature Review.
Proceedings of the Broadband Communications, Networks, and Systems, 2022

2021
Advances in Secure Knowledge Management in the Artificial Intelligence Era.
Inf. Syst. Frontiers, 2021

Robust Android Malware Detection System Against Adversarial Attacks Using Q-Learning.
Inf. Syst. Frontiers, 2021

Privacy-Preserving Mutual Authentication and Key Agreement Scheme for Multi-Server Healthcare System.
Inf. Syst. Frontiers, 2021

Robust Malware Detection Models: Learning from Adversarial Attacks and Defenses.
Digit. Investig., 2021

ADVERSARIALuscator: An Adversarial-DRL Based Obfuscator and Metamorphic Malware SwarmGenerator.
CoRR, 2021

DRo: A data-scarce mechanism to revolutionize the performance of Deep Learning based Security Systems.
CoRR, 2021

DRLDO: A novel DRL based De-ObfuscationSystem for Defense against Metamorphic Malware.
CoRR, 2021

Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review.
Proceedings of the Secure Knowledge Management In The Artificial Intelligence Era, 2021

Adversarial Robustness of Image Based Android Malware Detection Models.
Proceedings of the Secure Knowledge Management In The Artificial Intelligence Era, 2021

Are CNN based Malware Detection Models Robust?: Developing Superior Models using Adversarial Attack and Defense.
Proceedings of the SenSys '21: The 19th ACM Conference on Embedded Networked Sensor Systems, Coimbra, Portugal, November 15, 2021

Towards Robust Android Malware Detection Models using Adversarial Learning.
Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2021

DRo: A data-scarce mechanism to revolutionize the performance of DL-based Security Systems.
Proceedings of the 46th IEEE Conference on Local Computer Networks, 2021

Image-based Android Malware Detection Models using Static and Dynamic Features.
Proceedings of the Intelligent Systems Design and Applications, 2021

Are Android Malware Detection Models Adversarially Robust?: Poster Abstract.
Proceedings of the IPSN '21: The 20th International Conference on Information Processing in Sensor Networks, 2021

ADVERSARIALuscator: An Adversarial-DRL based Obfuscator and Metamorphic Malware Swarm Generator.
Proceedings of the International Joint Conference on Neural Networks, 2021

LSTM Hyper-Parameter Selection for Malware Detection: Interaction Effects and Hierarchical Selection Approach.
Proceedings of the International Joint Conference on Neural Networks, 2021

Identification of Adversarial Android Intents using Reinforcement Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

Designing Adversarial Attack and Defence for Robust Android Malware Detection Models.
Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2021

Duplicates in the Drebin Dataset and Reduction in the Accuracy of the Malware Detection Models.
Proceedings of the 26th IEEE Asia-Pacific Conference on Communications, 2021

2020
Assessment of the Relative Importance of different hyper-parameters of LSTM for an IDS.
Proceedings of the 2020 IEEE Region 10 Conference, 2020

How robust are malware detection models for Android smartphones against adversarial attacks?: poster abstract.
Proceedings of the SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems, 2020

DeepIntent: ImplicitIntent based Android IDS with E2E Deep Learning architecture.
Proceedings of the 31st IEEE Annual International Symposium on Personal, 2020

DOOM: a novel adversarial-DRL-based op-code level metamorphic malware obfuscator for the enhancement of IDS.
Proceedings of the UbiComp/ISWC '20: 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers, 2020

A Novel Spatial-Spectral Framework for the Classification of Hyperspectral Satellite Imagery.
Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference, 2020

Detection of Malicious Android Applications: Classical Machine Learning vs. Deep Neural Network Integrated with Clustering.
Proceedings of the Broadband Communications, Networks, and Systems, 2020

Identification of Significant Permissions for Efficient Android Malware Detection.
Proceedings of the Broadband Communications, Networks, and Systems, 2020

2019
Group-Wise Classification Approach to Improve Android Malicious Apps Detection Accuracy.
Int. J. Netw. Secur., 2019

Secure Communication Protocol for Smart Transportation Based on VC]Secure Communication Protocol for Smart Transportation Based on Vehicular Cloud.
CoRR, 2019

A Survey on the Detection of Android Malicious Apps.
CoRR, 2019

An Efficient Detection of Malware by Naive Bayes Classifier Using GPGPU.
CoRR, 2019

Detection of Advanced Malware by Machine Learning Techniques.
CoRR, 2019

Secure and Energy-Efficient Key-Agreement Protocol for Multi-server Architecture.
Proceedings of the Secure Knowledge Management In Artificial Intelligence Era, 2019

Secure communication protocol for smart transportation based on vehicular cloud.
Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019

2018
An investigation of the classifiers to detect android malicious apps.
CoRR, 2018

Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection.
Proceedings of the 19th IEEE/ACIS International Conference on Software Engineering, 2018

Android Malicious Application Classification Using Clustering.
Proceedings of the Intelligent Systems Design and Applications, 2018

Malware Detection Using Machine Learning and Deep Learning.
Proceedings of the Big Data Analytics - 6th International Conference, 2018

An investigation of a deep learning based malware detection system.
Proceedings of the 13th International Conference on Availability, Reliability and Security, 2018

2016
Improving the detection accuracy of unknown malware by partitioning the executables in groups.
CoRR, 2016

An effective approach for classification of advanced malware with high accuracy.
CoRR, 2016

Grouping the executables to detect malware with high accuracy.
CoRR, 2016

Covariance estimation for vertically partitioned data in a distributed environment.
CoRR, 2016

A communication efficient and scalable distributed data mining for the astronomical data.
Astron. Comput., 2016

K-means and Wordnet Based Feature Selection Combined with Extreme Learning Machines for Text Classification.
Proceedings of the Distributed Computing and Internet Technology, 2016

Distributed Multi-class Rule Based Classification Using RIPPER.
Proceedings of the 2016 IEEE International Conference on Computer and Information Technology, 2016

2015
A Novel Modified Apriori Approach for Web Document Clustering.
CoRR, 2015

Automated Document Indexing via Intelligent Hierarchical Clustering: A Novel Approach.
CoRR, 2015

A Novel Approach to Distributed Multi-Class SVM.
CoRR, 2015

Distributed Multi Class SVM for Large Data Sets.
Proceedings of the Third International Symposium on Women in Computing and Informatics, 2015

Extreme learning machines in the field of text classification.
Proceedings of the 16th IEEE/ACIS International Conference on Software Engineering, 2015

Hybrid Approach for Inductive Semi Supervised Learning Using Label Propagation and Support Vector Machine.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2015

Centroid based Binary Tree Structured SVM for multi classification.
Proceedings of the 2015 International Conference on Advances in Computing, 2015

2014
Evolution and Detection of Polymorphic and Metamorphic Malwares: A Survey.
CoRR, 2014

An Effective Approach for Web Document Classification using the Concept of Association Analysis of Data Mining.
CoRR, 2014

Web Document Clustering and Ranking using Tf-Idf based Apriori Approach.
CoRR, 2014

2012
An effective web document clustering for information retrieval
CoRR, 2012

An Effective Information Retrieval for Ambiguous Query
CoRR, 2012


  Loading...