Saikat Das

Orcid: 0000-0003-1142-8259

According to our database1, Saikat Das authored at least 22 papers between 2016 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
State of the art: Security Testing of Machine Learning Development Systems.
Proceedings of the 14th IEEE Annual Computing and Communication Workshop and Conference, 2024

Trusting Classifiers with Interpretable Machine Learning Based Feature Selection Backpropagation.
Proceedings of the 14th IEEE Annual Computing and Communication Workshop and Conference, 2024

2023
Predicting the outbreak of epidemics using a network-based approach.
Eur. J. Oper. Res., September, 2023

Classification of lung cancer from histopathology Images using a Deep Ensemble Classifier.
Proceedings of the IEEE International Conference on Imaging Systems and Techniques, 2023

Explainability of Artificial Intelligence Systems: A Survey.
Proceedings of the International Symposium on Networks, Computers and Communications, 2023

Requirements Elicitation and Stakeholder Communications for Explainable Machine Learning Systems: State of the Art.
Proceedings of the International Conference on Information Technology, 2023

Handling Node Discovery Problem in Fog Computing using Categorical51 Algorithm With Explainability.
Proceedings of the 2023 IEEE World AI IoT Congress (AIIoT), 2023

2022
Network Intrusion Detection and Comparative Analysis Using Ensemble Machine Learning and Feature Selection.
IEEE Trans. Netw. Serv. Manag., December, 2022

Securing IoT devices using Ensemble Machine Learning in Smart Home Management System.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Cascading Failure Risk Analysis of Electrical Power Grid.
Proceedings of the Future Technologies Conference, 2022

MVE-based Reinforcement Learning Framework with Explainability for improving Quality of Experience of Application Placement in Fog Computing.
Proceedings of the 2022 IEEE World AI IoT Congress (AIIoT), 2022

2021
Machine Learning application lifecycle augmented with explanation and security.
Proceedings of the 12th IEEE Annual Ubiquitous Computing, 2021

2020
Application of the Mixture of Lognormal Distribution to Represent the First-Order Statistics of Wireless Channels.
IEEE Syst. J., 2020

Detecting stealthy false data injection attacks in the smart grid using ensemble-based machine learning.
Comput. Secur., 2020

Taxonomy and Survey of Interpretable Machine Learning Method.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Network Intrusion Detection using Natural Language Processing and Ensemble Machine Learning.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Elliptic Envelope Based Detection of Stealthy False Data Injection Attacks in Smart Grid Control Systems.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Interpretable Machine Learning Tools: A Survey.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Empirical Evaluation of the Ensemble Framework for Feature Selection in DDoS Attack.
Proceedings of the 7th IEEE International Conference on Cyber Security and Cloud Computing, 2020

2019
DDoS Intrusion Detection Through Machine Learning Ensemble.
Proceedings of the 19th IEEE International Conference on Software Quality, 2019

2018
CoRuM: Collaborative Runtime Monitor Framework for Application Security.
Proceedings of the 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion, 2018

2016
CLOUBEX: A Cloud-Based Security Analysis Framework for Browser Extensions.
Proceedings of the 17th IEEE International Symposium on High Assurance Systems Engineering, 2016


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