Md. Shamsul Huda

Orcid: 0000-0001-7848-0508

According to our database1, Md. Shamsul Huda authored at least 69 papers between 2006 and 2025.

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

Timeline

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Bibliography

2025
Cross regional online food delivery: Service quality optimization and real-time order assignment.
Comput. Oper. Res., 2025

2024
A Cyber Risk Assessment Approach to Federated Identity Management Framework-Based Digital Healthcare System.
Sensors, August, 2024

MDS-Based Cloned Device Detection in IoT-Fog Network.
IEEE Internet Things J., June, 2024

Anonymous lattice-based authentication protocol for vehicular communications.
Veh. Commun., 2024

Highly-Secure Yet Efficient Blockchain-Based CRL-Free Key Management Protocol for IoT-Enabled Smart Grid Environments.
IEEE Trans. Inf. Forensics Secur., 2024

Untraceable blockchain-assisted authentication and key exchange in medical consortiums.
J. Syst. Archit., 2024

An enhanced pattern detection and segmentation of brain tumors in MRI images using deep learning technique.
Frontiers Comput. Neurosci., 2024

2023
Pashto Handwritten Invariant Character Trajectory Prediction Using a Customized Deep Learning Technique.
Sensors, July, 2023

Correction to: A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19.
J. Supercomput., June, 2023

A Privacy Frequent Itemsets Mining Framework for Collaboration in IoT Using Federated Learning.
ACM Trans. Sens. Networks, May, 2023

Feature Cloning and Feature Fusion Based Transportation Mode Detection Using Convolutional Neural Network.
IEEE Trans. Intell. Transp. Syst., April, 2023

Customer Analysis Using Machine Learning-Based Classification Algorithms for Effective Segmentation Using Recency, Frequency, Monetary, and Time.
Sensors, March, 2023

A Novel Approach to Improve Software Defect Prediction Accuracy Using Machine Learning.
IEEE Access, 2023

Non Functional Requirements Identification and Classification Using Transfer Learning Model.
IEEE Access, 2023

Near Feasibility Driven Adaptive Penalty Functions Embedded MOEA/D.
IEEE Access, 2023

A Comprehensive Survey of Machine Learning Methods for Surveillance Videos Anomaly Detection.
IEEE Access, 2023

2022
A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19.
J. Supercomput., 2022

An Industry-4.0-Complaint Sustainable Bitcoin Model Through Optimized Transaction Selection and Sustainable Block Integration.
IEEE Trans. Ind. Informatics, 2022

An Edge Tier Task Offloading to Identify Sources of Variance Shifts in Smart Grid Using a Hybrid of Wrapper and Filter Approaches.
IEEE Trans. Green Commun. Netw., 2022

Hand Gesture Recognition with Symmetric Pattern under Diverse Illuminated Conditions Using Artificial Neural Network.
Symmetry, 2022

An Advanced Boundary Protection Control for the Smart Water Network Using Semisupervised and Deep Learning Approaches.
IEEE Internet Things J., 2022

Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion.
Inf. Fusion, 2022

Prostate cancer classification from ultrasound and MRI images using deep learning based Explainable Artificial Intelligence.
Future Gener. Comput. Syst., 2022

2021
An Adaptive Trust Boundary Protection for IIoT Networks Using Deep-Learning Feature-Extraction-Based Semisupervised Model.
IEEE Trans. Ind. Informatics, 2021

A Robust Deep-Learning-Enabled Trust-Boundary Protection for Adversarial Industrial IoT Environment.
IEEE Internet Things J., 2021

Improving malicious PDF classifier with feature engineering: A data-driven approach.
Future Gener. Comput. Syst., 2021

A predictive intelligence approach to classify brain-computer interface based eye state for smart living.
Appl. Soft Comput., 2021

An Efficient, Hybrid Authentication Using ECG and Lightweight Cryptographic Scheme for WBAN.
IEEE Access, 2021

An Unsupervised Model for Identifying and Characterizing Dark Web Forums.
IEEE Access, 2021

2020
Increasing the Trustworthiness in the Industrial IoT Networks Through a Reliable Cyberattack Detection Model.
IEEE Trans. Ind. Informatics, 2020

A system call refinement-based enhanced Minimum Redundancy Maximum Relevance method for ransomware early detection.
J. Netw. Comput. Appl., 2020

An adaptive framework against android privilege escalation threats using deep learning and semi-supervised approaches.
Appl. Soft Comput., 2020

A robust cyberattack detection approach using optimal features of SCADA power systems in smart grids.
Appl. Soft Comput., 2020

Avoiding Future Digital Extortion Through Robust Protection Against Ransomware Threats Using Deep Learning Based Adaptive Approaches.
IEEE Access, 2020

Evolution of Dark Web Threat Analysis and Detection: A Systematic Approach.
IEEE Access, 2020

2019
Human emotion recognition using deep belief network architecture.
Inf. Fusion, 2019

Automatic extraction and integration of behavioural indicators of malware for protection of cyber-physical networks.
Future Gener. Comput. Syst., 2019

2018
A malicious threat detection model for cloud assisted internet of things (CoT) based industrial control system (ICS) networks using deep belief network.
J. Parallel Distributed Comput., 2018

Human Activity Recognition from Body Sensor Data using Deep Learning.
J. Medical Syst., 2018

Multistage fusion approaches based on a generative model and multivariate exponentially weighted moving average for diagnosis of cardiovascular autonomic nerve dysfunction.
Inf. Fusion, 2018

A hybrid-multi filter-wrapper framework to identify run-time behaviour for fast malware detection.
Future Gener. Comput. Syst., 2018

Identifying cyber threats to mobile-IoT applications in edge computing paradigm.
Future Gener. Comput. Syst., 2018

Securing the operations in SCADA-IoT platform based industrial control system using ensemble of deep belief networks.
Appl. Soft Comput., 2018

Malware Threats and Detection for Industrial Mobile-IoT Networks.
IEEE Access, 2018

An Ensemble Oversampling Model for Class Imbalance Problem in Software Defect Prediction.
IEEE Access, 2018

A Framework for Software Defect Prediction and Metric Selection.
IEEE Access, 2018

2017
Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabeled data.
Inf. Sci., 2017

Exponentially weighted control charts to monitor multivariate process variability for high dimensions.
Int. J. Prod. Res., 2017

A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression.
Concurr. Comput. Pract. Exp., 2017

A parallel framework for software defect detection and metric selection on cloud computing.
Clust. Comput., 2017

2016
Hybrids of support vector machine wrapper and filter based framework for malware detection.
Future Gener. Comput. Syst., 2016

A Hybrid Feature Selection With Ensemble Classification for Imbalanced Healthcare Data: A Case Study for Brain Tumor Diagnosis.
IEEE Access, 2016

2014
Hybrid Metaheuristic Approaches to the Expectation Maximization for Estimation of the Hidden Markov Model for Signal Modeling.
IEEE Trans. Cybern., 2014

A Hybrid Wrapper-Filter Approach for Malware Detection.
J. Networks, 2014

A hybrid wrapper-filter approach to detect the source(s) of out-of-control signals in multivariate manufacturing process.
Eur. J. Oper. Res., 2014

2013
An approach for Ewing test selection to support the clinical assessment of cardiac autonomic neuropathy.
Artif. Intell. Medicine, 2013

2011
Smart RFID Reader Protocol for Malware Detection.
Proceedings of the 12th ACIS International Conference on Software Engineering, 2011

Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem.
Proceedings of the 12th ACIS International Conference on Software Engineering, 2011

A Reinforcement Learning Approach with Spline-Fit Object Tracking for AIBO Robot's High Level Decision Making.
Proceedings of the Software Engineering, 2011

Multivariate control charts for surgical procedures.
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, 2011

Hybrid Wrapper-filter Aapproaches for Input Feature Selection using Maximum relevance-Minimum redundancy and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA).
Proceedings of the Thirty-Fourth Australasian Computer Science Conference, 2011

2010
Smokers' Characteristics and Cluster Based Quitting Rule Discovery Model for Enhancement of Government's Tobacco Control Systems.
Proceedings of the Pacific Asia Conference on Information Systems, 2010

Hybrid Wrapper-Filter Approaches for Input Feature Selection Using Maximum Relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA).
Proceedings of the Fourth International Conference on Network and System Security, 2010

Cluster Based Rule Discovery Model for Enhancement of Government's Tobacco Control Strategy.
Proceedings of the Fourth International Conference on Network and System Security, 2010

2009
A Constraint-Based Evolutionary Learning Approach to the Expectation Maximization for Optimal Estimation of the Hidden Markov Model for Speech Signal Modeling.
IEEE Trans. Syst. Man Cybern. Part B, 2009

A stochastic version of Expectation Maximization algorithm for better estimation of Hidden Markov Model.
Pattern Recognit. Lett., 2009

Process Performance Evaluation Using Evolutionary Algorithm.
Proceedings of the 2009 International Conference on Information & Knowledge Engineering, 2009

2007
A Hybrid Algorithm for Estimation of the Parameters of Hidden Markov Model based Acoustic Modeling of Speech Signals using Constraint-Based Genetic Algorithm and Expectation Maximization.
Proceedings of the 6th Annual IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), 2007

2006
A Variable Initialization Approach to the EM Algorithm for Better Estimation of the Parameters of Hidden Markov Model Based Acoustic Modeling of Speech Signals.
Proceedings of the Advances in Data Mining, 2006


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