Area of research
Electrical and Electronic Engineering · Computer Networks and Communications
Research interest
Research interests include Smart Grid Energy Management, Energy Load and Power Forecasting, Network Security and Intrusion Detection, and Anomaly Detection Techniques and Applications.
ResNeXt-SqueezeViTNet: A Ubiquitous Sensing Framework for Predictive Risk Assessment in Smart City Logistics Systems
Corrigendum to “ResSqueezeXNet: A lightweight deep learning framework for real-time agricultural logistics optimization in IoT environments”
Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks
Smart Farming: Enhancing Urban Agriculture Through Predictive Analytics and Resource Optimization
A Decision Framework for Intra Task Fixed Priority INTEL PXA270 Distributed Architecture for Soft RT- Applications Based on Deep Learning
BERT ensemble based MBR framework for android malware detection
Adaptive malware identification via integrated SimCLR and GRU networks
GNN-RMNet: Leveraging graph neural networks and GPS analytics for driver behavior and route optimization in logistics
Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism
REST Network: An Ensemble Deep Learning Approach for EV Charging Load Forecasting in Artificial Port Supply Chains
Regularized multi-path XSENet ensembler for enhanced student performance prediction in higher education
Enhancing Phishing Detection: A Novel Hybrid Deep Learning Framework for Cybercrime Forensics
Deep learning hybridization for improved malware detection in smart Internet of Things
Optimizing Electric Vehicle (EV) Charging with Integrated Renewable Energy Sources: A Cloud-Based Forecasting Approach for Eco-Sustainability
IoT-driven load forecasting with machine learning for logistics planning
Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection
Reliable renewable energy forecasting for climate change mitigation
Enhanced IoT Security for DDOS Attack Detection: Split Attention-Based ResNeXt-GRU Ensembler Approach
Nature-inspired approaches for clean energy integration in smart grids
Exploring Multi-Task Learning for Forecasting Energy-Cost Resource Allocation in IoT-Cloud Systems
Inclusive Smart Cities: IoT-Cloud Solutions for Enhanced Energy Analytics and Safety
Enhancing aspect-based multi-labeling with ensemble learning for ethical logistics
Online Payment Fraud Detection Model Using Machine Learning Techniques
Enhancing Smart IoT Malware Detection: A GhostNet-based Hybrid Approach
Ensemble learning approach for advanced metering infrastructure in future smart grids
Hybrid Algorithm-Driven Smart Logistics Optimization in IoT-Based Cyber-Physical Systems
An Efficient Optimized DenseNet Model for Aspect-Based Multi-Label Classification