Python
Efficient Machine Learning Models for Solar Radiation Prediction Using Ensemble Techniques: A Case Study in Low-Rainfall Arid Climates
Emoji, Sentiment and Emotion Aided Cyberbullying Detection in Hinglish
Enabling Ternary Hash Tree based Integrity Verification for Secure Cloud Data Storage
Enhancing Medical Education through interactive AR
Enhancing Road Safety: Detection of Animals on Highways During Night
Enhancing Smishing Detection A Deep Learning Approach for Improved Accuracy and Reduced False Positives
The aim of this work is to explore and develop advanced methods for enhancing the detection and prevention of smishing attacks. This involves utilizing cutting-edge technologies such as machine learning, artificial intelligence, and behavioral analysis to identify and block fraudulent SMS messages, protecting users from financial and personal data theft. The goal is to create more effective, real-time detection systems to mitigate the growing threat of smishing attack
Ephemeral Secret Leakage-Free ID-Role-Based Access Control Authentication and Key Exchange Protocol for Securing Electric Vehicle Data
Evasion Attacks and Defense Mechanisms for Machine Learning-Based Web Phishing Classifiers
Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System
Evolving Malware and DDoS Attacks: Decadal Longitudinal Study
Face Detection and Recognition for Criminal Identification System
