Android Malware Detected Using Machine Learning to Automatically Detect and Click on Ads

The malware can switch to a signalling mode that allows attackers to manually scroll and tap through a live stream of the virtual screen.
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
GitHub

Machine Learning spam classifier achieving 98% accuracy using SVM, NLP, and TF-IDF vectorization

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
IEEE

Email Spam Detection using Machine Learning

Abstract: While the world of digital communication is expanding at an unprecedented rate, email spam has emerged as a major problem causing security threats, information redundancy, and loss of ...
Frontiers

MLVI-CNN: a hyperspectral stress detection framework using machine learning-optimized indices and deep learning for precision agriculture

Department of Electronics Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India Introduction: Early and accurate detection of crop stress is vital for ...
GitHub

MusXIII/SMS_SPAM_DETECTION

This project implements a machine learning model to classify SMS messages as "spam" or "ham" (not spam) using Decision Trees and TF-IDF vectorization. CS_Project_II/ ├── dataset/ │ └── spam.csv # SMS ...
IEEE

Spam Detection on YouTube Comment Section: Comparison Between Deep Learning and Machine Learning Methods

Abstract: The comment sections of YouTube are increasingly targeted by spam generated by automated bots, leading to harmful and misleading content. This study evaluates the performance of classical ...