Android application which uses openlysis back end.
The project leverages Naive Bayes Classifiers, a family of algorithms based on Bayes’ Theorem, which presumes independence between predictive features. This theorem is crucial for calculating the likelihood of a message being spam based on various characteristics of the data.
Spam SMS Detection using Machine Learning is a text classification project that identifies whether an SMS is spam or not. It uses NLP techniques for text preprocessing and a machine learning model to accurately detect unwanted messages.
End-to-end NLP pipeline for SMS spam classification using TF-IDF and Logistic Regression, evaluated with precision, recall, F1 and confusion matrix on imbalanced data.
S'CAN — Android privacy & security audit suite (Wi-Fi MITM, SMS scam detection, HIBP breach checker). Final-year UOW project.
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