JJEM: Special Edition 2 (December 2024)
JJEM: Special Edition 2 (December 2024)
2024-12-08
Detection of Spam Sms.
SNEHA D, Adarsh MJ
The speedy development of technology and the well-known use of mobile phones have introduced various risks, such as spam and phishing attacks. Machine learning is one of the top extensively used and renowned technologies for detecting spam in communications. This work integration machine learning techniques like logistic regression and other classifiers to build a spam detection model. Various data analysis techniques will be employed to predict and classify spam information from user data, ensuring a clear separation of spam from legitimate information the ulti mate aim is to develop a robust model that enhances information categorization thereby ensuring secure data storage on devices. Feature extraction methods help classify messages as spam or legitimate with high accuracy. This system enhances communication safety and reduces spam impact. It significantly improves the reliability of cellular interactions for consumers.
SMS, spam detection, machine learning, algorithms, CNN algorithm