This paper is published in Volume-10, Issue-1, 2024
Area
AIML
Author
Kaustubh Chaubey, Naufil Ahmed Siddique, Ayush Singh, Reena Kothari
Org/Univ
Shree L.R. Tiwari College of Engineering, Mira Bhayandar, Maharashtra, India
Pub. Date
04 April, 2024
Paper ID
V10I1-1287
Publisher
Keywords
Spam, Naive Bayes, NLP, Machine Learning, Fraud, Classifier.

Citationsacebook

IEEE
Kaustubh Chaubey, Naufil Ahmed Siddique, Ayush Singh, Reena Kothari. Preventia: Spam Alert System, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Kaustubh Chaubey, Naufil Ahmed Siddique, Ayush Singh, Reena Kothari (2024). Preventia: Spam Alert System. International Journal of Advance Research, Ideas and Innovations in Technology, 10(1) www.IJARIIT.com.

MLA
Kaustubh Chaubey, Naufil Ahmed Siddique, Ayush Singh, Reena Kothari. "Preventia: Spam Alert System." International Journal of Advance Research, Ideas and Innovations in Technology 10.1 (2024). www.IJARIIT.com.

Abstract

In the ever-evolving landscape of digital communication, the proliferation of spam content continues to be a pressing concern. The "Preventia: Spam Alert System" project aims to tackle this challenge head-on by implementing a comprehensive and intelligent solution for identifying and classifying spam. Through the application of the Naive Bayes algorithm, the system gains the ability to process vast amounts of data efficiently and make probabilistic predictions about whether incoming content is spam or legitimate. To bolster its capabilities further, the Spam Alert System integrates cutting edge technologies like natural language processing (NLP) to comprehend textual content more effectively. Subsequently, the Naive Bayes classifier evaluates the content, assigning a probability score that determines the likelihood of it being spam. The Spam Alert System's successful implementation delivers a powerful and flexible solution to the problem of spam, endowing users with heightened security and protection from fraudulent activities and potential privacy breaches. With seamless integration into popular communication platforms, users can enjoy real-time defence against malicious content across email, messaging services, and web browsers.