The project aims to create a website that classifies SMS messages as spam or legitimate, enhancing mobile security through machine learning techniques. It features real-time detection, a user-friendly interface, and prioritizes privacy protection. Future enhancements include adaptive learning, mobile app integration, and multi-language support.

1. SMS Span Detection
Enhancing Mobile security with Al-powered spam Detection
Presented by:
Pranali Ananda Varekar
Prachi Amar Sakhargade
Aachal Santosh Pattebahadur

2. Introduction
• This project aims to build a
website that can accurately
classify messages as either
spam or legitimate.
• The website will help to filter
unwanted message,for user
security.

3. Objectives
classify SMS
messages as
spam or
legitimate.
1
Enhance security
by
identifying harmf
ul messages.
2
The site is secure
and ensure the
privacy.
3

4. Features
REAL-TIME SMS
DETECTION.
MACHINE
LEARNING-BASED
CLASSIFICATION.
USER-FRIENDLY
INTERFACE.
PRIVACY
PROTECTION.
SCALABILITY.

5. Technologies
Used
• Programming Language:
Python.
• Libraries & Tools : NLP:
NLTK, Spacy.
• Dataset: SMS Spam
Collection (Kaggle).
• Database: MySQL
• Hosting: Google Cloud.

6. System
Architecture
• Step 1: User submits message via the frontend
(website).
• Step 2: Frontend sends message to the backend
server.
• Step 3: Backend communicates with the
machine learning model to classify the message.
• Step 4: Model returns classification result (spam
or ham) to the backend.
• Step 5: Backend sends result back to the
frontend for the user to view.

7. Challenges &
Solutions
• Accuracy of Detection:
Solution: Update the model with new data and
use advanced algorithm like deep learning.
• Privacy Concerns:
Solution: Ensure secure data processing and
clear privacy policies.
• Continuous Model Improvement:
Solution: Regularly retrain the model with new
spam data and user feedback.

8. Future
Enhancements
• AI-based adaptive learning for
new spam trends.
• Mobile app integration.
• Multi-language spam detection.
• Improved accuracy.

9. conclusion
the SMS Spam Detection website
helps users easily identify and
detect spam messages using
machine learning. With a simple
and user-friendly interface, it
provides quick results and improves
security. This project makes it
easier for users to avoid unwanted
messages and offers a useful tool
for developers to add spam
detection to their own apps.

10. Thank You !