Spam-detection System Requirements Document

Introduction

The Spam-detection project aims to develop an AI-powered platform that leverages Machine Learning (ML) and Natural Language Processing (NLP) to automatically classify incoming messages as Spam or Not Spam (Ham). This system will address the growing challenge of spam messages, phishing attempts, and fraudulent communications across digital platforms.

System Overview

The Spam-detection system will provide a real-time, scalable, and automated solution for identifying spam messages. By analyzing message content and extracting meaningful features, the system will deliver fast and accurate predictions through a web-based interface and backend API. The platform will support real-time spam prediction, high classification accuracy, and a user-friendly interface, with a scalable backend architecture for future integration.

Functional Requirements

• As a User, I should be able to receive real-time spam predictions for incoming messages.
• As a User, I should be able to view the classification accuracy of the spam detection system.
• As a User, I should be able to interact with a user-friendly interface for managing spam detection settings.
• As a Developer, I should be able to integrate the spam detection API into other platforms.
• As a System Administrator, I should be able to scale the backend architecture to handle increased load.
• As a User, I should be able to extend the system to detect phishing URLs and malicious content.

User Personas

• End User: Individuals using the platform to filter spam messages in their personal or professional communications.
• Developer: Technical users integrating the spam detection API into other applications or platforms.
• System Administrator: IT professionals responsible for maintaining and scaling the backend infrastructure.

Visuals Colors and Theme

• primary: #2A9D8F (Teal)
• primary_light: #A8DADC (Light Teal)
• secondary: #E63946 (Crimson)
• accent: #F4A261 (Orange)
• highlight: #F4A261 (Amber)
• bg: #F1FAEE (Off White)
• surface: rgba(38, 70, 83, 0.8) (Dark Teal)
• text: #1D3557 (Dark Blue)
• text_muted: #457B9D (Muted Blue)
• border: rgba(233, 69, 96, 0.2) (Light Crimson)

Signature Design Concept

The homepage of the Spam-detection platform will feature an interactive "Spam Galaxy" concept. Users will navigate through a 3D galaxy where each star represents a different feature or section of the platform. By clicking on a star, users can explore detailed information about spam detection capabilities, system performance, and integration options. The galaxy will rotate and zoom as users interact, providing a dynamic and engaging experience. This concept will be implemented using @react-three/fiber for 3D rendering and gsap for smooth animations and transitions.

Interaction Model & Motion Direction

The landing page will utilize a "parallax" interaction model, creating a layered depth effect as users scroll through the page. Decorative elements will move at different speeds to enhance the visual storytelling, while real content will scroll naturally. This approach will provide a visually rich first impression, ideal for showcasing the platform's capabilities.

Non-Functional Requirements

• The system must handle a minimum of 10,000 concurrent users.
• The API response time should not exceed 200 milliseconds.
• The platform should maintain 99.9% uptime.
• The system must comply with data protection regulations, including GDPR.

Tech Stack

• Frontend: React + TypeScript + Tailwind
• Backend: Node.js + Express + TypeScript
• ML Service: Python (separate service)
• Database: PostgreSQL

Assumptions and Constraints

• The system will primarily target English language spam detection, with potential for multilingual support.
• The platform will be hosted on cloud infrastructure to ensure scalability.
• Users will require internet access to utilize the web-based interface.

Glossary

• Spam: Unwanted or unsolicited messages, often sent in bulk.
• Ham: Legitimate, non-spam messages.
• NLP: Natural Language Processing, a field of AI focused on the interaction between computers and humans through natural language.
• API: Application Programming Interface, a set of protocols for building and interacting with software applications.

This document outlines the foundational elements for the Spam-detection project, setting the stage for development and implementation. If you have any questions or need further clarification, feel free to reach out, Sasidhar!