Intrusion Detection System (IDS) Project Requirements

Overview

The Intrusion Detection System (IDS) project aims to provide an efficient and scalable solution for detecting malicious network traffic patterns. It utilizes machine learning models trained on the NSL-KDD dataset and provides a user-friendly interface for visualization and analysis. The system includes a backend for processing data, generating predictions, and creating visual summaries, along with a frontend for user interaction.

Functional Requirements

1. Data Processing

Input:
- Accept uploaded CSV files containing network traffic data in the NSL-KDD dataset format.
Preprocessing:
- Handle missing or incorrect data gracefully.
- Encode categorical features using one-hot encoding.
- Scale numerical features using a pre-trained StandardScaler.

2. Machine Learning Model

Model Details:
- Load a pre-trained Random Forest model (Random_Forest.joblib) for classification.
Predictions:
- Classify network traffic into the following categories: Normal, DoS, Probe, R2L, U2R.

3. Visualization

Graphical Representation:
- Display results in a bar graph with:
  - X-axis labeled with traffic categories.
  - Y-axis representing the count of instances.
- Labels for aggregated categories: “Normal Traffic” and “Malicious Traffic.”
Summary Report:
- Provide a numerical summary:
  - Count of normal traffic.
  - Count of all malicious traffic (aggregated).

4. Backend

APIs:
- /upload: Accepts file uploads and triggers processing.
- /process: Processes uploaded data, generates predictions, and creates visual output.
Error Handling:
- Return appropriate error messages for:
  - Missing files.
  - Model loading issues.
  - Invalid data format.

5. Frontend

User Interface:
- Provide buttons to:
  - Upload files.
  - Trigger data processing.
- Display the generated graph and summary report.
Interactivity:
- Ensure responsive and dynamic updates without reloading the page.

Non-Functional Requirements

1. Performance

Processing Time:
- Ensure data processing and prediction are completed within 5 seconds for datasets up to 10,000 rows.

2. Scalability

File Size:
- Handle CSV files up to 50 MB.
Concurrent Users:
- Support up to 100 simultaneous users.

3. Security

Data Validation:
- Validate uploaded files to prevent malicious data injections.
Model Security:
- Protect model files from unauthorized access.

4. Maintainability

Code Modularity:
- Separate concerns into distinct modules for preprocessing, model loading, and visualization.

Technical Requirements

1. Backend

Programming Language: Python 3.9+
Frameworks: Flask
Dependencies:
- pandas
- numpy
- matplotlib
- scikit-learn
- joblib

2. Frontend

Framework: Next.js
Language: TypeScript
CSS: Tailwind CSS

3. Deployment

Containerization: Docker
Orchestration: Kubernetes
Cloud: AWS (ECS Fargate, S3 for storage)

4. Infrastructure

Tools: Terraform for IaC
Storage: Amazon S3 for temporary file storage

Deliverables

Fully functional IDS application.
Dockerized backend and frontend services.
Kubernetes deployment manifests.
Documentation:
- User guide.
- Deployment guide.
- Developer guide.

Future Enhancements

Add real-time traffic monitoring.
Support additional data formats beyond NSL-KDD.
Integrate advanced visualization tools (e.g., D3.js).
Extend model to support additional attack categories.
Allow users to be able to sign up and save charts and results.
Allow users to use common type of network data

Intrusion Detection System: Documentation

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Intrusion Detection System

Part 1: Setting Up Initial AWS Infrastructure for the Intrusion Detection System with Terraform

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Intrusion Detection System (IDS) Project Requirements

Overview

Functional Requirements

1. Data Processing

2. Machine Learning Model

3. Visualization

4. Backend

5. Frontend

Non-Functional Requirements

1. Performance

2. Scalability

3. Security

4. Maintainability

Technical Requirements

1. Backend

2. Frontend

3. Deployment

4. Infrastructure

Deliverables

Future Enhancements

Command Palette

Comments

Intrusion Detection System

Part 1: Setting Up Initial AWS Infrastructure for the Intrusion Detection System with Terraform

More from this blog

Intrusion Detection System (IDS) Project Requirements

Overview

Functional Requirements

1. Data Processing

2. Machine Learning Model

3. Visualization

4. Backend

5. Frontend

Non-Functional Requirements

1. Performance

2. Scalability

3. Security

4. Maintainability

Technical Requirements

1. Backend

2. Frontend

3. Deployment

4. Infrastructure

Deliverables

Future Enhancements