Enhancing MQTT Intrusion Detection in IoT using Machine Learning and Feature Engineering

Project Code :TCMAPY1898

Objective

The primary objective of this project is to enhance intrusion detection in IoT networks using MQTT by implementing advanced machine learning techniques. The first key objective is to develop an intrusion detection system that leverages CatBoost, LightGBM, and AdaBoost to classify different attack types within MQTT-based IoT communication, ensuring high accuracy in detecting threats. Another important goal is to perform feature selection using Random Forest to identify the most relevant features from the network traffic data, thereby improving the overall model accuracy while reducing unnecessary computational complexity.

Abstract

The rapid growth of IoT (Internet of Things) systems has made them integral to a variety of industries, from smart homes to industrial automation. However, the increasing connectivity of IoT devices introduces significant security challenges. The MQTT (Message Queuing Telemetry Transport) protocol, widely used in IoT communication due to its lightweight and efficient design, is vulnerable to various types of intrusions. These vulnerabilities can potentially compromise the integrity of the IoT ecosystem. This project focuses on enhancing the intrusion detection capabilities in IoT systems by leveraging machine learning techniques and feature engineering. The goal is to develop an efficient and accurate intrusion detection system that identifies various attack types, including DoS attacks, ARP poisoning, and network scanning techniques.

Keywords: MQTT, IoT, Intrusion Detection, Machine Learning, Feature Engineering, CatBoost, LightGBM, AdaBoost, Random Forest, Security.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

HARDWARE REQUIREMENTS

• Processor - I5/Intel Processor

• RAM - 8GB (min)

• Hard Disk - 160 GB

• Key Board - Standard Windows Keyboard

• Mouse - Two or Three Button Mouse

• Monitor - Any

SOFTWARE REQUIREMENS

• Operating System : Windows 7/8/10

• Server side Script : HTML, CSS, Bootstrap & JS

• Programming Language : Python

• Libraries : Flask, Pandas, Mysql.connector, Os, Numpy,

Scikit-learn.

• IDE/Workbench : VS-Code

• Technology : Python 3.10+

• Server Deployment : Xampp Server

• Database : MySQL

Demo Video

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