University · Third year

Securing IoT Devices

This module explores IoT security through the lens of machine learning and data analysis. Smart devices and IoT systems generate vast amounts of data — this project investigates how that data can be used to predict user behaviour, detect threats, and protect critical infrastructure from adversarial exploitation using neural networks and ML algorithms.

Securing the Internet of Things

Executive Summary

As a cybersecurity specialist, understanding how IoT data is collected and processed is critical for protecting individuals and nations from data theft and manipulation. This project uses an anonymous IoT dataset to build machine learning models — including a Neural Network and Convolutional Neural Network — that predict user actions from IoT device data. The work demonstrates practical application of ML to IoT security challenges including threat detection and resilience against adversarial attacks.

Key Highlights

Machine Learning Models

Neural Network and CNN models built to predict user behaviour from IoT device data.

IoT Threat Analysis

Evaluation of how adversaries exploit IoT data including Trojan apps and device manipulation.

Dataset Analysis

GPS and IoT datasets processed and analysed to extract actionable security insights.

Critical Infrastructure

Assessment of IoT risks to critical infrastructure and recommendations for resilience.

Academic Report (Word)

Full academic documentation including research, implementation details, testing methodology, and evaluation.

Download Word Document →

IoT Presentation

Datasets, Neural Network & Machine Learning Algorithms

GPS Dataset (CSV)

Download GPS Dataset →

Neural Network (Python)

Download Neural Network →

Convolutional Neural Network (Python)

Download CNN ML →

Technical Breakdown

  • IoT data collection, processing, and anonymisation techniques
  • Neural Network model design and training on IoT datasets
  • Convolutional Neural Network implementation for behaviour prediction
  • Threat modelling and adversarial attack analysis on IoT systems
  • Critical infrastructure risk assessment and mitigation strategies