Detecting Ransomware Threats Using a Machine Learning Approach

Ransomware attacks continue to rise, targeting individuals, businesses, and large institutions with devastating consequences. The client needed a lightweight, practical system that could identify ransomware behaviour the moment a new device connects, preventing threats before they spread across the network.

This project combined a machine learning classifier with a real-time file-scanning software component—resulting in a simple yet effective security layer that detects suspicious activity early.

Understanding the Problem

Traditional antivirus tools often rely on signatures, which fail against new or rapidly evolving ransomware variants. The client’s requirement was clear:

Build an ML model capable of recognising ransomware patterns
Integrate it into a real-time monitoring tool
Automatically scan files and metadata when a device connects
Flag potential threats instantly

The aim was to enhance early detection without forcing users to manage complex security workflows.

Our Approach

1. Turning Data Into Actionable Insight

We trained a machine learning classification model using the provided dataset, extracting key behavioural features that distinguish ransomware from benign files. These signals formed the backbone of the real-time detection logic.

2. Real-Time Monitoring Software

Once the ML model was ready, we built a software module that:

Detects new device connections
Iterates through files and their metadata
Analyses each entry using the trained ML classifier
Flags suspicious items for immediate review

This created a practical defence layer that works passively in the background.

3. Seamless Integration for Non-Technical Users

The final tool required no technical knowledge—just plug in a device and the system automatically runs its checks. Any detected anomalies were displayed clearly, helping users take action quickly.

Impact and Outcome

The project delivered a compact, effective ransomware detection solution that demonstrates how machine learning can strengthen everyday cybersecurity. The client gained:

A working ML-powered detection engine
Real-time threat identification
A clear workflow for analysing connected devices
A foundation to scale into a more advanced enterprise-grade security system

This project highlights how even a simple machine learning model, when paired with the right software architecture, can significantly reduce vulnerability to ransomware attacks.