Detecting malware and phishing with deep learning
The last decade’s growing interest in deep learning was triggered by the proven capacity of neural networks in computer vision tasks. If you train a neural network with enough labeled photos of cats and dogs, it will be able to find recurring patterns in each category and classify unseen images with decent accuracy.
What else can you do with an image classifier?
In 2019, a group of cybersecurity researchers wondered if they could treat security threat detection as an image classification problem. Their intuition proved to be well-placed, and they were able to create a machine learning model that could detect malware based on images created from the content of application files. A year later, the same technique was used to develop a machine learning system that detects phishing websites.
The combination of binary visualization and machine learning is a powerful technique that can provide new solutions to old problems. It is showing promise in cybersecurity, but it could also be applied to other domains.
Read the full article on TechTalks.
For more on machine learning and cybersecurity: