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AI Case Study

Pixm plans to enhance protection against phishing attacks using computer vision

Pixm's deep learning platform aims to detect phishing attacks in real time conducting a visual and spatial analysis on the browser to verify if its a phishing link.



Software And It Services

Project Overview

The Pixm solution would be downloaded to a computer like any other antivirus software.

According to the AWS blog: "When a customer opens a phishing link in their browser, the Pixm software visually analyzes the page and performs computer vision object detection coupled with spatial analysis to determine if it’s a phishing attack, and shuts it down within a second. For example, perpetrators often target customers of large banks, creating phishing sites that look just like an authorized bank’s website.

Using deep learning computer vision models created with the Apache MXNet deep learning framework, Pixm continually analyzes website screenshots. For example, Pixm uses object detection to train their models on brand logos to detect if a logo on a bank’s login page is authentic.

This is particularly effective against zero-day phishing attacks.
Pixm ships its software with MXNet bundled to run deep learning computer vision algorithms directly on the endpoint. By using deep-learning computer vision for real-time detection of phishing websites, Pixm helps protect clients from major cyberattacks and the costs associated with them, which can amount to millions of dollars and loss of customer trust."

Reported Results

Results undisclosed.



Information Technology



"According to a recent Verizon Data Breach Investigations Report 93% of all data breaches today start with a phishing attack. Two years ago, that was 91%."



Website screenshots

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