SYSTEM AND METHOD FOR DETECTING HOMOGLYPH ATTACKS WITH A SIAMESE CONVOLUTIONAL NEURAL NETWORK

摘要

The present invention utilizes computer vision technologies to identify potentially malicious URLs and executable files in a computing device. In one embodiment, a Siamese convolutional neural network is trained to identify the relative similarity between image versions of two strings of text. After the training process, a list of strings that are likely to be utilized in malicious attacks are provided (e.g., legitimate URLs for popular websites). When a new string is received, it is converted to an image and then compared against the image of list of strings. The relative similarity is determined, and if the similarity rating falls below a predetermined threshold, an alert is generated indicating that the string is potentially malicious.