Ao Kaspersky Lab

Vladislav N Tushkanov

Anna D Larkina

Disclosed herein are systems and methods for creating a classifier for detecting phishing sites using Document Object Model (DOM) hashes. In one aspect, an exemplary method comprises: parsing each page of the website, wherein the parsing includes at least generating a DOM tree of the page, for each page, generating at least one string of DOM tree elements according to predetermined patterns, creating a first hash based on the string, creating a second hash for the page, generating a first dataset comprising hashes of safe pages and a second dataset comprising hashes of phishing pages, analyzing the first and second datasets to determine whether there is diversity of data in each dataset, generating a training sample from the datasets when there is diversity of data, and training a classifier of a machine learning model based on the training sample generated from the first and second datasets.

System and method of creating a classifier for detecting phishing sites using DOM hashes

Disclosed are systems and methods for limiting access of a user profile to dangerous content in a social network service. The described system produces a social graph for a given user profile in the social network service, and identifies clusters of objects (e.g., other user profiles, contents) within the social graph. The described system analyzes whether certain objects in the social graph should be characterized as suspicious based on their clustering and on a database of known forbidden objects. The described system may further learn and add unknown objects to the database of forbidden objects.

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Moscow, Russia

Vladislav N Tushkanov