Ao Kaspersky Lab

Anton B Galchenko

Vladimir A Kuskov

Oleg V Kupreev

Vitaly V Kondratov

Mikhail V Ustinov

Disclosed are system and method for building statistical models of malicious elements of web pages. One exemplary method comprises: obtaining, by a control server, data about malicious elements of web pages; transforming, by the control server, the obtained data into at least one N-dimensional vector; creating, by the control server, at least one cluster based on elements of the at least one N-dimensional vector; and building, by the control server, the statistical model of the malicious elements of the web page based on the created at least one cluster.

System and methods for building statistical models of malicious elements of web pages

Disclosed are system and method for detecting anomalous or malicious elements of a web page. One exemplary method comprises: obtaining data about elements of a tested web page; generating at least one N-dimensional vector characterizing elements of the tested web page; retrieving a statistical model of known malicious web page elements; comparing the at least one N-dimensional vector with clusters of the statistical model of known malicious web page elements, by measuring the distance of the N-dimensional vector of the element and centers of all clusters of the statistical model; and identifying at least one malicious element of the tested web page based on results of the comparison.

System and methods of detecting malicious elements of web pages

Disclosed are system and method for detecting anomalous elements of web pages. One exemplary method comprises: obtaining access to a web site, by a client computing device, by requesting a web page associated with the web site via a web server; executing the web page by the client computing device to gather data relating to the web page; determining at least one N-dimensional vector based at least on the gathered data; creating at least one cluster comprising a set of values of coordinates of vectors for at least one element of the web page in N-dimensional space based on the at least one N-dimensional vector; creating a statistical model of the web page based on the at least one cluster; and using the statistical model for detecting anomalous elements of the web page.

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Moscow, Russia

Anton B Galchenko