Avast Software S.r.o.

Thomas Salomon

Thomas Wespel

Armin Wasicek

Christopher Joseph O'Connell

Barna Csukas

Fabrizio Biondi

Denis Shtyrov

Hai Tung Nguyen

A system and method for preventing access to potentially malicious network destinations. The method includes determining a plurality of network destinations and indicators of the plurality of network destinations including an indicator of a first network destination. A plurality of feature vectors are generated based on the plurality of network destinations including a first feature vector based on the first network destination. Access by a user via a computing device to a second network destination is detected. A second feature vector is generated, and an indicator is determined based on the second network destination. The second feature vector is compared to the plurality of feature vectors. The access by the user to the second network destination is blocked based on the indicator of the first network destination, the indicator of the second network destination, and the comparison of the second feature vector to the plurality of feature vectors.

Network attack prevention systems and methods

A method of filtering a URL against a blacklist includes receiving at least a portion of a Uniform Resource Locator (URL), and determining which of a plurality of XOR filters is applicable to the received at least a portion of a URL, where each of the plurality of XOR filters represents a different portion of a URL blacklist. At least a portion of a URL is forwarded to the applicable one of the plurality of XOR filters, and the at least a portion of the URL is processed in the applicable one of the plurality of XOR filters to produce an output indicating whether the URL is likely on the blacklist.

Blocked XOR filter for blacklist filtering

Systems and methods for determining software recommendations for a user. A first application list of applications installed on a user's computer is received. A distribution score is determined for each application in the first application list. A set of least distributed applications is determined based on the distribution score. A similarity score is determined for each user in a set of users having one or more applications of the set of least distributed applications installed on their respective systems. A second list of applications is determined based on applications installed by users in the set of users having a similarity score above a threshold. Recommendations for applications in the first list of applications are determined based, at least in part, on typicality scores for the applications.

Systems and methods for recommending software based on user similarity

A method and system for an automated classification rating of browser extensions is provided. One embodiments of the present invention can track the behavior of a large number of users in order to determine the reputation of browser extensions such as toolbars. The rating can be determined based on similarity analysis of previously rated browser extension attributes, and can be adjusted in response to a determination of the user's choice on the browser extension removal and reinstallation.

Cloud based reputation system for browser extensions and toolbars

A method and apparatus for an automated classification and reset of browser settings is provided. A set of disreputable browser setting values is maintained based on statistics associated with the browser setting values. In response to determining that an attempt is made to set a browser setting to a value in the set of disreputable browser setting values, a notification can be presented to the user. The notification can include options in a set of reputable browser settings.

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Neukirch, Germany

Thomas Salomon