Google Inc.

Mo Yu

Sai Deep Tetali

Salvador Mandujano

Richard G Cannings

Richard Cannings

A method for identifying malicious software includes receiving and executing a software application, identifying a plurality of uniform resource identifiers the software application interacts with during execution of the software application, and generating a vector representation for the software application using a feed-forward neural network configured to receive the plurality of uniform resource identifiers as feature inputs. The method also includes determining similarity scores for a pool of training applications, each similarity score associated with a corresponding training application and indicating a level of similarity between the vector representation for the software application and a respective vector representation for the corresponding training application. The method also includes flagging the software application as belonging to a potentially harmful application category when one or more of the training applications have similarity scores that satisfy a similarity threshold and include a potentially harmful application label.

Identify malicious software

A method () for identifying malicious software includes receiving and executing a software application (), identifying a plurality of uniform resource identifiers () the software application interacts with during execution of the software application, and generating a vector representation () for the software application using a feed-forward neural network () configured to receive the plurality of uniform resource identifiers as feature inputs. The method also includes determining similarity scores () for a pool of training applications, each similarity score associated with a corresponding training application and indicating a level of similarity between the vector representation for the software application and a respective vector representation for the corresponding training application. The method also includes flagging the software application as belonging to a potentially harmful application category () when one or more of the training applications have similarity scores that satisfy a similarity threshold and include a potentially harmful application label.

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Mountain View, CA, United States of America

Mo Yu