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Recurrent neural networks for malware analysis

  • US 9,495,633 B2
  • Filed: 07/01/2015
  • Issued: 11/15/2016
  • Est. Priority Date: 04/16/2015
  • Status: Active Grant
First Claim
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1. A method comprising:

  • receiving or accessing data encapsulating a sample of at least a portion of one or more files;

    feeding at least a portion of the received or accessed data as a time-based sequence into a recurrent neural network (RNN) trained using historical data;

    extracting, by the RNN, a final hidden state hi in a hidden layer of the RNN in which i is a number of elements of the sample; and

    determining, using the RNN and the final hidden state, whether at least a portion of the sample is likely to comprise malicious code.

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