Invention Grant
- Patent Title: Systems and methods for malicious code detection
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Application No.: US15944679Application Date: 2018-04-03
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Publication No.: US10685284B2Publication Date: 2020-06-16
- Inventor: Cathal Smyth , Cory Fong , Yik Chau Lui , Yanshuai Cao
- Applicant: ROYAL BANK OF CANADA
- Applicant Address: CA Toronto
- Assignee: ROYAL BANK OF CANADA
- Current Assignee: ROYAL BANK OF CANADA
- Current Assignee Address: CA Toronto
- Agency: Norton Rose Fulbright Canada LLP
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N3/08 ; G06F21/56 ; G06N3/04 ; G06F17/16

Abstract:
There is provided a neural network system for detection of malicious code, the neural network system comprising: an input receiver configured for receiving input text from one or more code input sources; a convolutional neural network unit including one or more convolutional layers, the convolutional unit configured for receiving the input text and processing the input text through the one or more convolutional layers; a recurrent neural network unit including one or more long short term memory layers, the recurrent neural network unit configured to process the output from the convolutional neural network unit to perform pattern recognition; and a classification unit including one or more classification layers, the classification unit configured to receive output data from the recurrent neural network unit to perform a determination of whether the input text or portions of the input text are malicious code or benign code.
Public/Granted literature
- US20180285740A1 SYSTEMS AND METHODS FOR MALICIOUS CODE DETECTION Public/Granted day:2018-10-04
Information query