Invention Grant
- Patent Title: Learning detector of malicious network traffic from weak labels
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Application No.: US14960086Application Date: 2015-12-04
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Publication No.: US09923912B2Publication Date: 2018-03-20
- Inventor: Vojtech Franc , Michal Sofka , Karel Bartos
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Agency: Edell, Shapiro & Finnan, LLC
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06F21/53

Abstract:
Techniques are presented that identify malware network communications between a computing device and a server utilizing a detector process. Network traffic records are classified as either malware or legitimate network traffic records and divided into groups of classified network traffic records associated with network communications between the computing device and the server for a predetermined period of time. A group of classified network traffic records is labeled as malicious when at least one of the classified network traffic records in the group is malicious and as legitimate when none of the classified network traffic records in the group is malicious to obtain a labeled group of classified network traffic records. A detector process is trained on individual classified network traffic records in the labeled group of classified network traffic records and network communication between the computing device and the server is identified as malware network communication utilizing the detector process.
Public/Granted literature
- US20170063893A1 LEARNING DETECTOR OF MALICIOUS NETWORK TRAFFIC FROM WEAK LABELS Public/Granted day:2017-03-02
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