Invention Grant
- Patent Title: Detecting encrypted malware with SPLT-based deep networks
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Application No.: US16216361Application Date: 2018-12-11
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Publication No.: US11201877B2Publication Date: 2021-12-14
- Inventor: Karel Bartos , Martin Vejman
- 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: Behmke Innovation Group
- Agent Kenneth J. Heywood; Jonathon P. Western
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N3/04 ; G06N3/08

Abstract:
In one embodiment, a device obtains telemetry data for a plurality of encrypted traffic flows observed in a network. The device clusters the flows into observed flow clusters, based on one or more flow-level features of the obtained telemetry data, as well as malware-related traffic telemetry data into malware-related flow clusters. The observed and malware-related telemetry data are indicative of sequence of packet lengths and times (SPLT) information for the traffic flows. The device samples sets of flows from the observed and malware-related flow clusters, with each set including at least one flow from an observed flow cluster and at least one flow from a malware-related flow cluster. The device trains a deep learning neural network to determine whether a particular encrypted traffic flow is malware-related, by using the SPLT information for the sampled sets of traffic flows as input to an input layer of neurons of the deep network.
Public/Granted literature
- US20200186547A1 DETECTING ENCRYPTED MALWARE WITH SPLT-BASED DEEP NETWORKS Public/Granted day:2020-06-11
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