Machine learning-based traffic classification using compressed network telemetry data

    公开(公告)号:US11025654B2

    公开(公告)日:2021-06-01

    申请号:US16450164

    申请日:2019-06-24

    摘要: In one embodiment, a device in a network receives telemetry data regarding a traffic flow in the network. One or more features in the telemetry data are individually compressed. The device extracts the one or more individually compressed features from the received telemetry data. The device performs a lookup of one or more classifier inputs from an index of classifier inputs using the one or more individually compressed features from the received telemetry data. The device classifies the traffic flow by inputting the one or more classifier inputs to a machine learning-based classifier.

    IDENTIFYING AND USING DNS CONTEXTUAL FLOWS
    104.
    发明申请

    公开(公告)号:US20200067972A1

    公开(公告)日:2020-02-27

    申请号:US16669831

    申请日:2019-10-31

    IPC分类号: H04L29/06 H04L29/12

    摘要: In one embodiment, a device in a network captures domain name system (DNS) response data from a DNS response sent by a DNS service to a client in the network. The device captures session data for an encrypted session of the client. The device makes a determination that the encrypted session is malicious by using the captured DNS response data and the captured session data as input to a machine learning-based or rule-based classifier. The device performs a mediation action in response to the determination that the encrypted session is malicious.

    MACHINE LEARNING-BASED TRAFFIC CLASSIFICATION USING COMPRESSED NETWORK TELEMETRY DATA

    公开(公告)号:US20190312894A1

    公开(公告)日:2019-10-10

    申请号:US16450164

    申请日:2019-06-24

    摘要: In one embodiment, a device in a network receives telemetry data regarding a traffic flow in the network. One or more features in the telemetry data are individually compressed. The device extracts the one or more individually compressed features from the received telemetry data. The device performs a lookup of one or more classifier inputs from an index of classifier inputs using the one or more individually compressed features from the received telemetry data. The device classifies the traffic flow by inputting the one or more classifier inputs to a machine learning-based classifier.

    LEVERAGING POINT INFERENCES ON HTTP TRANSACTIONS FOR HTTPS MALWARE DETECTION

    公开(公告)号:US20190245866A1

    公开(公告)日:2019-08-08

    申请号:US15889392

    申请日:2018-02-06

    IPC分类号: H04L29/06 G06N99/00

    摘要: In one embodiment, a traffic analysis service receives captured traffic data regarding a Transport Layer Security (TLS) connection between a client and a server. The traffic analysis service applies a first machine learning-based classifier to TLS records from the traffic data, to identify a set of the TLS records that include Hypertext Transfer Protocol (HTTP) header information. The traffic analysis service estimates one or more HTTP transaction labels for the connection by applying a second machine learning-based classifier to the identified set of TLS records that include HTTP header information. The traffic analysis service augments the captured traffic data with the one or more HTTP transaction labels. The traffic analysis service causes performance of a network security function based on the augmented traffic data.

    Machine learning-based traffic classification using compressed network telemetry data

    公开(公告)号:US10375090B2

    公开(公告)日:2019-08-06

    申请号:US15469716

    申请日:2017-03-27

    摘要: In one embodiment, a device in a network receives telemetry data regarding a traffic flow in the network. One or more features in the telemetry data are individually compressed. The device extracts the one or more individually compressed features from the received telemetry data. The device performs a lookup of one or more classifier inputs from an index of classifier inputs using the one or more individually compressed features from the received telemetry data. The device classifies the traffic flow by inputting the one or more classifier inputs to a machine learning-based classifier.

    Associating a user identifier detected from web traffic with a client address

    公开(公告)号:US10348745B2

    公开(公告)日:2019-07-09

    申请号:US15399003

    申请日:2017-01-05

    摘要: In one embodiment, a device in a network receives a set of known user identifiers used in the network. The device receives web traffic log data regarding web traffic in the network. The web traffic log data includes header information captured from the web traffic and a plurality of client addresses associated with the web traffic. The device detects a particular one of the set of known user identifiers in the header information captured from the web traffic associated with a particular one of the plurality of client addresses. The device makes an association between the particular detected user identifier and the particular client address.