LIGHTWEIGHT DISTRIBUTED APPLICATION SECURITY THROUGH PROGRAMMABLE EXTRACTION OF DYNAMIC METADATA

    公开(公告)号:US20210218771A1

    公开(公告)日:2021-07-15

    申请号:US16741794

    申请日:2020-01-14

    Abstract: Presented herein are methodologies for implementing application security. A method includes generating an extraction vector based on a plurality of application security rules to be enforced, transmitting the extraction vector to a first agent operating on a first network device and to a second agent operating on a second network device; receiving, separately, from the first agent and from the second agent, first metadata generated by the first agent and second metadata generated by the second agent by the agents applying the extraction vector to network traffic passing, respectively, through the first network device and the second network device. The first metadata includes a transaction ID assigned by the first agent, and the second metadata includes the same transaction ID. The method further includes correlating the first metadata with the second metadata based on the transaction ID to construct a transactional service graph for the network traffic.

    MALWARE CLASSIFICATION AND ATTRIBUTION THROUGH SERVER FINGERPRINTING USING SERVER CERTIFICATE DATA

    公开(公告)号:US20200267164A1

    公开(公告)日:2020-08-20

    申请号:US16869726

    申请日:2020-05-08

    Abstract: In one embodiment, a device in a network receives certificate data for an encrypted traffic flow associated with a client node in the network. The device determines one or more data features from the certificate data. The device determines one or more flow characteristics of the encrypted traffic flow. The device performs a classification of an application executed by the client node and associated with the encrypted traffic flow by using a machine learning-based classifier to assess the one or more data features from the certificate data and the one or more flow characteristics of the traffic flow. The device causes performance of a network action based on a result of the classification of the application.

    Hierarchical activation of behavioral modules on a data plane for behavioral analytics

    公开(公告)号:US10659484B2

    公开(公告)日:2020-05-19

    申请号:US15898915

    申请日:2018-02-19

    Abstract: In one embodiment, a centralized controller maintains a plurality of hierarchical behavioral modules of a behavioral model, and distributes initial behavioral modules to data plane entities to cause them to apply the initial behavioral modules to data plane traffic. The centralized controller may then receive data from a particular data plane entity based on its having applied the initial behavioral modules to its data plane traffic. The centralized controller then distributes subsequent behavioral modules to the particular data plane entity to cause it to apply the subsequent behavioral modules to the data plane traffic, the subsequent behavioral modules selected based on the previously received data from the particular data plane entity. The centralized controller may then iteratively receive data from the particular data plane entity and distribute subsequently selected behavioral modules until an attack determination is made on the data plane traffic of the particular data plane entity.

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