Vmware, Inc.

Nicira, Inc.

Russell Lu

Jayant Jain

Rick Lund

Ly Loi

Sushruth Gopal

Alok S Tiagi

Anirban Sengupta

Raju Koganty

Subrahmanyam Manuguri

Shadab Shah

Margaret Angeline Petrus

Arnold Poon

Laxmikant Vithal Gunda

Jingmin Zhou

Sunitha Krishna

Xin Qi

Ming Wen

Yangyang Zhu

Edilmo Palencia

Some embodiments provide a novel method for collecting and analyzing attributes of data flows associated with machines executing on a plurality of host computers to detect anomalous behavior. In some embodiments, an anomalous behavior is detected for at least one particular flow associated with at least one machine executing on the host computer. In some embodiments, anomaly detection is based on the context data from the guest introspection agent and deep packet inspection. An identifier of the detected anomalous behavior is stored, in some embodiments. The stored attributes are provided, in some embodiments, to a server for further analysis.

Offloading anomaly detection from server to host

Some embodiments provide a novel method for collecting and reporting attributes of data flows associated with machines executing on a plurality of host computers to an analysis appliance. Each host computer, in some embodiments, is responsible for collecting and reporting attributes of data flows associated with machines executing on a host computer. In some embodiments, the host computer includes a flow exporter that processes and publishes flow data to the analysis appliance, a set of agents for collecting context data relating to the flows from machines executing on the host, a set of additional modules that provide additional context data, an anomaly detection engine that analyzes flow data and context data and provides additional context data, and a context exporter for processing and publishing context data to the analysis appliance.

Host-based flow aggregation

Some embodiments provide a novel method for collecting and reporting attributes of data flows associated with machines executing on a plurality of host computers to an analysis appliance. The analysis appliance, in some embodiments, receives definitions of keys and provides them to the host computers. In some embodiments, existing keys are modified based on the analysis. Additionally, or alternatively, new keys are provided based on the analysis. In some embodiments, the analysis appliance receives the flow group records (e.g., sets of attributes) based on the keys and the configuration data from each host computer.

Dynamically providing keys to host for flow aggregation

The disclosure provides an approach for establishing authentication between components in a network. Embodiments deploying a node of a monitoring appliance in response to a request and providing a token for accessing a network manager to the node of the monitoring appliance. Embodiments include generating, by the node of the monitoring appliance, a certificate of the node of the monitoring appliance and providing the certificate of the node of the monitoring appliance to the network manager with the token for accessing the network manager. Embodiments include adding, by the network manager, based on the token for accessing the network manager, the certificate of the node of the monitoring appliance to a first trust store and providing, by the network manager, a network manager certificate to the node of the monitoring appliance. Embodiments include adding, by the node of the monitoring appliance, the network manager certificate to a second trust store.

Apparatus to automatically establish or modify mutual authentications amongst the components in a software defined networking (SDN) solution

Some embodiments provide a novel method for collecting and reporting attributes of data flows associated with machines executing on a plurality of host computers to an analysis appliance. Each host computer, in some embodiments, is responsible for collecting and reporting attributes of data flows associated with machines executing on a host computer. The host computer, in some embodiments, first eliminates duplicative flow group records and then aggregates the flow data according to a set of received keys that specify attributes that define the aggregation. For example, a simple key that specifies a set of machine identifiers (e.g., a VM ID) as attribute values will, for each machine identifier, aggregate all flows with that machine identifier into a single aggregated flow group record. In some embodiments, the host computer includes a flow exporter that processes and publishes flow data to the analysis appliance.

Using keys to aggregate flow attributes at host

For a network including multiple host machines that together implement at least one logical network including a firewall, some embodiments provide a method for collecting traffic flow data that includes identifiers for firewall rules applied to the traffic flow and a logical entity identifier. In some embodiments, the host machines receive traffic monitoring configuration data for a logical network. The traffic monitoring configuration data in some embodiments indicates a set of logical entities of the logical network for which to collect traffic flow data and a set of traffic flow data collectors associated with the set of logical entities. The indicated logical entities may be logical forwarding elements (logical switches, routers, etc.) or logical ports of logical forwarding elements.

Internet protocol flow data including firewall rules

A computer system provides a method for identifying firewall rules to apply to a virtual machine based on detecting initiation of a new network connection from the virtual machine. An example method generally includes detecting initiation of communications on a network port by a virtual machine, identifying one or more applications executing on the virtual machine that initiated communications on the network port, identifying one or more firewall rules to apply to the virtual machine based, at least in part, on the identification of the one or more applications, determining a deviation between firewall rules applied to the virtual machine and the identified one or more firewall rules, and upon determining that a deviation exists between the firewall rules applied to the virtual machine and the identified one or more firewall rules, applying one or more rules corresponding to the determined deviation to the virtual machine.

Security policy analysis based on detecting new network port connections

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Pleasanton, CA, United States of America

Russell Lu