Cisco Technology, Inc.

Robert Bukofser

Navindra Yadav

Supreeth Rao

Umamaheswaran Arumugam

Aiyesha Ma

Prasannakumar Jobigenahally Malleshaiah

Kai Zhu

Ashok K Kumar

Hanlin He

Kannan Ponnuswamy

Hazim Hashim Dahir

Alok Lalit Wadhwa

Furong Ma Gisiger

Saad Syed Hasan

Andrey Kvasyuk

Systems, methods, and computer-readable media for determine a neighborhood graph can include the following processes. A neighborhood graph system generates a neighborhood graph for a plurality of nodes in an enterprise network, the neighborhood graph representing a multi-hop connections between any two nodes of the plurality of nodes. A security score service determines a security score for each of the plurality of nodes to yield a plurality of scores. The neighborhood graph system updates the neighborhood graph of the plurality of nodes using the plurality of scores to provide a visual representation of securities of the plurality of nodes relative to each other.

Secure neighborhoods assessment in enterprise networks

Systems, methods, and computer-readable media for providing network assurance across a network. In some embodiments, network traffic data of a cluster of nodes in a network environment can be gathered based on first network traffic flowing through the nodes using a first group of sensors implemented in the network environment. Network events occurring in the network environment can be identified, e.g. using sensors deployed in an infrastructure of the network environment. Subsequently, the network events can be correlated with the network traffic data to generate correlated network data for the network environment. The correlated network data for the network environment can be used to provide assurance between at least one server in the cluster of nodes and the network infrastructure of the network environment as part of providing assurance across the network environment.

Cross-domain assurance

In one embodiment, a device obtains telemetry data regarding a plurality of traffic flows in a network. The device forms a directed graph based on the telemetry data, wherein nodes of the graph represent devices in the network. The device simulates traffic for one or more of the devices by performing random walks starting at a particular node on the directed graph to generate a set of trails, each trail representing a sequence of one or more flows. The device clusters the set of trails to form one or more clusters. The device generates an application fingerprint for an application based on one of the one or more clusters. The device uses the application fingerprint to identify traffic in the network as associated with the application.

Fingerprinting application traffic in a network

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Mason, NH, United States of America

Robert Bukofser