San Jose, CA, United States
San Jose, CA, United States

Cisco Systems, Inc. is an American multinational corporation headquartered in San Jose, California, that designs, manufactures, and sells networking equipment. The stock was added to the Dow Jones Industrial Average on June 8, 2009, and is also included in the S&P 500 Index, the Russell 1000 Index, NASDAQ-100 Index and the Russell 1000 Growth Stock Index. Wikipedia.

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Patent
Cisco Systems | Date: 2017-03-22

An electronic device includes a plurality of logic units, which have respective inputs and outputs and are arranged in a ring topology, such that an input of each of the logic units is coupled to an output of another of the logic units. Each of the logic units includes respective processing logic, which is identical to and operates in synchrony with the processing logic of the other logic units to process respective data values using at least one secret value stored in the device. The logic units are coupled, at an initial cycle of the device, to receive respective input values that are mutually uncorrelated. At subsequent cycles of the device, each of the logic units receives and operates on intermediate values that are output by another of the logic units.


Patent
Cisco Systems | Date: 2017-09-27

In one embodiment, a device in a network maintains a plurality of anomaly detection models for different sets of aggregated traffic data regarding traffic in the network. The device determines a measure of confidence in a particular one of the anomaly detection models that evaluates a particular set of aggregated traffic data. The device dynamically replaces the particular anomaly detection model with a second anomaly detection model configured to evaluate the particular set of aggregated traffic data and has a different model capacity than that of the particular anomaly detection model. The device provides an anomaly event notification to a supervisory controller based on a combined output of the second anomaly detection model and of one or more of the anomaly detection models in the plurality of anomaly detection models.


Patent
Cisco Systems | Date: 2017-09-20

A software defined network controller detects when a host has moved between network elements in a network. The controller generates a list of network elements to which the host has roamed, the list being sorted by time when the host is attached to a network element so that a most recent network element to which the host is attached is the root network element and at a head of the list. The controller updates the root network element in the list first for traffice flow associated with the host. The controller sends command to the network elements to program a tunnel from each previous point of attachment network element in the list to the most recent root network element in the list in reverse order of the roaming path so as to route traffic for the host via a tunnel.


Patent
Cisco Systems | Date: 2017-09-27

In one embodiment, a device in a network performs (810) anomaly detection functions using a machine learning-based anomaly detector to detect anomalous traffic in the network. The device identifies (815) an ability of one or more nodes in the network to perform at least one of the anomaly detection functions. The device selects (820) a particular one of the anomaly detection functions to offload to a particular one of the nodes, based on the ability of the particular node to perform the particular anomaly detection function. The device instructs (825) the particular node to perform the selected anomaly detection function.


A networking device in a network causes (1110) formation of device clusters of devices in the network exhibiting similar characteristics. The networking device receives (1115) feedback from a device identity service regarding the device clusters. The feedback is based in part on the device identity service probing the devices. The networking device adjusts (1120) the device clusters based on the feedback from the device identity service. The networking device performs (1125) anomaly detection in the network using the adjusted device clusters.


In one embodiment, a device in a network detects an anomaly in the network by analyzing a set of sample data regarding one or more conditions of the network using a behavioral analytics model. The device receives feedback regarding the detected anomaly. The device determines that the anomaly was a true positive based on the received feedback. The device excludes the set of sample data from a training set for the behavioral analytics model, in response to determining that the anomaly was a true positive.


A supervisory device in a network receives (810) traffic data from a security device that uses traffic signatures to assess traffic in the network. The supervisory device receives (815) traffic data from one or more distributed learning agents that use machine learning-based anomaly detection to assess traffic in the network. The supervisory device trains (820) a traffic classifier using the received traffic data from the security device and from the one or more distributed learning agents. The supervisory device deploys (825) the traffic classifier to a selected one of the one or more distributed learning agents.


Patent
Cisco Systems | Date: 2017-09-13

Presented herein are downstream recovery (error correction) techniques for an aggregated/consolidated media stream. In one example, a consolidated media stream that includes source media packets from one or more sources is sent to one or more downstream receiving devices. Based on the source media packets, one or more self-describing recovery packets for downstream error correction of the source media packets are generated. The self-describing recovery packets include a mapping to the source media packets used to generate the self-describing recovery packets, thereby avoiding the addition of error correction information in the consolidated media stream. The one or more self-describing recovery packets are sent to each of the downstream receiving devices as a separate stream.


A method is provided in one example embodiment and may include communicating information between a plurality of network function virtualized (NFV) based applications; and creating at least one service chain using at least two of the plurality of NFV-based applications based on the information communicated between the plurality NFV based applications. In some instances, the information can be communicated using border gateway protocol (BGP) exchanges between the NFV-based applications. In some instances, the information can include at least one of: next-hop address information for one or more ingress points of a particular NFV-based application; one or more capabilities by which a particular NFV-based application can receive data on one or more ingress points; and a method by which one or more egress points of a previous NFV-based application in a particular service chain is to perform load balancing for a subsequent NFV-based application in the particular service chain.


In one embodiment, a method includes importing a route target for a remote Virtual Routing and Forwarding instance (VRF) at a leaf node in an overlay network, the leaf node comprising at least one local VRF configured thereon, processing routes received for the route target at the leaf node, and installing the routes for the remote VRF at the local VRF at the leaf node to enable inter- VRF communication via the leaf node. An apparatus and logic are also disclosed herein.

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