公开(公告)号：US11570062B2

公开(公告)日：2023-01-31

申请号：US17130804

申请日：2020-12-22

Applicant: Cisco Technology, Inc.

Inventor： Enzo Fenoglio ,  Hugo M. Latapie ,  Kenneth Gray ,  Sawsen Rezig ,  David Delano Ward

IPC: H04L41/5009 ,  H04W28/02 ,  H04L41/16 ,  H04L43/08 ,  H04L41/22

Abstract: In one embodiment, a network quality assessment service that monitors a network obtains multimodal data indicative of a plurality of measurements from the network and subjective perceptions of the network by users of the network. The network quality assessment service uses the obtained multimodal data as input to one or more neural network-based models. The network quality assessment service maps, using a conceptual space, outputs of the one or more neural network-based models to symbols. The network quality assessment service applies a symbolic reasoning engine to the symbols, to generate a conclusion regarding the monitored network. The network quality assessment service provides an indication of the conclusion to a user interface.

公开(公告)号：US11074710B2

公开(公告)日：2021-07-27

申请号：US16724751

申请日：2019-12-23

Applicant: Cisco Technology, Inc.

Inventor： Huy Phuong Tran ,  Xu Zhang ,  Santosh Ghanshyam Pandey ,  Hugo Latapie ,  Abhishek Mukherji ,  Enzo Fenoglio

IPC: G06T7/70 ,  G06K9/46 ,  G01S5/02 ,  H04W4/33

Abstract: In one embodiment, a service obtains spatial information regarding a physical area. The service estimates locations of a device within the physical area over time, based on wireless signals sent by the device. The service generates a set of images based on the spatial information regarding the physical area and on the estimated locations of the device within the physical area over time. The service updates an estimated location of the device by inputting the generated set of images to a machine learning model trained to minimize a location estimation error.

公开(公告)号：US20210184915A1

公开(公告)日：2021-06-17

申请号：US17186148

申请日：2021-02-26

Applicant: Cisco Technology, Inc.

Inventor： Enzo Fenoglio ,  Hugo Latapie ,  David Delano Ward ,  Sawsen Rezig ,  Raphaël Wouters ,  Didier Colens ,  Donald Mark Allen ,  Dmitri Goloubev

IPC: H04L12/24 ,  G06N20/00 ,  G06N5/04 ,  H04L12/26

Abstract: In one embodiment, a service that monitors a network detects a plurality of anomalies in the network. The service uses data regarding the detected anomalies as input to one or more machine learning models. The service maps, using a conceptual space, outputs of the one or more machine learning models to symbols. The service applies a symbolic reasoning engine to the symbols, to rank the anomalies. The service sends an alert for a particular one of the detected anomalies to a user interface, based on its corresponding rank.

公开(公告)号：US10740675B2

公开(公告)日：2020-08-11

申请号：US16151783

申请日：2018-10-04

Applicant: Cisco Technology, Inc.

Inventor： Hugo Mike Latapie ,  Enzo Fenoglio ,  Joseph T. Friel ,  Andre Surcouf ,  Pascal Thubert

IPC: G06N3/08 ,  G06T7/246 ,  G06N3/04 ,  G06K9/00 ,  G06K9/62

Abstract: In one embodiment, a method includes receiving current data, the current data including time series data representing a plurality of time instances. The method includes storing at least a recent portion of the current data in a buffer. The method includes reducing the dimensionality of the current data to generate dimensionality-reduced data. The method includes generating a reconstruction error based on the dimensionality-reduced data and a plurality of neural network metrics. At least one of a size of the recent portion of the current data stored in the buffer or an amount of the reducing the dimensionality of the current data is based on the reconstruction error.

公开(公告)号：US20190253452A1

公开(公告)日：2019-08-15

申请号：US15896182

申请日：2018-02-14

Applicant: Cisco Technology, Inc.

Inventor： Hugo Latapie ,  Enzo Fenoglio ,  Pascal Thubert ,  Jean-Philippe Vasseur

IPC: H04L29/06 ,  G06F17/30 ,  G06N3/08 ,  G06F15/18

Abstract: In one embodiment, a device maintains a journal of uncommitted changes to a file system of the device in a layer that is hot-swappable with a writable container layer. The device augments the journal with metadata regarding a particular uncommitted change to the file system of the device. The device applies, within a sandbox environment of the device, a machine learning-based anomaly detector to the particular uncommitted change to the file system and the metadata regarding the change, to determine whether the particular uncommitted change to the file system is indicative of a destruction of service attack on the device. The device causes performance of a mitigation action when the machine learning-based anomaly detector determines that the particular uncommitted change to the file system is indicative of a destruction of service attack on the device.

公开(公告)号：US20190097809A1

公开(公告)日：2019-03-28

申请号：US15713463

申请日：2017-09-22

Applicant: Cisco Technology, Inc.

Inventor： Ronnie Dan ,  Hugo Mike Latapie ,  Andre Jean-Marie Surcouf ,  Enzo Fenoglio ,  Thierry Gruszka

IPC: H04L9/32 ,  H04L9/14 ,  H04L29/06

Abstract: In one illustrative example, a network cybersecurity procedure may be employed with use of at least one unmanned aerial vehicle (UAV), where the UAV includes an intermediary pairing device for providing a temporary connection between a first network (e.g. a private LAN) and a second network (e.g. the Internet). The network cybersecurity procedure may involve deploying the UAV in proximity to the first network, such that the intermediary pairing device pairs with a first pairing device via a first transceiver and with a second pairing device via a second transceiver. A temporary connection is established between the first network connected via the first pairing device and the second network connected via the second pairing device. Data is communicated between a first device (e.g. IoT device) or server of the first network and a second device or server of the second network over the temporary connection. During this time, the intermediary pairing device executes a cybersecurity service function. Once completed, the UAV may be withdrawn out of proximity of the first network. One or more features of the cybersecurity service function may be updated and the UAV redeployed. Multimodal data fusion techniques with use of a plurality of network and device sensors may be employed for device verification and/or anomaly detection.

公开(公告)号：US10158973B1

公开(公告)日：2018-12-18

申请号：US15662082

申请日：2017-07-27

Applicant: Cisco Technology, Inc.

Inventor： Andre Surcouf ,  Thierry Gruszka ,  Hugo Latapie ,  Ronnie Dan ,  Enzo Fenoglio

IPC: H04W4/02 ,  H04L29/08 ,  G08G1/123 ,  H04W88/02 ,  H04W4/04

Abstract: Techniques in an information-centric network (ICN) for facilitating the transport of passengers or items are described. In one illustrative example, a first mobile device is configured to operate as a mobile transportation-offering ICN endpoint device. The first mobile device may connect to one of a plurality of fixed-location ICN nodes in the ICN network. The first mobile device may communicate in the ICN network one or more interest packet messages indicating an interest in a passenger or item to transport. The interest in a passenger or item to transport may be indicated in, for example, a Named Data Object (NDO). The one or more interest packet messages may include current transportation route information indicating a current anticipated route of transportation for a current passenger or item. In response, the first mobile device may receive, from a second mobile device configured to operate as a mobile transportation-accepting ICN node, one or more response messages indicating an acceptance of the transport.

公开(公告)号：US10067810B2

公开(公告)日：2018-09-04

申请号：US15222890

申请日：2016-07-28

Applicant: Cisco Technology, Inc.

Inventor： Andre Jean-Marie Surcouf ,  Hugo Mike Latapie ,  Enzo Fenoglio ,  Joseph T. Friel

IPC: G06F9/54 ,  G06F21/60

Abstract: Various implementations disclosed herein provide a method for performing one or more transactions between application containers. In various implementations, the method includes transmitting a key request to a first network node within a cluster of network nodes that are configured to generate and maintain a distributed ledger. In some implementations, the key request indicates that the requested key is for one or more transactions between a first application container and a second application container. In various implementations, the method includes receiving a key in response to transmitting the key request. In some implementations, the key is valid for the one or more transactions between the first application container and the second application container. In various implementations, the method includes synthesizing, at the first application container, transaction data with the key. In various implementations, the method includes transmitting, by the first application container, the transaction data to the second application container.

公开(公告)号：US20180234348A1

公开(公告)日：2018-08-16

申请号：US15432385

申请日：2017-02-14

Applicant: Cisco Technology, Inc.

Inventor： Dmitry Goloubew ,  Gonzalo Salgueiro ,  Enzo Fenoglio ,  Hugo Latapie ,  Andre Surcouf

IPC: H04L12/825 ,  H04L12/24 ,  G06N99/00

CPC classification number: G06N20/00 ,  G06N3/0445 ,  G06N3/0454 ,  G06N3/08 ,  G06N7/005 ,  H04L41/0631 ,  H04L41/142 ,  H04L41/147 ,  H04L41/16 ,  H04L43/04 ,  H04L45/22 ,  H04L47/122

Abstract: In one embodiment, a device in a network receives control plane packet data indicative of control plane packets for a control plane in the network. The device models the control plane using a machine learning model based on the control plane packet data. The device predicts an instability in the control plane using the machine learning model. The device causes performance of a mitigation action based on the predicted instability in the control plane.

公开(公告)号：US20180165579A1

公开(公告)日：2018-06-14

申请号：US15374599

申请日：2016-12-09

Applicant: Cisco Technology, Inc.

Inventor： Joseph T. Friel ,  Andre Surcouf ,  Hugo Mike Latapie ,  Enzo Fenoglio ,  Pascal Thubert

IPC: G06N3/08 ,  G06N3/04

Abstract: In one embodiment, a method includes training a deep neural network using a first set of network characteristics corresponding to a first time and a second set of network characteristics corresponding to a second time, generating, using the deep neural network, a predictive set of network characteristics corresponding to a future time, and assigning a task of a distributed application to a processing unit based on the predictive set of network characteristics.