公开(公告)号：US11170319B2

公开(公告)日：2021-11-09

申请号：US15581719

申请日：2017-04-28

Applicant: Cisco Technology, Inc.

Inventor： Sujit Biswas ,  Milind Naphade ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Srinivas Ruddaraju ,  Carlos M. Pignataro

IPC: G06N20/00

Abstract: In one embodiment, a computing device scans a plurality of available data sources associated with a profiled identity for an individual, and categorizes instances of the data sources according to recognized terms within the data sources. Once determining whether the profiled identity contributed positively to each categorized instance, categorized instances that have a positive contribution by the profiled identity may be clustered into clusters. The computing device may then rank the clusters based on size of the clusters and frequency of recognized terms within the clusters, and can then infer an expertise of the profiled identity based on one or more best-ranked clusters. The inferred expertise of the profiled identity may then be stored.

公开(公告)号：US10771488B2

公开(公告)日：2020-09-08

申请号：US15949198

申请日：2018-04-10

Applicant: Cisco Technology, Inc.

Inventor： Saurabh Verma ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Antonio Nucci

IPC: H04L29/06 ,  G06N3/08

Abstract: In one embodiment, a device receives sensor data from a plurality of nodes in a computer network. The device uses the sensor data and a graph that represents a topology of the nodes in the network as input to a graph convolutional neural network. The device provides an output of the graph convolutional neural network as input to a convolutional long short-term memory recurrent neural network. The device detects an anomaly in the computer network by comparing a reconstruction error associated with an output of the convolutional long short-term memory recurrent neural network to a defined threshold. The device initiates a mitigation action in the computer network for the detected anomaly.

公开(公告)号：US20190312898A1

公开(公告)日：2019-10-10

申请号：US15949198

申请日：2018-04-10

Applicant: Cisco Technology, Inc.

Inventor： Saurabh Verma ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Antonio Nucci

IPC: H04L29/06 ,  G06N3/08

Abstract: In one embodiment, a device receives sensor data from a plurality of nodes in a computer network. The device uses the sensor data and a graph that represents a topology of the nodes in the network as input to a graph convolutional neural network. The device provides an output of the graph convolutional neural network as input to a convolutional long short-term memory recurrent neural network. The device detects an anomaly in the computer network by comparing a reconstruction error associated with an output of the convolutional long short-term memory recurrent neural network to a defined threshold. The device initiates a mitigation action in the computer network for the detected anomaly.

公开(公告)号：US20240311512A1

公开(公告)日：2024-09-19

申请号：US18671930

申请日：2024-05-22

Applicant: Cisco Technology, Inc.

Inventor： Gyana Ranjan Dash ,  Antonio Nucci ,  Donald Mark Allen ,  Kabeer Noorudeen ,  Tatiana Alexandrovna Gaponova ,  Konstantin Grechishchev

IPC: G06F21/62 ,  G06F21/60 ,  H04L41/0813

CPC classification number: G06F21/6254 ,  G06F21/604 ,  H04L41/0813

Abstract: In one example embodiment, a server that is in communication with a network that includes a plurality of network elements obtains, from the network, a service request record that includes sensitive information related to at least one of the plurality of network elements. The server parses the service request record to determine that the service request record includes a sequence of characters that is repeated in the service request record, and tags the sequence of characters as a particular sensitive information type. Based on the tagging, the server identically replaces the sequence of characters so as to preserve an internal consistency of the service request record. After identically replacing the sequence of characters, the server publishes the service request record for analysis without revealing the sequence of characters.

公开(公告)号：US12026280B2

公开(公告)日：2024-07-02

申请号：US17164056

申请日：2021-02-01

Applicant: Cisco Technology, Inc.

Inventor： Gyana Ranjan Dash ,  Antonio Nucci ,  Donald Mark Allen ,  Kabeer Noorudeen ,  Tatiana Alexandrovna Gaponova ,  Konstantin Grechishchev

IPC: G06F7/04 ,  G06F21/60 ,  G06F21/62 ,  H04L41/0813

CPC classification number: G06F21/6254 ,  G06F21/604 ,  H04L41/0813

Abstract: In one example embodiment, a server that is in communication with a network that includes a plurality of network elements obtains, from the network, a service request record that includes sensitive information related to at least one of the plurality of network elements. The server parses the service request record to determine that the service request record includes a sequence of characters that is repeated in the service request record, and tags the sequence of characters as a particular sensitive information type. Based on the tagging, the server identically replaces the sequence of characters so as to preserve an internal consistency of the service request record. After identically replacing the sequence of characters, the server publishes the service request record for analysis without revealing the sequence of characters.

公开(公告)号：US20210150060A1

公开(公告)日：2021-05-20

申请号：US17164056

申请日：2021-02-01

Applicant: Cisco Technology, Inc.

Inventor： Gyana Ranjan Dash ,  Antonio Nucci ,  Donald Mark Allen ,  Kabeer Noorudeen ,  Tatiana Alexandrovna Gaponova ,  Konstantin Grechishchev

IPC: G06F21/62 ,  G06F21/60 ,  H04L12/24

Abstract: In one example embodiment, a server that is in communication with a network that includes a plurality of network elements obtains, from the network, a service request record that includes sensitive information related to at least one of the plurality of network elements. The server parses the service request record to determine that the service request record includes a sequence of characters that is repeated in the service request record, and tags the sequence of characters as a particular sensitive information type. Based on the tagging, the server identically replaces the sequence of characters so as to preserve an internal consistency of the service request record. After identically replacing the sequence of characters, the server publishes the service request record for analysis without revealing the sequence of characters.

公开(公告)号：US10963590B1

公开(公告)日：2021-03-30

申请号：US15964876

申请日：2018-04-27

Applicant: Cisco Technology, Inc.

Inventor： Gyana Ranjan Dash ,  Antonio Nucci ,  Donald Mark Allen ,  Kabeer Noorudeen ,  Tatiana Alexandrovna Gaponova ,  Konstantin Grechishchev

IPC: G06F7/04 ,  G06F21/62 ,  H04L12/24 ,  G06F21/60

Abstract: In one example embodiment, a server that is in communication with a network that includes a plurality of network elements obtains, from the network, a service request record that includes sensitive information related to at least one of the plurality of network elements. The server parses the service request record to determine that the service request record includes a sequence of characters that is repeated in the service request record, and tags the sequence of characters as a particular sensitive information type. Based on the tagging, the server identically replaces the sequence of characters so as to preserve an internal consistency of the service request record. After identically replacing the sequence of characters, the server publishes the service request record for analysis without revealing the sequence of characters.

公开(公告)号：US20180314956A1

公开(公告)日：2018-11-01

申请号：US15581719

申请日：2017-04-28

Applicant: Cisco Technology, Inc.

Inventor： Sujit Biswas ,  Milind Naphade ,  Manjula Shivanna ,  Gyana Ranjan Dash ,  Srinivas Ruddaraju ,  Carlos M. Pignataro

IPC: G06N5/04 ,  G06N99/00

Abstract: In one embodiment, a computing device scans a plurality of available data sources associated with a profiled identity for an individual, and categorizes instances of the data sources according to recognized terms within the data sources. Once determining whether the profiled identity contributed positively to each categorized instance, categorized instances that have a positive contribution by the profiled identity may be clustered into clusters. The computing device may then rank the clusters based on size of the clusters and frequency of recognized terms within the clusters, and can then infer an expertise of the profiled identity based on one or more best-ranked clusters. The inferred expertise of the profiled identity may then be stored.