公开(公告)号：US10904643B2

公开(公告)日：2021-01-26

申请号：US16378286

申请日：2019-04-08

Applicant: PINDROP SECURITY, INC.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04M1/56 ,  H04M15/06 ,  H04Q3/70 ,  H04M3/22 ,  H04M7/12 ,  H04Q1/45 ,  G10L25/51 ,  H04L25/02 ,  H04M3/493

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

公开(公告)号：US20220337924A1

公开(公告)日：2022-10-20

申请号：US17857618

申请日：2022-07-05

Applicant: Pindrop Security, Inc.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04Q3/70 ,  H04M3/22 ,  H04M7/12 ,  H04Q1/45 ,  G10L25/51 ,  H04L25/02 ,  H04M3/493

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

公开(公告)号：US10685008B1

公开(公告)日：2020-06-16

申请号：US15587143

申请日：2017-05-04

Applicant: PINDROP SECURITY, INC.

Inventor： Aditya Kurve ,  Hassan Kingravi

IPC: G06F16/23 ,  G10L17/04 ,  G10L17/18 ,  G06F21/44

Abstract: Systems and methods for classification using an explicit feature map or an approximate feature map based on a relative locality measure. In at least one embodiment, a method of authenticating a user operates data points having feature vectors pertaining to user events comprises selecting an approximate feature map based on a subset of features in each data point and a relative locality measure of a cluster including a plurality of the data points; mapping, to a feature space, the subset of features in each data point and a new data point pertaining to a phone call of the user using the selected approximate feature map; determining a classification of the new data point based on its relative locality measure with respect to a cluster in the feature space; storing the classification of the new data point in a memory device; and authenticating the user during the phone call.

公开(公告)号：US10666792B1

公开(公告)日：2020-05-26

申请号：US15217780

申请日：2016-07-22

Applicant: PINDROP SECURITY, INC.

Inventor： Aude Marzuoli ,  Hassan Kingravi ,  David Dewey

IPC: H04M3/22 ,  H04L29/08 ,  H04M7/00 ,  G10L15/26 ,  G06N20/00 ,  G06F16/35 ,  G06F16/61

Abstract: Methods and systems for detecting new calls from an existing spam or robocaller and aggregating calls that originate from the same infrastructure using a telephony honeypot are disclosed. An example method may receive a telephone call to a telephony honeypot and store metadata and a call audio recording associated with the telephone call. A transcript may be created of the call audio recording. Audio features may be extracted from the call audio recording. The transcript may be compared to other previously-received transcripts in order to determine a similarity between the call and previously-received calls. Audio features and metadata may also be compared to determine whether the call is similar to other previously-received calls. If a call is similar, the call may be identified with the same spam campaign or robocaller as the similar, previously-received call.

公开(公告)号：US10257591B2

公开(公告)日：2019-04-09

申请号：US15600625

申请日：2017-05-19

Applicant: PINDROP SECURITY, INC.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04M1/56 ,  H04M15/06 ,  H04Q3/70 ,  G10L25/51 ,  H04L25/02 ,  H04M3/493 ,  H04M3/22 ,  H04M7/12 ,  H04Q1/45

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

公开(公告)号：US20240323270A1

公开(公告)日：2024-09-26

申请号：US18680327

申请日：2024-05-31

Applicant: Pindrop Security, Inc.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04M1/56 ,  G10L25/51 ,  H04L25/02 ,  H04M3/22 ,  H04M3/493 ,  H04M7/12 ,  H04Q1/45 ,  H04Q3/70

CPC classification number: H04M1/56 ,  H04L25/0202 ,  H04M3/2281 ,  H04M3/493 ,  H04M7/1295 ,  H04Q1/45 ,  H04Q3/70 ,  G10L25/51 ,  H04M2201/18 ,  H04M2203/60 ,  H04Q2213/13139 ,  H04Q2213/13405 ,  H04Q2213/13515

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

公开(公告)号：US12015731B2

公开(公告)日：2024-06-18

申请号：US17857618

申请日：2022-07-05

Applicant: Pindrop Security, Inc.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04M1/56 ,  H04L25/02 ,  H04M3/22 ,  H04M3/493 ,  H04M7/12 ,  H04M15/06 ,  H04Q1/45 ,  H04Q3/70 ,  G10L25/51

CPC classification number: H04M1/56 ,  H04L25/0202 ,  H04M3/2281 ,  H04M3/493 ,  H04M7/1295 ,  H04Q1/45 ,  H04Q3/70 ,  G10L25/51 ,  H04M2201/18 ,  H04M2203/60 ,  H04Q2213/13139 ,  H04Q2213/13405 ,  H04Q2213/13515

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.

公开(公告)号：US11388490B2

公开(公告)日：2022-07-12

申请号：US17157848

申请日：2021-01-25

Applicant: PINDROP SECURITY, INC.

Inventor： Nick Gaubitch ,  Scott Strong ,  John Cornwell ,  Hassan Kingravi ,  David Dewey

IPC: H04M1/56 ,  H04M15/06 ,  H04Q3/70 ,  H04M3/22 ,  H04M7/12 ,  H04Q1/45 ,  G10L25/51 ,  H04L25/02 ,  H04M3/493

Abstract: Systems, methods, and computer-readable media for call classification and for training a model for call classification, an example method comprising: receiving DTMF information from a plurality of calls; determining, for each of the calls, a feature vector including statistics based on DTMF information such as DTMF residual signal comprising channel noise and additive noise; training a model for classification; comparing a new call feature vector to the model; predicting a device type and geographic location based on the comparison of the new call feature vector to the model; classifying the call as spoofed or genuine; and authenticating a call or altering an IVR call flow.