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公开(公告)号：US11646018B2
公开(公告)日：2023-05-09
申请号：US16829705
申请日：2020-03-25
Applicant: PINDROP SECURITY, INC.
Inventor： Vinay Maddali , David Looney , Kailash Patil
IPC: G10L15/197 , G10L15/18 , G10L15/02 , G10L15/04 , G10L15/06 , G10L15/22 , G10L25/84 , G10L25/21 , H04M3/51
CPC classification number: G10L15/197 , G10L15/02 , G10L15/04 , G10L15/063 , G10L15/1822 , G10L15/22 , G10L25/21 , G10L25/84 , H04M3/5183 , H04M2203/558
Abstract: Embodiments described herein provide for automatically classifying the types of devices that place calls to a call center. A call center system can detect whether an incoming call originated from voice assistant device using trained classification models received from a call analysis service. Embodiments described herein provide for methods and systems in which a computer executes machine learning algorithms that programmatically train (or otherwise generate) global or tailored classification models based on the various types of features of an audio signal and call data. A classification model is deployed to one or more call centers, where the model is used by call center computers executing classification processes for determining whether incoming telephone calls originated from a voice assistant device, such as Amazon Alexa® and Google Home®, or another type of device (e.g., cellular/mobile phone, landline phone, VoIP).
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公开(公告)号：US11632460B2
公开(公告)日：2023-04-18
申请号：US17201849
申请日：2021-03-15
Applicant: PINDROP SECURITY, INC.
Inventor： Ricardo Casal , Theo Walker , Kailash Patil , John Cornwell
Abstract: Embodiments described herein provide for performing a risk assessment using graph-derived features of a user interaction. A computer receives interaction information and infers information from the interaction based on information provided to the computer by a communication channel used in transmitting the interaction information. The computer may determine a claimed identity of the user associated with the user interaction. The computer may extract features from the inferred identity and claimed identity. The computer generates a graph representing the structural relationship between the communication channels and claimed identities associated with the inferred identity and claimed identity. The computer may extract additional features from the inferred identity and claimed identity using the graph. The computer may apply the features to a machine learning model to generate a risk score indicating the probability of a fraudulent interaction associated with the user interaction.
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公开(公告)号：US10692502B2
公开(公告)日：2020-06-23
申请号：US15910387
申请日：2018-03-02
Applicant: PINDROP SECURITY, INC.
Inventor： Elie Khoury , Parav Nagarsheth , Kailash Patil , Matthew Garland
Abstract: An automated speaker verification (ASV) system incorporates a first deep neural network to extract deep acoustic features, such as deep CQCC features, from a received voice sample. The deep acoustic features are processed by a second deep neural network that classifies the deep acoustic features according to a determined likelihood of including a spoofing condition. A binary classifier then classifies the voice sample as being genuine or spoofed.
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公开(公告)号：US10362172B2
公开(公告)日：2019-07-23
申请号：US15880287
申请日：2018-01-25
Applicant: PINDROP SECURITY, INC.
Inventor： Scott Strong , Kailash Patil , David Dewey , Raj Bandyopadhyay , Telvis Calhoun , Vijay Balasubramaniyan
Abstract: Systems and methods for call detail record (CDR) analysis to determine a risk score for a call and identify fraudulent activity and for fraud detection in Interactive Voice Response (IVR) systems. An example method may store information extracted from received calls. Queries of the stored information may be performed to select data using keys, wherein each key relates to one of the received calls, and wherein the queries are parallelized. The selected data may be transformed into feature vectors, wherein each feature vector relates to one of the received calls and includes a velocity feature and at least one of a behavior feature or a reputation feature. A risk score for the call may be generated during the call based on the feature vectors.
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公开(公告)号：US09883040B2
公开(公告)日：2018-01-30
申请号：US15294538
申请日：2016-10-14
Applicant: PINDROP SECURITY, INC.
Inventor： Scott Strong , Kailash Patil , David Dewey , Raj Bandyopadhyay , Telvis Calhoun , Vijay Balasubramaniyan
CPC classification number: H04M3/527 , G06F21/32 , G06F21/552 , G06N99/005 , H04M3/493 , H04M7/0078 , H04M15/41 , H04M2203/551 , H04M2203/6027 , H04W12/12
Abstract: Systems and methods for call detail record (CDR) analysis to determine a risk score for a call and identify fraudulent activity and for fraud detection in Interactive Voice Response (IVR) systems. An example method may store information extracted from received calls. Queries of the stored information may be performed to select data using keys, wherein each key relates to one of the received calls, and wherein the queries are parallelized. The selected data may be transformed into feature vectors, wherein each feature vector relates to one of the received calls and includes a velocity feature and at least one of a behavior feature or a reputation feature. A risk score for the call may be generated during the call based on the feature vectors.
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Patent Agency Ranking
公开(公告)号：US20240363099A1
公开(公告)日：2024-10-31
申请号：US18388466
申请日：2023-11-09
Applicant: PINDROP SECURITY, INC.
Inventor： Umair Altaf , Sai Pradeep Peri , Lakshay Phatela , Payas Gupta , Yitao Sun , Svetlana Afanaseva , Kailash Patil , Elie Khoury , Bradley Magnetta , Vijay Balasubramaniyan , Tianxiang Chen
Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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公开(公告)号：US20240355319A1
公开(公告)日：2024-10-24
申请号：US18388385
申请日：2023-11-09
Applicant: PINDROP SECURITY, INC.
Inventor： Umair Altaf , Sai Pradeep Peri , Lakshay Phatela , Payas Gupta , Yitao Sun , Svetlana Afanaseva , Kailash Patil , Elie Khoury , Bradley Magnetta , Vijay Balasubramaniyan , Tianxiang Chen
Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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公开(公告)号：US11870932B2
公开(公告)日：2024-01-09
申请号：US17706398
申请日：2022-03-28
Applicant: Pindrop Security, Inc.
Inventor： Akanksha , Terry Nelms, II , Kailash Patil , Chirag Tailor , Khaled Lakhdhar
CPC classification number: H04M3/42102 , G06N20/00 , H04M2203/556 , H04M2203/558
Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.
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公开(公告)号：US11019201B2
公开(公告)日：2021-05-25
申请号：US16784071
申请日：2020-02-06
Applicant: PINDROP SECURITY, INC.
Inventor： Akanksha , Terry Nelms, II , Kailash Patil , Chirag Tailor , Khaled Lakhdhar
Abstract: Embodiments described herein provide for detecting whether an Automatic Number Identification (ANI) associated with an incoming call is a gateway, according to rules-based models and machine learning models generated by the computer using call data stored in one or more databases.
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公开(公告)号：US20240355337A1
公开(公告)日：2024-10-24
申请号：US18388364
申请日：2023-11-09
Applicant: PINDROP SECURITY, INC.
Inventor： Umair Altaf , Sai Pradeep Peri , Lakshay Phatela , Payas Gupta , Yitao Sun , Svetlana Afanaseva , Kailash Patil , Elie Khoury , Bradley Magnetta , Vijay Balasubramaniyan , Tianxiang Chen
IPC: G10L17/24
CPC classification number: G10L17/24
Abstract: Disclosed are systems and methods including software processes executed by a server that detect audio-based synthetic speech (“deepfakes”) in a call conversation. The server applies an NLP engine to transcribe call audio and analyze the text for anomalous patterns to detect synthetic speech. Additionally or alternatively, the server executes a voice “liveness” detection system for detecting machine speech, such as synthetic speech or replayed speech. The system performs phrase repetition detection, background change detection, and passive voice liveness detection in call audio signals to detect liveness of a speech utterance. An automated model update module allows the liveness detection model to adapt to new types of presentation attacks, based on the human provided feedback.
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