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    DEEPFAKE DETECTION
    32.
    发明公开
    DEEPFAKE DETECTION 审中-公开

    公开(公告)号：US20240355334A1

    公开(公告)日：2024-10-24

    申请号：US18388457

    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: G10L17/06

    CPC classification number: G10L17/06

    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.

    Telecommunications validation system and method
    33.
    发明授权
    Telecommunications validation system and method 有权

    公开(公告)号：US12120263B2

    公开(公告)日：2024-10-15

    申请号：US18123463

    申请日：2023-03-20

    Applicant: Pindrop Security, Inc.

    Inventor： MohammedAli Merchant ,  Matthew Williams ,  Tim Prugar

    IPC: H04M3/22 ,  H04M3/42

    CPC classification number: H04M3/2281 ,  H04M3/42059 ,  H04M3/42306 ,  H04M2203/6045

    Abstract: According to an embodiment of the disclosure, a toll-free telecommunications validation system determines a confidence value that an incoming phone call to an enterprises' toll-free number is originating from the station it purports to be, i.e., is not a spoofed call by incorporating one or more layers of signals and data in determining said confidence value, the data and signals including, but not limited to, toll-free call routing logs, service control point (SCP) signals and data, service data point (SDP) signals and data, dialed number information service (DNIS) signals and data, automatic number identification (ANI) signals and data, session initiation protocol (SIP) signals and data, carrier identification code (CIC) signals and data, location routing number (LRN) signals and data, jurisdiction information parameter (JIP) signals and data, charge number (CN) signals and data, billing number (BN) signals and data, and originating carrier information (such as information derived from the ANI, including, but not limited to, alternative service provider ID (ALTSPID), service provider ID (SPID), or operating company number (OCN)). In certain configurations said enterprise provides an ANI and DNIS associated with said incoming toll-free call, which is used to query a commercial toll-free telecommunications routing platform for any corresponding log entries. The existence of any such log entries, along with the originating carrier information in the event log entries do exist, is used to determine a confidence value that said incoming toll-free call is originating from the station it purports to be. As a result, said entities or enterprises operating a toll-free number may be provided a confidence value regarding an incoming telephone call, and using that confidence value, further determine whether or not to accept the authenticity of the incoming telephone call and/or based on said confidence value, service the incoming call differently.

    Robust spoofing detection system using deep residual neural networks
    36.
    发明授权
    Robust spoofing detection system using deep residual neural networks 有权

    公开(公告)号：US11862177B2

    公开(公告)日：2024-01-02

    申请号：US17155851

    申请日：2021-01-22

    Applicant: PINDROP SECURITY, INC.

    Inventor： Tianxiang Chen ,  Elie Khoury

    IPC: G10L17/18 ,  G10L17/02 ,  G10L17/22 ,  G10L17/04 ,  G10L17/08

    CPC classification number: G10L17/18 ,  G10L17/02 ,  G10L17/04 ,  G10L17/08 ,  G10L17/22

    Abstract: Embodiments described herein provide for systems and methods for implementing a neural network architecture for spoof detection in audio signals. The neural network architecture contains a layers defining embedding extractors that extract embeddings from input audio signals. Spoofprint embeddings are generated for particular system enrollees to detect attempts to spoof the enrollee's voice. Optionally, voiceprint embeddings are generated for the system enrollees to recognize the enrollee's voice. The voiceprints are extracted using features related to the enrollee's voice. The spoofprints are extracted using features related to features of how the enrollee speaks and other artifacts. The spoofprints facilitate detection of efforts to fool voice biometrics using synthesized speech (e.g., deepfakes) that spoof and emulate the enrollee's voice.

    AUTHENTICATION USING DTMF TONES
    38.
    发明公开
    AUTHENTICATION USING DTMF TONES 审中-公开

    公开(公告)号：US20230283711A1

    公开(公告)日：2023-09-07

    申请号：US18317799

    申请日：2023-05-15

    Applicant: PINDROP SECURITY, INC.

    Inventor： Payas GUPTA

    IPC: H04M3/38 ,  H04M3/51 ,  H04L9/40

    CPC classification number: H04M3/382 ,  H04M3/5166 ,  H04L63/0838 ,  H04L63/18 ,  H04M2203/6072 ,  H04M3/42008

    Abstract: A method of obtaining and automatically providing secure authentication information includes registering a client device over a data line, storing information and a changeable value for authentication in subsequent telephone-only transactions. In the subsequent transactions, a telephone call placed from the client device to an interactive voice response server is intercepted and modified to include dialing of a delay and at least a passcode, the passcode being based on the unique information and the changeable value, where the changeable value is updated for every call session. The interactive voice response server forwards the passcode and a client device identifier to an authentication function, which compares the received passcode to plural passcodes generated based on information and iterations of a value stored in correspondence with the client device identifier. Authentication is confirmed when a generated passcode matches the passcode from the client device.

    Channel-compensated low-level features for speaker recognition
    39.
    发明授权
    Channel-compensated low-level features for speaker recognition 有权

    公开(公告)号：US11657823B2

    公开(公告)日：2023-05-23

    申请号：US17107496

    申请日：2020-11-30

    Applicant: PINDROP SECURITY, INC.

    Inventor： Elie Khoury ,  Matthew Garland

    IPC: G10L17/20 ,  G10L17/02 ,  G10L17/04 ,  G10L17/18 ,  G10L19/028

    CPC classification number: G10L17/20 ,  G10L17/02 ,  G10L17/04 ,  G10L17/18 ,  G10L19/028

    Abstract: A system for generating channel-compensated features of a speech signal includes a channel noise simulator that degrades the speech signal, a feed forward convolutional neural network (CNN) that generates channel-compensated features of the degraded speech signal, and a loss function that computes a difference between the channel-compensated features and handcrafted features for the same raw speech signal. Each loss result may be used to update connection weights of the CNN until a predetermined threshold loss is satisfied, and the CNN may be used as a front-end for a deep neural network (DNN) for speaker recognition/verification. The DNN may include convolutional layers, a bottleneck features layer, multiple fully-connected layers and an output layer. The bottleneck features may be used to update connection weights of the convolutional layers, and dropout may be applied to the convolutional layers.

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