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公开(公告)号：US12013963B2
公开(公告)日：2024-06-18
申请号：US17232577
申请日：2021-04-16
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
CPC分类号： G06F21/6245 , G06F21/554 , G06F21/602 , G06N20/00
摘要： Aspects of the disclosure relate to information masking. A user device may receive a request to access information that includes personal identifiable information (PII) and retrieve source data comprising the PII. The user device may mask, within the source data and based on a data management policy, the PII, resulting in masked information. The user device may display the masked information. The user device may receive a request to unmask the masked information and unmask the PII, resulting in unmasked PII. The user device may display the unmasked PII and send unmasking event information to a PII footprint modeling platform, which may cause the PII footprint modeling platform to: log the request to unmask the masked information in an unmasking event log, 2) apply a machine learning model to the unmasking event log to identify malicious events, and 3) trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US11522697B2
公开(公告)日：2022-12-06
申请号：US17232517
申请日：2021-04-16
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
摘要： Aspects of the disclosure relate to information masking. A computing platform may receive, from a user computing device, a request to access information that includes personal identifiable information (PII). The computing platform may retrieve source data comprising the PII and mask, within the source data and based on a data management policy, the PII. The computing platform may send the masked information in response to the request to access the information. The computing platform may receive a request to unmask the masked information and unmask the PII. The computing platform may log the request to unmask the masked information in an unmasking event log and send the unmasked PII in response to the request to unmask the masked information. The computing platform may apply a machine learning model to the unmasking event log to identify malicious events and trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US20230040441A1
公开(公告)日：2023-02-09
申请号：US17943276
申请日：2022-09-13
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
摘要： Aspects of the disclosure relate to information masking. A computing platform may receive, from a user computing device, a request to access information that includes personal identifiable information (PII). The computing platform may retrieve source data comprising the PII and mask, within the source data and based on a data management policy, the PII. The computing platform may send the masked information in response to the request to access the information. The computing platform may receive a request to unmask the masked information and unmask the PII. The computing platform may log the request to unmask the masked information in an unmasking event log and send the unmasked PII in response to the request to unmask the masked information. The computing platform may apply a machine learning model to the unmasking event log to identify malicious events and trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US20220166872A1
公开(公告)日：2022-05-26
申请号：US17101171
申请日：2020-11-23
发明人： Charlene L. Ramsue , Thomas G. Frost , Youshika C. Scott , George Albero , Brian H. Corr , Scott Nielsen
摘要： Aspects of the disclosure relate to voiceprint tracking and anomaly detection. A computing platform may detect voice information from a call management system. The computing platform may establish voiceprints for employees and clients of an enterprise. The computing platform may detect a call between an employee and a caller attempting to access a client account. The computing platform may identify a first voiceprint corresponding to the employee and a second voiceprint corresponding to the caller. The computing platform may compare the second voiceprint to a known voiceprint corresponding to the client. Based on the comparison of the second voiceprint to the known voiceprint, the computing platform may determine that the second voiceprint does not match the known voiceprint. The computing platform may identify that the second voiceprint corresponds to another employee of the enterprise, and may send a security notification indicating potential unauthorized account access to an enterprise computing device.
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公开(公告)号：US12120262B2
公开(公告)日：2024-10-15
申请号：US17954422
申请日：2022-09-28
发明人： George Albero , Youshika C. Scott , Brian H. Corr , Thomas G. Frost , Scott Nielsen , Charlene L. Ramsue
CPC分类号： H04M3/2281 , G10L17/04 , G10L17/06 , G10L25/90 , H04M3/42042 , H04M3/5175 , H04M3/5183 , H04M2201/41
摘要： Aspects of the disclosure relate to voiceprint tracking and anomaly detection. A computing platform may detect voice information from a call management system. The computing platform may establish voiceprints for employees and clients of an enterprise. The computing platform may detect a call between an employee and a caller attempting to access a client account. The computing platform may identify a first voiceprint corresponding to the employee and a second voiceprint corresponding to the caller. The computing platform may compare the second voiceprint to a known voiceprint corresponding to the client. Based on the comparison of the second voiceprint to the known voiceprint, the computing platform may determine that the second voiceprint does not match the known voiceprint. The computing platform may identify that the second voiceprint corresponds to another employee of the enterprise, and may send a security notification indicating potential unauthorized account access to an enterprise computing device.
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公开(公告)号：US20230016130A1
公开(公告)日：2023-01-19
申请号：US17954422
申请日：2022-09-28
发明人： George Albero , Youshika C. Scott , Brian H. Corr , Thomas G. Frost , Scott Nielsen , Charlene L. Ramsue
摘要： Aspects of the disclosure relate to voiceprint tracking and anomaly detection. A computing platform may detect voice information from a call management system. The computing platform may establish voiceprints for employees and clients of an enterprise. The computing platform may detect a call between an employee and a caller attempting to access a client account. The computing platform may identify a first voiceprint corresponding to the employee and a second voiceprint corresponding to the caller. The computing platform may compare the second voiceprint to a known voiceprint corresponding to the client. Based on the comparison of the second voiceprint to the known voiceprint, the computing platform may determine that the second voiceprint does not match the known voiceprint. The computing platform may identify that the second voiceprint corresponds to another employee of the enterprise, and may send a security notification indicating potential unauthorized account access to an enterprise computing device.
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公开(公告)号：US20220335155A1
公开(公告)日：2022-10-20
申请号：US17232577
申请日：2021-04-16
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
摘要： Aspects of the disclosure relate to information masking. A user device may receive a request to access information that includes personal identifiable information (PII) and retrieve source data comprising the PII. The user device may mask, within the source data and based on a data management policy, the PII, resulting in masked information. The user device may display the masked information. The user device may receive a request to unmask the masked information and unmask the PII, resulting in unmasked PII. The user device may display the unmasked PII and send unmasking event information to a PII footprint modeling platform, which may cause the PII footprint modeling platform to: log the request to unmask the masked information in an unmasking event log, 2) apply a machine learning model to the unmasking event log to identify malicious events, and 3) trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US20220337412A1
公开(公告)日：2022-10-20
申请号：US17232517
申请日：2021-04-16
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
摘要： Aspects of the disclosure relate to information masking. A computing platform may receive, from a user computing device, a request to access information that includes personal identifiable information (PII). The computing platform may retrieve source data comprising the PII and mask, within the source data and based on a data management policy, the PII. The computing platform may send the masked information in response to the request to access the information. The computing platform may receive a request to unmask the masked information and unmask the PII. The computing platform may log the request to unmask the masked information in an unmasking event log and send the unmasked PII in response to the request to unmask the masked information. The computing platform may apply a machine learning model to the unmasking event log to identify malicious events and trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US20240281563A1
公开(公告)日：2024-08-22
申请号：US18650200
申请日：2024-04-30
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
CPC分类号： G06F21/6245 , G06F21/554 , G06F21/602 , G06N20/00
摘要： Aspects of the disclosure relate to information masking. A user device may receive a request to access information that includes personal identifiable information (PII) and retrieve source data comprising the PII. The user device may mask, within the source data and based on a data management policy, the PII, resulting in masked information. The user device may display the masked information. The user device may receive a request to unmask the masked information and unmask the PII, resulting in unmasked PII. The user device may display the unmasked PII and send unmasking event information to a PII footprint modeling platform, which may cause the PIT footprint modeling platform to: log the request to unmask the masked information in an unmasking event log, 2) apply a machine learning model to the unmasking event log to identify malicious events, and 3) trigger remediation actions based on identification of the malicious events.
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公开(公告)号：US11888986B2
公开(公告)日：2024-01-30
申请号：US17943276
申请日：2022-09-13
发明人： Allison Zimmer , Brian H. Corr , Charlene L. Ramsue , Scott Nielsen , Thomas G. Frost , Youshika C. Scott
CPC分类号： H04L9/32 , G06N20/00 , H04L63/0428
摘要： Aspects of the disclosure relate to information masking. A computing platform may receive, from a user computing device, a request to access information that includes personal identifiable information (PII). The computing platform may retrieve source data comprising the PII and mask, within the source data and based on a data management policy, the PII. The computing platform may send the masked information in response to the request to access the information. The computing platform may receive a request to unmask the masked information and unmask the PII. The computing platform may log the request to unmask the masked information in an unmasking event log and send the unmasked PII in response to the request to unmask the masked information. The computing platform may apply a machine learning model to the unmasking event log to identify malicious events and trigger remediation actions based on identification of the malicious events.
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