Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is in response to the amendment filed on 4/14/2026. Claims 1-11, 13, 16-32, 36-37, and 51 are currently pending in the filing of 4/14/2026 which included cancellation of claims 12, 14-15, 33-35, and 38-50 and added new independent claim 51. Claims 1-50 were pending in the previous filing of 05/24/2024.
Information Disclosure Statements
The information disclosure statement(s) (IDS) submitted on 4/14/2026 and 6/17/2026 have been considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) have been considered by the examiner.
Response to Applicant’s Amendments / Arguments Regarding 35 U.S.C. § 103
The applicant’s remarks, on pages 9-26 of the response / amendment, the applicant argues the features which allegedly distinguish over the previously cited references cited in the 35 U.S.C. § 103 rejections.
Applicant’s arguments have been considered but are moot in view of the new ground(s) of rejection.
Previous Statutory Double Patenting Rejections
Due to the amendments to independent claim 1 and the cancellation of independent claim 38, the previous Statutory Double Patenting rejection has been withdrawn.
Previous Non-Statutory Double Patenting Rejections
Due to the amendments to independent claims 1, 29, and 36, the previous Non-Statutory Double Patenting rejection has been withdrawn.
Previous Claim Objections
The previous objections to claims 25 and 49 are withdrawn due to the amendments to claim 25 and the cancelation of claim 49.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 6-7, 11, 17, 24, 26, 29, and 36 are rejected under 35 U.S.C. 103 as being unpatentable over US 20110214171 to Wolfond et al. (hereinafter Wolfond), in view of US 20100242106 to Harris et al. (hereinafter Harris), in view of US 20230177495 to Duffy et al. (hereinafter Duffy).
Regarding claim 1, Wolfond teaches,
A system for authentication, comprising: (Title, teaches multimode credential authentication.)
a validation system; (Abstract & fig. 7, teach authentication by scoring / ranking first and second credentials.)
an agent configured to communicate a first credential indicating an identification to the validation system and communicate a second credential indicating the identification to a verification service, (fig. 7 and [0088-90] teach the identity scoring facility 400 receiving credentials from the agent. Fig. 7, 700-722 teach the first and second credentials discussed in detail below regarding [0089-98]. See also Abstract, teaching the first and second credentials being used for authentication by scoring the credentials. [0035] teaches distinct servers for credentials, sample acquisition, and identity scoring, discussed in detail in the rejection of claim 26 below. Additionally, fig. 1 & [0032] teach identity scoring separate from a financial facility / third party.) (Harris, further discussed below, also teaches client agents 120 in figs. 1D & 2B providing information for vServer 275 which authenticates, also discussed below in rejection of claim 26.)
… wherein the validation system includes:
a database configured to store authorized user data; and (fig. 1, credential reference records 202, see also fig. 7, 710)
a portal configured to provide selection of the verification service (fig. 7, 716, teaches selecting the second channel. [0033] teaches identity system working web site or other secure database on network/internet. ) wherein the validation system is configured to compare the first credential to the authorized user data, determine a confidence level of validity of the identification based on the comparison of the first credential to the authorized user data, (fig. 7, 700-708 at [0089-92] teaching receiving non-biometric credential and scoring / “confidence level”. Also, fig. 7, 710-716 at [0093-98] teaches first biometric credential being received and scored. ) receive a verification of the second credential from the verification service, (fig. 7, 718-720 in [0105-106] teaches scoring the second biometric credential.) and modify the confidence level based on the verification. (fig. 7, 722 in [0107] teaches ultimate identity score based on the scoring of the first and second credentials.)
Wolfond fails to explicitly teach selecting verification service from a plurality of verification services,
However, Harris teaches,
a portal configured to provide selection of the verification service from a plurality of verification services, …. ([0013] teaches based on a policy, selecting an authentication virtual server of the plurality of authentication virtual servers to authenticate the client. See also, fig. 2B showing plurality of vServers 275a-n, which are the selectable plurality of servers.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond with the added ability to select from a plurality of verification / authentication servers when an authentication server is down or based on a policy, as taught by Harris, for the purpose of increasing efficiency by providing multiple options of authentication servers to prevent failure in the ability to authenticate, and thus, increasing efficiency while maintaining security, and/or based on a policy, selecting an authentication server, and thus, increasing security.
Wolfond and Harris fail to explicitly teach using machine learning weights of credentials to determine scores,
However, Duffy teaches,
at least one machine learning model trained to generate the confidence level based on the first credential and the second credential and configured to adjust a function for determining the confidence level by adjusting a relative functional weight of at least one of the first credential and the second credential, ([0006-7] teach machine learning using weights to score identity credentials. See also Abstract & fig. 7b.)
wherein the validation system is configured to determine a reliability score for the verification service based on the weight for the second credential ([0006-7] teach score based on weights.) and present, at the portal, an indication of the reliability score. (Fig. 7b showing scores by issuer \ “verification service”.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond and Harris with the added ability to use machine learning to score identity credentials, as taught by Duffy, for the purpose of increasing security by determining the score of different identity credentials.
Regarding claim 2, Wolfond, Harris, and Duffy teach,
The system of claim 1, further comprising:
at least one application programming interface (API) communicatively coupling the verification service with the agent and the validation system. (Harris, [0067] teaches using an API when performing monitoring an agent using an API. See also, at least, [0103] & [0124].)
Regarding claim 3, Wolfond, Harris, and Duffy teach,
The system of claim 2, wherein the at least one API includes a first API at the validation system and a second API installed on a machine on which the agent is running. (fig. 2b & [0041] teaches appliance 200 which is an interface, that performs communications between client agents 120 and servers 106. [0067] teaches monitoring agent 197 of appliance 200 including API. fig. 3, teaches the 120 client agent, where [0124] teaches an API of the client agent 120.)
Regarding claim 6, Wolfond, Harris, and Duffy teach,
The system of claim 1, wherein the verification service interfaces with the agent via a web service. (Harris, in at least [0061] teaches the applications using protocols such as HTTP, which is a web service.)
Regarding claim 7, Wolfond, Harris, and Duffy teach,
The system of claim 1, wherein the verification service includes endpoint service and detection. (Harris, [0045] teaches that client 102 may be client nodes or endpoints. [0064] teaches the appliance 200 having monitoring agent 197 performing collection of data upon detection of any user data from any user input.)
Regarding claim 11, Wolfond, Harris, and Duffy teach,
The system of claim 1, further comprising:
a user device on which the agent runs, wherein the first credential includes data representative of an identity of the user device, the data including at least one of location information, voice information, and video information. (Wolfond, [0090] teaches authentication using a first non-biometric credential that is an address / “location information”.)
Regarding claim 17, Wolfond, Harris, and Duffy teach,
The system of claim 1, wherein the second credential includes biometric data of a user of the agent. (Wolfond, fig. 7, 718-720 in [0105-106] teaches scoring the second biometric credential.)
Regarding claim 24, Wolfond, Harris, and Duffy teach,
The system of claim 11, wherein the data includes at least one of a textual confirmation via an instant messaging application running on the user device and data from a web application running on the user device. (Wolfond, [0085] teaches the displaying a notification message.) (Harris, [0006] also teaches the client being informed that the authentication is successful by being granted access.)
Regarding claim 26, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the verification service is a third-party service separate from the validation system. (Wolfond, [0035] teaches distinct servers for credentials, sample acquisition, and identity scoring.) (Harris, fig. 2b & [0008] teaches that vServer 275 of appliance 200 performs authentication. [0134] teaches that client 102 / client agent 120 provide information, including identity information, for access / authentication, to the appliance 200, which includes vServer 275.)
Regarding claim 29, Wolfond, Harris, and Duffy teach,
The method for authentication, comprising:
selecting, via a portal of a validation system, a verification service from a plurality of verification services separate from the validation system;
receiving, at the validation system, a first credential from an agent indicating an identification;
comparing the first credential to authorized user data stored in an authorized user database;
determining a confidence level of validity of the identification based on the comparison of the first credential to the authorized user data;
communicating to the verification service a second credential from the agent indicating the identification;
receiving, via the verification service, verification of the second credential;
modifying the confidence level based on the verification.
adjusting a function for determining the confidence level by adjusting a relative functional weight of the first credential and the second credential;
determining a reliability score for the verification service based on the weight for the second credential;
presenting, at the portal, an indication of the reliability score; and
The above features of claim 29 are rejected using the same basis of arguments used to reject claim 1 above.
recommending, via the validation system, an alternative verification service of the plurality of verification services based on the reliability score. (Duffy, fig. 7B showing users issuers \ “verification services” and associated credentials which are scored. [0048] teaches coaching users to choose some credentials.) (Harris, [0013] teaches based on a policy, selecting an authentication virtual server of the plurality of authentication virtual servers to authenticate the client. See also, fig. 2B showing plurality of vServers 275a-n, which are the selectable plurality of servers.)
Regarding claim 36, Wolfond, Harris, and Duffy teach,
A method for authentication, comprising:
selecting a verification service from a plurality of verification services;
receiving, at a validation system, a first credential from an agent indicating an identification;
comparing the first credential to authorized user data;
determining a confidence level of validity of the identification based on the comparison of the first credential to the authorized user data;
communicating to the verification service a second credential indicating the identification;
receiving a verification of the second credential from the verification service;
modifying the confidence level based on the validation.
adjusting a function for determining the confidence level by adjusting a relative functional weight of the first credential and the second credential;
determining a reliability score for the verification service based on the weight for the second credential;
presenting, at a portal, an indication of the reliability score; and
Claim 36 is rejected using the same basis of arguments used to reject claim 1 above.
recommending, via the validation system, an alternative verification service of the plurality of verification services based on the reliability score. (Duffy, fig. 7B showing users issuers \ “verification services” and associated credentials which are scored. [0048] teaches coaching users to choose some credentials.) (Harris, [0013] teaches based on a policy, selecting an authentication virtual server of the plurality of authentication virtual servers to authenticate the client. See also, fig. 2B showing plurality of vServers 275a-n, which are the selectable plurality of servers.)
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20150334098 to Keys et al. (hereinafter Keys).
Regarding claim 4, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the verification service interfaces with the agent (As discussed above in the rejection of claim 1, both Wolfond and Harris teach interfacing between verification / authentication system and agent using interfaces.)
Wolfond, Harris, and Duffy fail to explicitly teach using an SDK when interfacing between an agent and verification / authentication services,
However, Keys teaches,
wherein the verification service interfaces with the agent via a software development kit (SDK). ([0074] teaches an agent, authentication hub, and SDK. In detail, [0089] teaches the client side SDK being used by client to submit device attributes based on an authentication request by system 100.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Keys, which also teaches a level of authentication (Abstract), and additionally teaches using an SDK when interfacing between an agent and verification / authentication services ([0089]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to utilize an SDK to provide device attributes during a verification / authentication, as taught by Keys, for the purpose of increasing security by utilizing additional information, such as device attributes, during authentication / verification.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20220253511 to Popa et al. (hereinafter Popa).
Regarding claim 5, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the verification service interfaces with the agent via a (Harris, [0124] & [0126] teaches the use of hooks.)
Wolfond, Harris, and Duffy fail to explicitly teach the use of a webhook in interfacing,
However, Popa teaches,
wherein the verification service interfaces with the agent via a webhook. ([0066] teaches communications between verification server 103 and client occurring using webhooks.) (as discussed above in the rejection of claim 1, both Wolfond and Harris teach the client including an agent.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Popa, which also teaches two factor authentication (Abstract) and the use of biometrics ([0023]), and additionally teaches using webhooks for communications between clients and verification servers ([0066]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to use webhooks when interfacing between verification services and a client / agent, as taught by Popa, for the purpose of increasing computational efficiency by using webhooks to enable real-time, event-driven communication between applications, to avoid constant checking / polling, while maintaining security.
Claims 8 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20210314331 to Singh (hereinafter Singh).
Regarding claim 8, Wolfond, Harris, and Duffy teach,
The system of claim 1,
Wolfond, Harris, and Duffy fail to explicitly teach a virtual marketplace that provides multiple verification services,
However, Singh teaches,
wherein the plurality of verification services is presented via a virtual marketplace via the portal. ([0012] teaches an online marketplace that provides identity verification data services which may be provided by different bureaus / verification services.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Singh, which also teaches identity verification (Abstract), and additionally teaches an online marketplace that provides different verification services ([0012]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to have a marketplace provide multiple options for identity verification, as taught by Singh, for the purpose of increasing security by providing verification using different verification services that have access to different verification data.
Regarding claim 30, Wolfond, Harris, Duffy, and Singh teach,
The method of claim 29, further comprising:
presenting, at the portal, the plurality of verification services via a virtual marketplace.
Claim 30 is rejected using the same basis of arguments used to reject claim 8 above.
Claims 9, 31, and 37 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20230396428 to Gunn et al. (hereinafter Gunn).
Regarding claim 9, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the validation system is configured to determine a . (Wolfond, Abstract teaches scoring credentials.)
Wolfond, Harris, and Duffy fail to explicitly teach using scoring / confidence level to determine a deepfake condition,
However, Gunn teaches,
wherein the validation system is configured to determine a deepfake condition in response to the confidence level. ([0058] teaches using scoring to determine a deepfake.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Gunn, which also teaches authentication (Abstract), using biometrics including heart rhythms ([0061-62]) and scoring ([0058]), and additionally teaches using scoring to determine if data is a deepfake ([0058]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to determine if information is a deepfake, as taught by Gunn, for the purpose of increasing security by detecting a more recent method / deepfake of providing false data..
Regarding claim 31, Wolfond, Harris, Duffy, and Gunn teach,
The method of claim 29, further comprising:
determining a deepfake condition in response to the confidence level.
Claim 31 is rejected using the same basis of arguments used to reject claim 9 above.
Regarding claim 37, Wolfond, Harris, Duffy, and Gunn teach,
The method of claim 36, further comprising:
determining a deepfake condition in response to the confidence level.
Claim 37 is rejected using the same basis of arguments used to reject claim 9 above.
Claim 10 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20200406859 to Hassani (hereinafter Hassani).
Regarding claim 10, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the authorized user data (Wolfond, fig. 1, credential reference records 202, see also fig. 7, 710, such as the first and second biometric credentials of fig. 7.)
Wolfond, Harris, and Duffy fail to explicitly teach the user data / biometrics being stored in an immutable storage / blockchain,
However, Hassani teaches,
wherein the authorized user data includes immutable data stored on the database. ([0035] teaches storing user biometric data on a blockchain, which is understood to be immutable. [0044] teaches that the biometric is a token. Abstract, teaches authentication using blockchains and tokens.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Hassani, which also teaches authentication using tokens (Abstract) where the tokens may be biometrics of a user ([0044]), and additionally teaches storing biometrics of a user on a blockchain ([0035]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to maintain user authentication data / biometrics on an immutable storage / blockchain, as taught by Hassani, for the purpose of increasing security by maintain user biometrics that are used for authentication on an immutable data source that is extremely difficult hack, so that authentication data cannot be changed by a hacker.
Claims 13, 16, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20240248971 to Rao et al. (hereinafter Rao).
Regarding claim 13, Wolfond, Harris, and Duffy teach,
The system of claim 1, further comprising:
Wolfond and Harris fail to explicitly teach using machine learning for verification,
However, Rao teaches,
an artificial intelligence engine that trains the machine learning model using the first credential and the verification. (Rao, [0109] teaches using supervisor / artificial neural networks to train or fitting of the parameters of the machine learning (ML) model. See also previous claim 12 rejection, fig. 2 & [0050-51] teach a same score model that performs biometric evaluation. [0051] last sentence teaches that different biometrics may be used. [0022] teaches two factor authentication / first and second credentials)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Rao, which also teaches identifying a user based on behavioral biometrics (Abstract), and additionally teaches using machine learning models ([0047]) including score models 210 that use biometric evaluation ([0050-51]) where the model improves its biometric scoring ability ([0056]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to utilize machine learning in biometric authentication, as taught by Rao, for the purpose of increasing security by training models to improve biometric evaluations and improve biometric scoring.
Regarding claim 16, Wolfond, Harris, and Duffy teach,
The system of claim 1,
Wolfond, Harris, and Duffy fail to explicitly teach using alternative verification,
However, Rao teaches,
wherein the validation system is configured to recommend an alternative verification service of the plurality of verification services based on the reliability score. (Rao, fig. 2 and [0059-60] teach additional security measures 214 needing to be performed when the threshold at 212 is not high enough. See also previous claim 12 rejection, fig. 2 & [0050-51] teach a same score model that performs biometric evaluation. [0051] last sentence teaches that different biometrics may be used. [0022] teaches two factor authentication / first and second credentials)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Rao, which also teaches identifying a user based on behavioral biometrics (Abstract), and additionally teaches using machine learning models ([0047]) including score models 210 that use biometric evaluation ([0050-51]) where the model improves its biometric scoring ability ([0056]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to utilize machine learning in biometric authentication, as taught by Rao, for the purpose of increasing security by training models to improve biometric evaluations and improve biometric scoring.
Regarding claim 32, Wolfond, Harris, and Duffy teach,
The method of claim 29, further comprising:
Wolfond, Harris, and Duffy fail to explicitly teach using alternative verification,
However, Rao teaches,
training, via an artificial intelligence engine, at least one machine learning model to generate the confidence level based on the first credential and the second credential. ([0109] teaches using supervisor / artificial neural networks to train or fitting of the parameters of the machine learning (ML) model. See also the first Office action’s rejection of claims 12 and 13. See also previous claim 12 rejection, fig. 2 & [0050-51] teach a same score model that performs biometric evaluation. [0051] last sentence teaches that different biometrics may be used. [0022] teaches two factor authentication / first and second credentials)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Rao, which also teaches identifying a user based on behavioral biometrics (Abstract), and additionally teaches using machine learning models ([0047]) including score models 210 that use biometric evaluation ([0050-51]) where the model improves its biometric scoring ability ([0056]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to utilize machine learning in biometric authentication, as taught by Rao, for the purpose of increasing security by training models to improve biometric evaluations and improve biometric scoring.
Claims 18-21 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20140188770 to Agrafioti et al. (hereinafter Agrafioti).
Regarding claim 18, Wolfond, Harris, and Duffy teach,
The system of claim 17,
wherein the biometric data includes at least one of a (Wolfond, [0046] teaches biometric sensing / authentication including fingerprints and voice sampling.)
Wolfond, Harris, and Duffy fail to explicitly teach the use of electrocardiograms as the biometric authentication,
However, Agrafioti teaches,
wherein the biometric data includes at least one of a heartrate and an electrocardiogram, and wherein the verification service includes a heartrate monitoring system for the user. (Abstract, teaches biometric authentication, and [0004] teaches using electrocardiograms (ECG) as the biometric to identify the user. See also figs. 2-3 showing the ECG, which includes the rate of the heart. [0011] teaches temporal characteristics of heart beats.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Agrafioti, which also teaches authentication using biometrics in combination with machine learning (Abstract), and additionally teaches the use of biometrics that include electrocardiograms ([0004]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to use machine learning to perform the biometric authentication including the use of electrocardiograms, as taught by Agrafioti, for the purpose of increasing security by adding an additional biometric factor, electrocardiograms, for authentication.
Regarding claim 19, Wolfond, Harris, Duffy, and Agrafioti teach,
The system of claim 18, wherein the validation system includes at least one machine learning model trained to generate the confidence level based on the electrocardiogram of a user to whom the agent is registered. (Agrafioti, Abstract, teaches biometric authentication using machine learning, and [0004] teaches using electrocardiograms (ECG) as the biometric to identify the user. See also figs. 2-3 showing the ECG. See also [0063] teaching machine learning and ECG pattern recognition.)
Regarding claim 20, Wolfond, Harris, Duffy, and Agrafioti teach,
The system of claim 19, wherein the heartrate monitoring system is configured to identify the user based on the electrocardiogram. (Agrafioti, Abstract, teaches biometric authentication using machine learning, and [0004] teaches using electrocardiograms (ECG) as the biometric to identify the user. See also at least [0063-64].)
Regarding claim 21, Wolfond, Harris, Duffy, and Agrafioti teach,
The system of claim 19, further comprising:
an artificial intelligence engine that trains the machine learning model using the electrocardiogram. (Agrafioti, [0122-123] teach LDA machine learning using ECG, and LDA learning technique / supervised learning that is trained. See also, [0188] teaching training using ECG.)
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of Agrafioti, in view of Rao.
Regarding claim 22, Wolfond, Harris, Duffy, and Agrafioti teach,
The system of claim 20,
wherein the machine learning model is configured to adjust a function for determining the confidence level . (Agrafioti, [0095-96] teaches an ECG and score level. [0121] teaches comparing to a threshold.)
Wolfond, Harris, and Duffy and Agrafioti fail to explicitly teach adjusting weights of the model based on biometrics,
However, Rao teaches,
wherein the machine learning model is configured to adjust a function for determining the confidence level by adjusting a relative functional weight of at least one of the first credential and the . (Rao, [0056] teaches adjusting the weights of the models to improve scoring of the biometrics. Both the device fingerprint model 204 / first credential and the same user score model 210 of fig. 2 may be adjusted.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Agrafioti, which also teaches authentication using biometrics in combination with machine learning (Abstract), and additionally teaches the use of biometrics that include electrocardiograms ([0004]), with Rao, which also teaches identifying a user based on behavioral biometrics (Abstract), and additionally teaches using machine learning models ([0047]) including score models 210 that use biometric evaluation ([0050-51]) where the model improves its biometric scoring ability by adjusting weights ([0056]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, Duffy, and Agrafioti with the added ability to adjust weights in machine learning in biometric authentication / identification to better train the machine learning, as taught by Rao, for the purpose of increasing security by training models and adjusting the weights of the models to improve biometric evaluations and improve biometric scoring.
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20230185423 to Wang et al. (hereinafter Wang).
Regarding claim 23, Wolfond, Harris, and Duffy teach,
The system of claim 11,
wherein the user device is configured to run . (Wolfond, [0085] teaches the displaying a notification message.) (Harris, [0006] also teaches the client being informed that the authentication is successful by being granted access.)
Wolfond, Harris, and Duffy fail to explicitly teach using conferencing or email to present the confidence level,
However, Wang teaches,
wherein the user device is configured to run a conferencing software or an email application that presents the confidence level. ([0032] teaches the server delivering an authentication result and rank which grants a user access to different levels of access in the conferencing screen.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Wang, which also teaches authentication (Abstract) including biometric authentication ([0005]), and additionally teaches the server delivering an authentication result and rank which grants a user access to different levels of access in the conferencing screen ([0032]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to provide authentication results including confidence / rank using a conferencing software, as taught by Wang, for the purpose of increasing security by restricting users based on the confidence / ranking of the authentication result.
Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20230082094 to Keret et al. (hereinafter Keret).
Regarding claim 25, Wolfond, Harris, and Duffy teach,
The system of claim 11,
Wolfond, Harris, and Duffy fail to explicitly teach authenticating using a voice provided over VOIP or PSTN,
However, Keret teaches,
wherein the voice information is provided via at least one of Voice over Internet Protocol and Public Switched Telephone Network. ([0004] teaches “During voice communications, such as communications over a publicly switched telephone network (PSTN), cellular network, voice over IP (VoIP), voice over LTE (VoLTE), and/or voice communications over data networks, voice biometric authentication and fraud detection may be done.”)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Keret, which also teaches biometric / voice print fraud prevention / authentication (Abstract), and additionally teaches using voice provided over VOIP and/or PSTN to authenticate a user ([0004]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to provide voice authentication while using VOIP and/or PSTN, as taught by Keret, for the purpose of increasing computational efficiency.
Claim 27 is rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of US 20190020480 to Camenisch et al. (hereinafter Camenisch).
Regarding claim 27, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the validation system provides certificate . (Harris, [0169] teaches supporting certificate based authentication, and fig. 2b teaches an appliance 200 with vServer 275 that performs authentication.)
Wolfond, Harris, and Duffy fail to explicitly teach certificate transparency / logging of certificates for auditing,
However, Camenisch teaches,
wherein the validation system provides certificate transparency. ([0053] teaches an authentication system with a tamper proof log for auditing that has a Certificate Transparency type architecture. [0058] teaches usage of digital signatures, which is related to claim 28 below.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Camenisch, which also teaches an authentication system (Title), and additionally teaches an authentication system with a tamper proof log for auditing that has a Certificate Transparency type architecture ([0053]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to use a certificate transparency to log authentication events, and potentially revoke certificates (Abstract), as taught by Camenisch, for the purpose of increasing security by maintaining a log for auditing.
Claims 28 are rejected under 35 U.S.C. 103 as being unpatentable over Wolfond, in view of Harris, in view of Duffy, in view of Camenisch, in view of US 20220067814 to Goncalves et al. (hereinafter Goncalves).
Regarding claim 28, Wolfond, Harris, and Duffy teach,
The system of claim 1,
wherein the validation system employs . (Harris, [0169] teaches certificate based authentication, which uses signatures for verification / authentication.)
Wolfond, Harris, and Duffy fail to explicitly teach the use of a claimant model, which involves logging and verifying important events,
However, Camenisch teaches,
wherein the validation system employs a . (In the art of computer networking a claimant model is a formal framework for logging and verifying important events.) ([0053] teaches an authentication system with a tamper proof log for auditing that has a Certificate Transparency type architecture. [0058] teaches usage of digital signatures. See also rejection of claim 27 above.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Camenisch, which also teaches an authentication system (Title), and additionally teaches an authentication system with a tamper proof log for auditing that has a Certificate Transparency type architecture ([0053]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, and Duffy with the added ability to use a certificate transparency to log authentication events, and potentially revoke certificates (Abstract), as taught by Camenisch, for the purpose of increasing security by maintaining a log for auditing.
Wolfond, Harris, Duffy and Camenisch fail to explicitly teach “claimant model”,
However, Goncalves teaches,
wherein the validation system employs a claimant model for verifying . ([0100-101] teach a claimant model and authentication to find a claimant. [0072] also teaches authentication.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Wolfond, which teaches authenticating a user based on at least a first and second credential, both of which are scored, to obtain in ultimate score (Abstract and fig. 7), with Harris, which also teaches authentication using credentials ([0007]), and additionally teaches select an authentication virtual server of the plurality of authentication virtual servers to authenticate the client ([0013]), and the use of agents and APIs ([0067]), with Duffy, which also teaches weighting of identity credentials (Abstract & [0006-7]), and additionally teaches using machine learning to perform the scoring based on the weights (fig. 7b & [0006-7]), with Camenisch, which also teaches an authentication system (Title), and additionally teaches an authentication system with a tamper proof log for auditing that has a Certificate Transparency type architecture ([0053]), with Goncalves, which also teaches authentication ([0072]), and additionally teaches use of a claimant model and authentication ([0100-101]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Wolfond, Harris, Duffy and Camenisch with the added ability to use a claimant model to find a claimant, as taught by Goncalves, for the purpose of increasing efficiency in finding claimants while maintain security by using authentication.
Claim 51 is rejected under 35 U.S.C. 103 as being unpatentable over US 20210194872 to Chang et al. (hereinafter Chang), in view of Duffy, in view of US 20220417250 to Zhang et al. (hereinafter Zhang).
Regarding claim 51, Chang teaches,
A system for authentication of a live video communication, comprising: (Abstract)
a validation system; and (Fig. 1, verification system 100.)
an (Abstract & Fig. 5 described in [0048-49] performing verification of video conference.)
a database configured to store authorized user data; and (fig. 1, database 120. [0025] teaches database 120 storing user / agent information for verification system 100.)
a portal configured ([0033] teaches verification service 100 may be implemented as services. [0002] teaches facilitating interactions with customers.)
wherein the validation system is configured to compare the first credential to the authorized user data, determine a confidence level of validity of the identification based on the comparison of the first credential to the authorized user data, (Figs. 4-5) (See also Duff, further discussed below, [0031])
receive a verification from the verification service that the video data is representative of the user, and modify the confidence level based on the verification. (Fig. 5 described in [0048-49] performing verification of video conference, [0051] teaching similarity metrics. See also at least fig. 4 description teaching thresholds and similarities used in comparisons.)
Chang fails to teach an agent that communicates credentials,
However, Duffy teaches,
an agent configured to communicate a first credential indicating an identification to the validation system … (Duff, [0031]teaches agent communicating credentials)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Chang, which teaches video conferencing verification (Abstract) by using the images in the video conferencing data to verify the user using similarity comparisons based on threshold (Figs. 4-5), with Duffy, which also teaches credential verification (Abstract), and additionally teaches using agents to communicate the credentials ([0031]). One of ordinary skill in the art would have been motivated to perform such an addition to provide Chang with the added ability to use an agent to communicate credentials, as taught by Duffy, for the purpose of increasing security by using a secure software agent to communicate credentials.
Chang and Duffy fail to teach selecting a verification service from a plurality of verification services,
However, Zhang teaches,
a portal configured to provide selection of the verification service from a plurality of verification services presented via a virtual marketplace, (Abstract & [0095] teaching a marketplace.)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Chang, which teaches video conferencing verification (Abstract) by using the images in the video conferencing data to verify the user using similarity comparisons based on threshold (Figs. 4-5), with Duffy, which also teaches credential verification (Abstract), and additionally teaches using agents to communicate the credentials ([0031]), with Zhang, which also teaches verification services (Abstract), and additionally teaches selecting a verification service from a plurality of verification services (Abstract). One of ordinary skill in the art would have been motivated to perform such an addition to provide Chang and Duffy with the added ability to select a verification from a plurality of verification services, as taught by Zhang, for the purpose of increasing security.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/B.W.A./
/JASON K GEE/Primary Examiner, Art Unit 2495
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