DETAILED ACTION
This office action is in response to the application filed on 06/09/2026. Claim(s) 1-9 and 11-19 is/are pending and are examined. Claim(s) 10 and 20 are cancelled.
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 .
Response to Arguments
Applicant's arguments with respect to amended claim 1 and 11 have been fully considered but are moot in view of the new ground(s) of rejection.
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.
Claim(s) 1-5 and 11-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Witchey (US 12,462,246 B1), hereinafter Witchey in view of Zhang (US 2025/0165467 A1), hereinafter Zhang in further view of Dupont (US 12,164,664 B1), hereinafter Dupont.
Regarding Claim(s) 1 and 11 Witcheyt teaches:
A computer-implemented method executed by data processing hardware that causes the data processing hardware to perform operations comprising: (Witchey Col. 2 Ln. 54-59 teaches, The inventive subject matter provides apparatus, systems and methods in which private digital data may be accessed or otherwise managed via one or more digital access tokens (DATs) via which data owners retain control over their private data while also permitting others to access the data owner's private data. Col. 43 Ln. 1-15 teaches, Various aspects and functions described herein may be implemented as hardware, software executing on hardware, or a combination of hardware and software executing on one or more computer systems.)
receiving, by a data escrow system, (Witchey Col. 20 Ln. 25-30 teaches, the private data exchange server can operate as a data escrow service or server)
subset of data from the one
or more datasets that satisfies the access query; (Witchey Col. 9 Ln. 60-67 teaches, Server 120 can then refer to, if necessary, private database by forwarding request to database or by reformatting the request as a query that database can understand (e.g., SQL, DQLs, keywords, etc.) to see if request or at least a portion of request may be fulfilled. Col. 10 Ln. 14-20 teaches, For a request for such a large number of fields of interest, server could respond with a message indicating how much of the request may be serviced, say only 5000 fields are available of the 10000 fields requested.)
generating, by the data escrow service, a temporary access request on behalf of the user to the subset of data; and (Witchey Col. 9 Ln. 50-60 teaches, Requestor device can construct or otherwise provision request with the information outlining the task's field requirements (e.g., entity data, number of entities, time requirements, waveforms, vital signs, demographics, metadata, etc.). Request can be submitted through a client agent running on requestor device. Col. 11-12 Ln. 67 and 1-10 teaches, DAT data can include other types of data including access dimensions (e.g., time period of authorized access of an owner of DAT, number of authorized accesses of an owner of DAT), metadata, timestamps, version numbers, attributes of DAT, data describing the nature of DAT, time-to-live information, links to data sources (e.g., private database, entity, etc.))
providing, by the data escrow system, to the user device, a notification indicating status of the temporary access request, wherein the notification excludes the subset of data (Witchey Col. 9-10 Ln. 67 and 1-15 teaches, server can transmit a response back to requestor device, possibly outlining the extent of which it is able to service the cohort request. The response could comprise one or more messages regarding the request. For example, the response could comprise a SUCCESS message indicating the request can be serviced, an ACK message indicating the request has been received but not yet processed which could also include an estimated time to complete, a COMPLETE message indicating the request has been completed, a FAILED message indicating the request cannot be serviced, or other messages to ensure requestor device can properly handle the state of request.)
Witchey does not appear to explicitly teach but in related art:
an access query from a user device, an access query requesting access for a user associated with the user device access to one or more datasets of a plurality of datasets, the access query comprising natural language text describing information associated with the one or more datasets of the plurality of datasets; (Zhang ¶ 14 teaches, the LLM-based data query optimizer may be an LLM or may include an LLM. The LLM may parse and analyze the programming code, in a manner similar to accepting natural languages as an input and analyzing natural languages. The LLM may determine a set of queries for execution against the database system based on analyzing the programming code. As defined by the programming code, each of the queries may include operations associated with retrieving data from one or more data structures (e.g., a table, a container, etc.) in the database system, re-organizing the data retrieved from the database system in one or more new data structures, and/or processing data from one or more data structures in the database system.)
It would have been obvious to one with ordinary skill the art, prior to the applicant's earliest effective filing date, to combine the teachings of Witchey with Zhang, to modify the token based digital private data exchange system of Witchey with the dynamic querying of Zhang. The motivation to do so, Zhang ¶ 12, to improve the efficiency in executing data queries against the large-scaled datasets.
Witchey in view of Zhang does not appear to explicitly teach but in related art:
determining, by a large language model (LLM) executing within a trusted hardware execution environment, (Dupont Col. 24 Ln. 10-11 teaches, The LLM, which can be deployed in a variety of secure environments, including TEEs)
It would have been obvious to one with ordinary skill the art, prior to the applicant's earliest effective filing date, to combine the teachings of Witchey in view of Zhang with Dupont, to modify the token based digital private data exchange system of Witchey with the dynamic querying of Zhang with the LLM execution within a TEE of Dupont. The motivation to do so, Dupont Col. 11 Ln. 44-45, to protect and store data in a more efficient way than in known methods.
Regarding Claim(s) 2 and 12 Witchey-Zhang-Dupont teaches:
The method of claim 1, (Witchey-Zhang-Dupont teaches the parent claim above.) wherein the natural language text further describes a question posed by the user that requires data from the one or more datasets to answer. (Zhang ¶ 12 teaches, example, the program developers may generate
programming code for querying data against a database system (e.g., a distributed database system).)
The motive given in Claim 1 is equally applicable to the above claim.
Regarding Claim(s) 3 and 13 Witchey-Zhang-Dupont teaches:
The method of claim 2, (Witchey-Zhang-Dupont teaches the parent limitation above.) wherein the notification comprises a data query for querying the one or more datasets for the subset data. (Zhang ¶ 29 teaches, the LLM may also generate a summary of the strategies applied to the set of queries, including the hierarchical order in which the queries were executed and the optimization strategies that were applied in executing each of the queries.)
The motive given in Claim 1 is equally applicable to the above claim.
Regarding Claim(s) 4 and 14 Witchey-Zhang-Dupont teaches:
The method of claim 3, wherein determining the subset of data comprises: (Witchey-Zhang-Dupont teaches the parent limitation above.)
generating, by the LLM, a plurality of data queries;
executing each of the plurality of data queries; and
based on executing each of the plurality of data queries:
selecting the data query; and
select subset of data from the one or more datasets. (Zhang ¶ 22-24 teaches, in order to determine characteristics associated with the queried data, the LLM may generate additional queries for retrieving sample data from the database system. The additional queries may be generated based on each query in the set of queries corresponding to the programming code. For example, when a query from the set of queries is configured to retrieve data from a particular data structure that satisfies a set of criteria, the LLM may generate a corresponding additional query for retrieving a subset of that data (e.g., every 10th record from the particular data structure that satisfies the set of criteria, etc.).)
The motive given in Claim 1 is equally applicable to the above claim.
Regarding Claim(s) 5 and 15 Witchey-Zhang-Dupont teaches:
The method of claim 4, wherein selecting the data query comprises determining, (Witchey-Zhang-Dupont teaches the parent limitation.)
for each respective data query in the plurality of data queries, a plausibility that the respective data query answers the question posed by the user. (Zhang ¶ 22-24 teaches, As discussed herein, the data from the database system may be associated with one or more characteristics. For example, the queried data may include files that exceed a threshold file size (or that are smaller than another thresh old file size))
The motive given in Claim 1 is equally applicable to the above claim.
Claim(s) 6-7 and 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Witchey-Zhang-Dupont as applied to claim 1 and 11 above, and further in view of Alphin III (US 2024/0427928 A1), hereinafter Alphin.
Regarding Claim(s) 6 and 16 Witchey-Zhang-Dupont teaches:
The method of claim 1, (Witchey-Zhang-Dupont teaches the parent claim above.)
Witchey-Zhang-Dupont does not appear to explicitly teach but in related art:
wherein the temporary access request comprises a single-use access request. (Alphin ¶ 71 teaches, An access duration component determines a duration for which access to additional user data should be granted. The duration may be specified in the request. In general, the duration should be limited to an amount needed to complete a requested task. Example durations can be single use, browsing session, a boot cycle, a day, a week, a month, a year, and the like)
It would have been obvious to one with ordinary skill the art, prior to the applicant's earliest effective filing date, to combine the teachings of Witchey-Zhang-Dupont with Alphin, to modify the token based digital private data exchange system of Witchey with the dynamic querying of Zhang with the LLM execution within a TEE of Dupont with the access request specifications of Alphin. The motivation to do so constitutes applying a known technique of applying limitations to an access request to known devices and/or methods for retrieving data via an LLM ready for improvement to yield predictable results of limiting valuable data exposure.
Regarding Claim(s) 7 and 17 Witchey-Zhang-Dupont-Alphin teaches:
The method of claim 1, (Witchey-Zhang-Dupont teaches the parent claim above.) wherein the temporary access request comprises an expiration time period. (Alphin ¶ 71 teaches, An access duration component determines a duration for which access to additional user data should be granted. The duration may be specified in the request. In general, the duration should be limited to an amount needed to complete a requested task. Example durations can be single use, browsing session, a boot cycle, a day, a week, a month, a year, and the like)
The motive given in Claim 6 is equally applicable to the above claim.
Claim(s) 8-9 and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Witchey-Zhang-Dupont as applied to claim 1 and 11 above, and further in view of Mudulodu (US 2025/0005021 A1), hereinafter Mudu.
Regarding Claim(s) 8 and 18 Witchey-Zhang-Dupont teaches:
The method of claim 1, wherein the operations further comprise providing, (Witchey-Zhang-Dupont teaches the parent claim above.)
Witchey-Zhang-Dupont does not appear to explicitly teach but in related art:
to an administrator of the one or more datasets, the access request. (Mudu ¶ 73 teaches, the VA can send the selected or predicted answer to the UI of the system admin to request the admin approval (e.g., curating), and then, once curated, it can send the curated predicted answer to the client device 310.)
It would have been obvious to one with ordinary skill the art, prior to the applicant's earliest effective filing date, to combine the teachings of Witchey-Zhang-Dupont with Mudu, to modify the token based digital private data exchange system of Witchey with the dynamic querying of Zhang with the LLM execution within a TEE of Dupont with the administrator of Mudu. The motivation to do so constitutes applying a known technique of utilizing an administrator to known devices and/or methods for retrieving data via an LLM ready for improvement to yield predictable results of having secure oversight of an access request.
Regarding Claim(s) 9 and 19 Witchey-Zhang-Dupont-Mudu teaches:
The method of claim 8, wherein the operations further comprise, after providing, (Witchey-Zhang-Dupont teaches the parent limitation above.)
to the administrator of the one or more datasets, the access request:
receiving, from the administrator, approval of the temporary access request; and
based on the approval of the temporary access request, providing the subset of data from the one or more
datasets to the user device. (Mudu ¶ 73 teaches, the VA can send the selected or predicted answer to the UI of the system admin to request the admin approval (e.g., curating), and then, once curated, it can send the curated predicted answer to the client device.)
The motive given in Claim 8 is equally applicable to the above claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 12,436,946 B2 - Systems And Methods For Facilitating Database Queries
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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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/J.B.K./Examiner, Art Unit 2408
/LINGLAN EDWARDS/Supervisory Patent Examiner, Art Unit 2408
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