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 .
Detailed Action
In amendments dated 3/12/26, Applicant amended claims 1, 3-8, and 19-20, canceled no claims, and added no new claims. Claims 1-20 are presented for examination.
Objections
Claims 5 and 6 are objected to because of the following informality: the amended preamble in each claim recites “detecting satisfaction of the comprises:” which is unclear language.
Rejections under 35 U.S.C. 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to mental processes without significantly more. Independent claims 1, 19, and 20 each recites continuously monitoring a set of attributes of the one or more tables identified by the classification scope to detect satisfaction of the one or more conditions for triggering the performance of data sensitivity classification; detecting, based on the monitoring, satisfaction of the one or more conditions of the automatic classification profile based on one or more changes to the set of attributes of the one or more tables; and in response to detecting satisfaction of the one or more conditions of the automatic classification profile, automatically triggering the performance of the data sensitivity classification on the one or more tables, the performance of data sensitivity classification comprising classifying data stored in one or more columns of the one or more tables to identify data sensitivity categories for data protection compliance. Monitoring attributes of tale to detect one or more conditions is evaluating and a mental process, detecting one or more conditions in a set of attributes is recited broadly and an evaluation and also a mental process, and classifying data in one or more tables is recited broadly and an evaluation of data and also a mental process. Each claim recites additional elements of receiving input from a user account that specifies one or more conditions for triggering data sensitivity classification; storing the input in an automatic classification profile for controlling when data sensitivity classification is triggered; accessing the automatic classification profile comprising the one or more conditions for triggering data sensitivity classification; and accessing a classification scope that identifies one or more tables to be classified. Receiving input, accessing a classification profile, and accessing a classification scope are each data gathering steps and insignificant extra-solution activity, and storing an input is also insignificant extra-solution activity. Claim 1 recites at least one hardware processor and at least one memory storing instructions and claim 20 recites a computer-storage medium comprising instructions, and each of these are generic components of a computer. Examiner notes specification paragraph 17 states “The need for users to create and maintain custom pipelines to automate the classification of multiple tables introduces a considerable cognitive and financial burden.” Also, paragraph 18 states “the ad-hoc or periodic nature of running these pipelines can lead to increased time to detection of personally identifiable information (PII) or sensitive data. Since the pipelines are not continuously active, there can be significant delays between the introduction of new data and its classification. This lag creates windows of vulnerability where sensitive data may be exposed to unauthorized access or may not comply with data protection regulations, potentially leading to legal and reputational risks.” Also, from paragraph 20, “the claimed approach provides ‘an automatic classification profile comprising one or more conditions for triggering data classification and access a classification scope that identifies one or more tables to be classified.’” Applicant’s amendments regard the type of data being classified but do not recite inventive details showing how the invention improves a technology or improves the function of a computer per MPEP 2106.04(d) and do not recite any unconventional steps in the invention per MPEP 2106.05(a). Therefore, the recited mental processes are not integrated into a practical application. Taking the claims as a whole, receiving input is recited broadly and amounts to receiving data across a network at least per specification paragraphs 21, 24, 34 and figure 1, which is routine and conventional per the list of such activities in MPEP 2106.05(d) part II, and accessing and storing data are retrieving and storing data from/in a memory which are also routine and conventional activities per the list of such activities in MPEP 2106.05(d) part II. The at least one hardware processor, at least one memory storing instructions, and computer-storage medium comprising instructions, are still generic components of a computer. The receiving, storing, and accessing steps are recited highly generally and can be conventionally performed in a computer. Therefore these claims do not include additional elements that are sufficient to amount to significantly more than the recited mental processes.
Claim 2 recites wherein the one or more conditions comprise at least one of an age of the one or more tables, a duration of time since the one or more tables have been previously classified, a minimum number of rows of the one or more tables, a data drift percentage of the one or more tables, a duration of time since a new column has been added to the one or more tables, one or more classification runtime parameters being met, or one or more default settings being met, and these conditions are mental processes accomplishable in the human mind or on paper. Claim 3 recites wherein detecting satisfaction of the one or more conditions of the automatic classification profile comprises: determining that the one or more tables comprises a new table that has not yet been classified (determining is evaluating and a mental process); computing an age for the new table based on a difference between a creation time of the new table and a current time (computing an age is a mental process accomplishable in the human mind or on paper); and determining that the age for the new table transgresses an age threshold to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process). Claim 4 recites wherein detecting satisfaction of the one or more conditions of the automatic classification profile comprises: obtaining a time representing when the one or more tables have previously been classified (obtaining data is a mental process accomplishable in the human mind or on paper); and determining that the time transgresses a duration threshold to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process).
Claim 5 recites wherein detecting satisfaction of the comprises: determining a number of rows present in the one or more tables (determining is evaluating and a mental process); and determining that the number of rows transgresses a minimum number of rows threshold to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process). Claim 6 recites wherein detecting satisfaction of the comprises: determining an increase percentage in a number of rows of the one or more tables (determining is evaluating and a mental process); and determining that the increase percentage in the number of rows transgresses a threshold to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process). Claim 7 recites wherein detecting satisfaction of the one or more conditions of the automatic classification profile comprises: determining that the one or more tables comprises a new column (determining is evaluating and a mental process); computing an age for the new column based on a difference between a creation time of the new column and a current time (computing data is a mental process accomplishable in the human mind or on paper); and determining that the age transgresses an age threshold to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process).
Claim 8 recites wherein detecting satisfaction of the one or more conditions of the automatic classification profile comprises: obtaining one or more default settings; and determining that the one or more default settings are currently met to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (determining is evaluating and a mental process). Claim 9 recites generating a set of categories for the one or more columns of the one or more tables in response to automatically classifying the data stored in the one or more columns of the one or more tables (generating data is a mental process accomplishable in the human mind or on paper). Claim 10 recites wherein the set of categories represents a type of data stored in the one or more columns (data is a mental process accomplishable in the human mind or on paper). Claim 11 recites accessing a map of tags representing sensitivity of data stored in the one or more tables (data is a mental process accomplishable in the human mind or on paper); determining that the set of categories for the one or more columns corresponds to the map of tags (determining is evaluating and a mental process); and in response to determining that the set of categories for the one or more columns corresponds to the map of tags, associating a tag with the one or more columns (associating data is evaluating data and a mental process).
Claim 12 recites restricting or masking data stored in the one or more columns in response to associating the tag with the one or more columns based on a defined masking policy (masking data is evaluating data and a mental process). Claim 13 recites wherein the map of tags is user defined or automatically generated (generating data is a mental process accomplishable in the human mind or on paper). Claim 14 recites wherein a tag in the map of tags comprises a plurality of categories (data is a mental process accomplishable in the human mind or on paper), and wherein determining that the set of categories for the one or more columns corresponds to the map of tags comprises determining that the set of categories includes each tag in the plurality of categories (determining is evaluating and a mental process). Claim 15 recites wherein a role of an account that creates the automatic classification profile excludes permissions to access data stored in the one or more tables, comprising: applying a global privilege to a process used to classify the data to enable the data stored in the one or more columns to be classified without exposing the data to the account (applying a global privilege is applying data and is a mental process accomplishable in the human mind or on paper). Claim 16 recites automatically selecting a warehouse size and time for execution of automatically classifying the data based on one or more heuristics for maximizing throughput and minimizing cost of execution (selecting data is evaluation and a mental process).
Claim 17 recites determining that one or more categories generated in response to automatically classifying the data stored in the one or more columns of the one or more tables corresponds to a predefined semantic category (determining is evaluating and a mental process). Claim 18 recites in response to determining that the one or more categories generated in response to automatically classifying the data stored in the one or more columns of the one or more tables corresponds to the predefined semantic category, tagging the one or more columns as at least one of an identifier, quasi-identifier, sensitive, or insensitive (tagging data is associating data with data and is a mental process accomplishable in the human mind or on paper).
Rejections under 35 U.S.C. 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2 and 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wiggins et al (US 20250126152), hereafter Wiggins.
With respect to claims 1, 19, and 20, Wiggins teaches:
receiving input from a user account that specifies one or more conditions for triggering performance of data sensitivity classification (paragraph 0048 input for user/client data about attributes about data for sensitivity (violating policy), described in the end of paragraph 0027 and 0028, also paragraph 0105 figure 15, scan profile 1506 with instructions for classifying a dataset, user account 1500 input with request);
storing the input in an automatic classification profile for controlling when data sensitivity classification is triggered (paragraph 0105 storing input policies in scan profile);
accessing the automatic classification profile comprising the one or more conditions for triggering data sensitivity classification (paragraph 0105 accessing scan profile);
accessing a classification scope that identifies one or more tables to be classified (paragraph 0031 access specific operations to a specific dataset according to requirements of a policy, paragraph 006 determine tables to update based on data policy for item (scope));
continuously monitoring a set of attributes of the one or more tables identified by the classification scope to detect satisfaction of the one or more conditions for triggering the performance of data sensitivity classification (paragraph 0028 monitoring attributes of content items related to classifications policy, also paragraph 0061);
detecting, based on the monitoring, satisfaction of the one or more conditions of the automatic classification profile based on one or more changes to the set of attributes of the one or more tables (paragraph 0031 detecting violations of policy to items in dataset, also paragraph 0028); and
in response to detecting satisfaction of the one or more conditions of the automatic classification profile, automatically triggering the performance of the data sensitivity classification on the one or more tables, the performance of data sensitivity classification comprising classifying data stored in one or more columns of the one or more tables to identify data sensitivity categories for data protection compliance (paragraph 0031 when detecting violations, classifying/modifying data to correct for violations per policies, also paragraphs 0119-0121).
With respect to claims 1, Wiggins teaches at least one hardware processor and at least one memory storing instructions (paragraph 0143 processor, memory).
With respect top claim 20, Wiggins teaches a computer-storage medium (paragraph 0143 computer-readable media).
With respect to clam 2, Wiggins teaches wherein the one or more conditions comprise at least one of an age of the one or more tables, a duration of time since the one or more tables have been previously classified, a minimum number of rows of the one or more tables, a data drift percentage of the one or more tables, a duration of time since a new column has been added to the one or more tables, one or more classification runtime parameters being met, or one or more default settings being met (paragraph 0044 example of policies based on third party requirements (default settings), paragraph 0080 example of attribute for policy including a timestamp of content item (age)).
Rejections under 35 U.S.C. 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 8 is rejected under 35 U.S.C. 103 as being unpatentable over Wiggins in view of Grondin et al (US 20150324606), hereafter Grondin.
With respect to claim 8, all the limitations in claim 1 are addressed by Wiggins above. Wiggins does not teach:
obtaining one or more default settings; and
determining that the one or more default settings are currently met to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile.
Grondin teaches these things:
obtaining one or more default settings (paragraph 0072 obtain settings for default protection policy); and
determining that the one or more default settings are currently met to determine that the set of attributes of the one or more tables identified by the classification scope corresponds to the one or more conditions of the automatic classification profile (paragraph 0072 policy satisfied so data blocked when an assessment score of the data meets a threshold).
It would have been obvious to have combined the function of detecting satisfaction of a policy per default settings in Grondin with the data sensitivity classification techniques in Wiggins as an efficient way to apply a rule/policy for classifying data.
Responses to Applicant’s Remarks
Regarding objection to the specification for paragraph 61 missing information, in view of amendments removing the dangling clause at the end of this paragraph, this objection is withdrawn. Regarding rejections of claims 1-20 under 35 U.S.C. 101 for reciting mental processes without significantly more, Applicant’s arguments have been considered but are not persuasive. On page 11 of his Remarks Applicant asserts the “continuously monitoring a set of attributes … to detect satisfaction of the one or more conditions …” and “detecting, based on the monitoring, satisfaction of the one or more conditions …” are not mental processes. Examiner disagrees and notes each step is recited generally and uses a generic computer as a tool and thus can be mental processes per MPEP 2106.04(a)(2)(III)(c). Examiner also notes the actions of monitoring to detect a condition and detecting said conditions both involve judgement or evaluation and are thus mental processes. On page 12 Applicant asserts the human mind is not equipped to perform the combination of claims operations. Examiner disagrees and notes each of the steps are recited broadly and, apart from the generic computer on which each step is performed, Examiner believes the combination of steps can be performed in the human mind. Also on pages 12-15 of his Remarks Applicant excerpts from specification paragraphs 17-19 and asserts “the claims reflect an improvement to automated data governance in database systems.” Examiner disagrees and notes those same paragraphs discuss drawbacks found in the art such as overhead of creating and maintaining pipelines for automating classification, slower detection of PII, standardizing processes/rules for classification, or inefficiencies in consuming system resources, and the clams do not recite details from the invention that improve upon any of these drawbacks. Examiner also notes the “continuously monitoring,” “detecting,” and “triggering the performance” steps are recited broadly and Examiner believes the additional elements of receiving input, string input, and accessing a profile and a classification scope do generally link the mental processes to a technological environment of the computer where data classification occurs per MPEP 2106.05(e).
On pages 15-16 Applicant asserts the additional elements along with the mental process steps recite a specific combination or operations that is not routine and conventional. Examiner disagrees and noted in the rejection maintained above that each said additional element is routine and conventional per the list of said activities in MPEP 2106.05(d)(II). Examiner believes the combination of operations in the claims, namely receiving input, storing the input, accessing conditions for the classifying, monitoring and detecting the conditions for the classifying, and then classifying according to the accessed conditions, is the combination of steps a person or ordinary skill in the art would find conventional for automated classifying of data.
Conclusion
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.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRUCE M MOSER whose telephone number is (571)270-1718. The examiner can normally be reached M-F 9a-5p.
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/BRUCE M MOSER/Primary Examiner, Art Unit 2154 4/24/26
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