DETAILED ACTION
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 .
The instant application having Application No. 19/253,533 filed on 6/27/2025 is presented for examination by the Examiner. Claims 1-20 are currently pending in the present application.
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of Applicant's claim for priority as a CON of 18/416,728 filed on 1/18/2024 now Patent 12,367,310 B2; which is a CON of 17/444,245 filed on 8/2/2021 now Patent 11,914,741 B2; which is a CON of 16/219,504 filed on 12/13/2018 now Patent 11,093,634 B1; which has PRO of 62,747,532 filed on 10/18/2018.
Drawings
The Applicant's drawings filed on 6/27/2025 are acceptable for examination purpose.
Information Disclosure Statement
As required by M.P.E.P. 609, the Applicant's submission of the Information Disclosure Statement dated 7/25/2025 is acknowledged by the Examiner and the cited references have been considered in the examination of the claims now pending.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
As per claims 1 and 16, the claims recite “in response to said determining, applying a sensitivity marker to at least the portion of the data set or confirming the sensitivity marker’s application to at least the portion of the data set” which contains subject matter which was not described in the specification. The specification only describes the process of applying a sensitivity marker in response to receiving input/instruction from a user.
Clarification or correction is respectfully required.
Note, the dependent claims are also rejected because they depend on and/or do not remedy the deficiencies inherited by their parent claims.
Claim Rejections - 35 USC § 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 an abstract idea without significantly more.
As per claim 1, the claim recites “A computer-implemented method comprising:
storing a data set in a quarantine database;
parsing the data set to determine that at least a portion of the data set matches criteria indicative of potentially sensitive data; and
in response to said determining, applying a sensitivity marker to at least the portion of the data set or confirming the sensitivity marker’s application to at least the portion of the data set”.
Step 1: Statutory Category
Claim 1 discloses a method which is a process within the meaning of the section.
Step 2A - Prong One: Judicial Exception Recited
The claim recites the limitation “parsing the data set to determine…”. This limitation is process that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen or paper. For example, “parsing the data set to determine…” in the context of this claim encompass a user mentally, and with the aid of pen and paper looking at information of data and examining to identify or determine the relevant or desired data.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A - Prong Two: Integrated into a Practical Application
The claim recites the additional elements “storing a data set…” and “applying a sensitivity marker…”. The judicial exception is not integrated into a practical application. In particular, the additional steps: the “storing” step mounts to data gathering which is considered to be insignificant extra-solution activity (see MPEP 2106.05(g)), and the “applying a sensitivity marker…” step is considered as a mere instruction to apply an exception to perform an existing process on a generic computer and/or no more than an idea of a solution or outcome on a generic computer (see MPEP 2106.05(f)). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea, thus fail to integrate the abstract idea into a practical application. See MPEP 2106.05(g).
Step 2B: Claim provides an Inventive Concept
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activities identified above, which include the data-gathering and the step of “applying a sensitivity marker…” is recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d)(II)). For these reasons, there is no inventive concept in the claim, and thus it is ineligible.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of performing the “applying a sensitivity marker…” step amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The claim as a whole, does not amount to significantly more than the abstract idea itself. This is because the claim does not affect an improvement to the functioning of a computer itself; and the claim does not move beyond a general link of the use of an abstract idea to a particular technological environment.
Accordingly, claim 1 is directed to an abstract idea.
As per claim 2, the claim recites “The computer-implemented method of Claim 1, wherein applying the sensitivity marker or confirming the sensitivity marker’s application is performed automatically in response to said determining”. The judicial exception is not integrated into a practical application. In particular, the additional limitation amounts to no more than mere instructions to apply an exception to perform an existing process on a generic computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 3, the claim recites “The computer-implemented method of Claim 1 further comprising: in response to application of the sensitivity marker, releasing at least the portion of the data set to a second database where copying, moving, or sharing of the data set are permitted”. The judicial exception is not integrated into a practical application. In particular, the additional limitation amounts to no more than mere instructions to apply an exception to perform an existing process on a generic computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 4, the claim recites “The computer-implemented method of Claim 1, wherein a regular expression is used as the criteria indicative of potentially sensitive data”. The judicial exception is not integrated into a practical application. In particular, this additional limitation covers mathematical concepts. Accordingly, the claim recites an abstract idea.
As per claim 5, the claim recites “The computer-implemented method of Claim 4 further comprising: receiving, from a user, the regular expression or a selection of the regular expression”. The judicial exception is not integrated into a practical application. In particular, this additional limitation amounts to a data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)) and does not amount to significantly more than the above-identified judicial exception.
As per claim 6, the claim recites “The computer-implemented method of Claim 4 further comprising:
determining, based on matching the regular expression to the portion of the data set, an indication of a type of sensitive information; and
transmitting data to visually indicate that the portion of the data set is the type of sensitive information”. The judicial exception is not integrated into a practical application. In particular, the additional limitation of “determining” has been discussed above with respect to the abstract idea (i.e., “Mental Processes”) and does not amount to significantly more than the above-identified judicial exception; and the additional limitation of “transmitting” amounts to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 7, the claim recites “The computer-implemented method of Claim 4, wherein: the data set is received from a data provider; and the regular expression is provided or selected by the data provider”. The judicial exception is not integrated into a practical application. In particular, these limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 8, the claim recites “The computer-implemented method of Claim 1, wherein said determining includes at least one of: scoring words in the data set, determining uniqueness of data in the data set, or applying an artificial intelligence (AI) model to the data set”. The judicial exception is not integrated into a practical application. In particular, the additional limitation of “scoring words…” covers mathematical concepts; the additional limitation of “determining” has been discussed above with respect to the abstract idea (i.e., “Mental Processes”) and does not amount to significantly more than the above-identified judicial exception; and the additional limitation of “applying” amounts to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 9, the claim recites “The computer-implemented method of Claim 1 further comprising:”, the judicial exception is not integrated into a practical application.
“receiving, from a first user, an authorization to release one or more portions of the data set, including the portion of the data set to which the sensitivity marker has been applied, from the quarantine database;”, this additional limitation amounts to a data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)) and does not amount to significantly more than the above-identified judicial exception.
“in response to receiving the authorization, moving the one or more portions of the data set to a second database where copying, moving, or sharing of the data set are permitted; and”, these limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)).
“receiving, from the second user, instructions for applying an ontology to the data set;”, this additional limitation amounts to a data gathering which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)) and does not amount to significantly more than the above-identified judicial exception.
“wherein the second user is granted access to the data set that is in the second database; wherein the second user is not authorized to access the data set in the quarantine database; and wherein copying, moving, and share of the data set are prohibited for the data set while the data set is in the quarantine database until the data set is released from the quarantine database”, these limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 10, the claim recites “The computer-implemented method of Claim 9, wherein: the first user is not authorized to use or share the data set that is in the second database; and the second user is not authorized to view, copy, move, share, or release the data set in the quarantine database”. The judicial exception is not integrated into a practical application. In particular, these limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 11, the claim recites “The computer-implemented method of Claim 10, wherein: the data set is received from a data provider; and the data provider is not authorized to release the data set from the quarantine database”. The judicial exception is not integrated into a practical application. In particular, these limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 12, the claim recites “The computer-implemented method of Claim 11, wherein: the data provider is not authorized to write data sets to the second database”. The judicial exception is not integrated into a practical application. In particular, this limitation amounts to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 13, the claim recites “The computer-implemented method of Claim 9 further comprising:
transmitting data to display, to the second user, a list of a plurality of data sets in the second database;
wherein the list of the plurality of data sets includes the data set; and
wherein the list of the plurality of data sets is filtered to exclude any data sets associated with markers that the second user is not authorized to view”. The judicial exception is not integrated into a practical application. In particular, these additional limitations amount to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 14, the claim recites “The computer-implemented method of Claim 1 further comprising:
performing a statistical analysis on the portion of the data set; and
transmitting data to display, to a first user, results of the statistical analysis about the portion of the data set, wherein the statistical analysis is indicative of a uniqueness of the portion of the data set”. The judicial exception is not integrated into a practical application. In particular, the additional limitation of “performing a statistical analysis” covers mathematical concepts; and the additional limitation of “transmitting” amounts to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 15, the claim recites “The computer-implemented method of Claim 14, wherein the statistical analysis includes at least one of: a graph indicating a distribution of values; a histogram; a report about a number of unique entries; or a report about a number of repeated entries”. The judicial exception is not integrated into a practical application. In particular, this additional limitation amounts to no more than mere instructions to implement the abstract idea on a general purpose computer (MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer do not amount to significantly more.
As per claim 16, the claim recites “A computer system comprising: one or more non-transitory, computer readable storage devices configured to store computer-readable instructions; and one or more processors configured to execute the computer-readable instructions to cause the computer system to perform operations comprising:” the limitations as same as claim 1.
Step 1: Statutory Category
Claim 16 discloses a computer system which is a machine within the meaning of the section.
Step 2A – Prong One: Judicial Exception Recited
The claim recites the limitations as same as claim 1, and therefore are interpreted as an abstract idea under the same premise as claim 1.
Step 2A – Prong Two: Integrated into a Practical Application
The claim recites additional elements as same as claim 1, and therefore are interpreted as an abstract idea under the same premise as claim 1.
Step 2B: Claim provides an Inventive Concept
The claim recites the limitations as same as claim 1, and therefore is considered under the same premise as claim 1 as no inventive concept in the claim, and thus it is ineligible.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nagasundaram et al. (US 2014/0047551 A1) in view of Redlich et al. (US 2009/0178144 A1).
As per claim 1, Nagasundaram et al. and Redlich et al. disclose A computer-implemented method comprising:
storing a data set in a quarantine database; as (Nagasundaram et al., see e.g., ¶ 0030: as embodiments of the present invention provide more efficient use of system resources because the system can search, compare, and use anonymized databases without having to decrypt huge databases of information. The anonymized database read as quarantine database)
parsing the data set to determine that at least a portion of the data set matches criteria indicative of potentially sensitive data; and as (Nagasundaram et al., see e.g., ¶ 0032: as a digital wallet provider may include de-contexting and encryption steps on sensitive data but may not remove data from database records because the digital wallet may desire to keep records of all previous purchases in case of a charge-back).
in response to said determining, applying a sensitivity marker to at least the portion of the data set or confirming the sensitivity marker’s application to at least the portion of the data set, as (Redlich et al., see e.g., ¶ 0140: as based at least on an access authorization of a second user and the sensitivity marker, granting the second user access to the data set (i.e., Release of extractions into a projection display in order to project with the modified data stream, the original document while maintaining complete separation of the modified source data stream (the source modified by the extraction of data objects and insertion of placeholders) and the extracted data object streams).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to modify the method of Nagasundaram et al. with the teaching of Redlich et al. to improve data security. The motivation to combine is apparent in Nagasundaram et al.’s reference, because of anonymization rules may be used to identify which data should be removed, masked, scrubbed, separated, and/or de-contexted in order to provide a meaningful and useful anonymized dataset for the requestor's particular purpose; (see e.g., Nagasundaram et al., ¶ 0027). Therefore, it would be advantageous to share the document within the organization or transmit it to outsiders while still maintaining security over the most important and critical content of the document (see e.g., Redlich et al., ¶ 0060).
As per claim 2, Redlich et al. discloses The computer-implemented method of Claim 1, wherein applying the sensitivity marker or confirming the sensitivity marker’s application is performed automatically in response to said determining, which is not explicitly disclosed by Nagasundaram et al., as (Redlich et al., see e.g., ¶ 0140: as based at least on an access authorization of a second user and the sensitivity marker, granting the second user access to the data set (i.e., Release of extractions into a projection display in order to project with the modified data stream, the original document while maintaining complete separation of the modified source data stream (the source modified by the extraction of data objects and insertion of placeholders) and the extracted data object streams).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to modify the method of Nagasundaram et al. with the teaching of Redlich et al. to improve data security. The motivation to combine is apparent in Nagasundaram et al.’s reference, because of anonymization rules may be used to identify which data should be removed, masked, scrubbed, separated, and/or de-contexted in order to provide a meaningful and useful anonymized dataset for the requestor's particular purpose; (see e.g., Nagasundaram et al., ¶ 0027). Therefore, it would be advantageous to share the document within the organization or transmit it to outsiders while still maintaining security over the most important and critical content of the document (see e.g., Redlich et al., ¶ 0060).
As per claim 3, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 1 further comprising: in response to application of the sensitivity marker, releasing at least the portion of the data set to a second database where copying, moving, or sharing of the data set are permitted, as (Nagasundaram et al., see e.g., ¶ 0071: as receiving, from the first user, an authorization to release one or more portions of the data set from the quarantine database (i.e., for recipient computers 140 that are authorized to receive anonymized information (and the private information that may be gained by reversing the anonymization process) from the secure organization 120, the set of privacy rules may be provided to the recipient computer so that some of the private data may be recreated by reversing the anonymization processes applied to the private data); and (see e.g., ¶ 0053: as moving the one or more portions of the data set to a second database where copying, moving, or sharing of the data set are permitted (i.e., the process of “de-contexting” data may include any method of switching, repackaging, moving, or otherwise changing the context in which data may be presented in order to make the data less sensitive and/or private. There are numerous manners in which to de-context data).
As per claim 4, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 1, wherein a regular expression is used as the criteria indicative of potentially sensitive data, as (Nagasundaram et al., see e.g., ¶ 0102: as At step 403, the anonymization engine 134 determines if the message includes the identified type or types of private information. As explained above, any method may be used to determine if a social security number is present in the message. Using the example above, the anonymization engine 134 may search the message and any attached documentation, files, etc., for the criteria associated with social security numbers that are determined in step 402 above).
As per claim 5, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 4 further comprising: receiving, from a user, the regular expression or a selection of the regular expression, as (Nagasundaram et al., see e.g., ¶ 0102: as At step 403, the anonymization engine 134 determines if the message includes the identified type or types of private information. As explained above, any method may be used to determine if a social security number is present in the message. Using the example above, the anonymization engine 134 may search the message and any attached documentation, files, etc., for the criteria associated with social security numbers that are determined in step 402 above).
As per claim 6, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 4 further comprising:
determining, based on matching the regular expression to the portion of the data set, an indication of a type of sensitive information; and as (Nagasundaram et al., see e.g., ¶ 0028: as an anonymization engine implementing a customizable rule-based anonymization of large amounts of data may be provided based on each particular customer's need and capabilities. Accordingly, a customer may provide anonymization rules to an anonymization engine and may be provided with their customized anonymized data. Depending on the needs of the customer, the anonymization rules may be generated so that the customer can customize the de-contexting, the separation of data, etc., to match their needs).
transmitting data to visually indicate that the portion of the data set is the type of sensitive information, as (Nagasundaram et al., see e.g., ¶ 0060: as As long as the data is transmitted outside the enterprise environment through a communications network 160, the privacy computer 130 may analyze the data being sent outside the environment to ensure no private information is being transmitted outside the secure area 120 that is not within the access rights of the recipient computer 140).
As per claim 7, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 4, wherein: the data set is received from a data provider; and the regular expression is provided or selected by the data provider, as (Nagasundaram et al., see e.g., ¶ 0151: as the determination of whether data is truly necessary for a particular requesting system could be determined by a system administrator, the security or legal agreements of the information provider whose information is being used, a state or federal government, or any other entity associated with the data).
As per claim 8, Redlich et al. discloses The computer-implemented method of Claim 1, wherein said determining includes at least one of: scoring words in the data set, determining uniqueness of data in the data set, or applying an artificial intelligence (AI) model to the data set, which is not explicitly disclosed by Nagasundaram et al., as (Redlich et al., see e.g., ¶¶ 0130, 0167, and 0245).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to modify the method of Nagasundaram et al. with the teaching of Redlich et al. to improve data security. The motivation to combine is apparent in Nagasundaram et al.’s reference, because of anonymization rules may be used to identify which data should be removed, masked, scrubbed, separated, and/or de-contexted in order to provide a meaningful and useful anonymized dataset for the requestor's particular purpose; (see e.g., Nagasundaram et al., ¶ 0027). Therefore, it would be advantageous to share the document within the organization or transmit it to outsiders while still maintaining security over the most important and critical content of the document (see e.g., Redlich et al., ¶ 0060).
As per claim 9, Nagasundaram et al. and Redlich et al. disclose The computer-implemented method of Claim 1 further comprising:
receiving, from a first user, an authorization to release one or more portions of the data set, including the portion of the data set to which the sensitivity marker has been applied, from the quarantine database; as (Nagasundaram et al., see e.g., ¶ 0071: as for recipient computers 140 that are authorized to receive anonymized information (and the private information that may be gained by reversing the anonymization process) from the secure organization 120, the set of privacy rules may be provided to the recipient computer so that some of the private data may be recreated by reversing the anonymization processes applied to the private data).
in response to receiving the authorization, moving the one or more portions of the data set to a second database where copying, moving, or sharing of the data set are permitted; and as (Nagasundaram et al., see e.g., ¶ 0053: as the process of "de-contexting" data may include any method of switching, repackaging, moving, or otherwise changing the context in which data may be presented in order to make the data less sensitive and/or private. There are numerous manners in which to de-context data).
receiving, from the second user, instructions for applying an ontology to the data set; as (Redlich et al., see e.g., ¶ 0337: as These keywords are the initial sensitive word/objects. Statistical algorithms are applied to gather non-common word/objects which are associate with the keywords as found in the additional data compilations. The goal of the adaptive filter is to obtain contextual, semiotic and taxonomic words, characters or data objects from the compilation of additional data related to the security sensitive words, characters or data objects. Semiotic is a general philosophical theory of signs and symbols (read language and words and objects) that especially deals with their function. Semiotics include syntactics, semantics and pragmatics. Syntactics is the formal relationship between signs).
wherein the second user is granted access to the data set that is in the second database; as (Nagasundaram et al., see e.g., ¶ 0007: as the present invention allow protection from unlawful use of consumer information or other private information, provide prevention from identification of people (i.e., "anonymizes" any sensitive data such that an individual cannot be readily identified by the data), and can render data useless from a privacy and security standpoint, while still allowing efficient access and use for specific purposes).
wherein the second user is not authorized to access the data set in the quarantine database; and as (Nagasundaram et al., see e.g., ¶ 0024: as embodiments of the present invention provide a customizable anonymization engine that may provide anonymization for many different entities based on their needs, access rights, trust level, etc., according to a plurality of privacy and anonymization rules that are configured or associated with a particular user, organization, or computer).
wherein copying, moving, and share of the data set are prohibited for the data set while the data set is in the quarantine database until the data set is released from the quarantine database, as (Nagasundaram et al., see e.g., ¶ 0023: as The anonymization engine may be used for a number of purposes including protecting private information from export outside of a secure environment as well as for providing easily customizable anonymized data for a specific purpose of a requestor).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to modify the method of Nagasundaram et al. with the teaching of Redlich et al. to improve data security. The motivation to combine is apparent in Nagasundaram et al.’s reference, because of anonymization rules may be used to identify which data should be removed, masked, scrubbed, separated, and/or de-contexted in order to provide a meaningful and useful anonymized dataset for the requestor's particular purpose; (see e.g., Nagasundaram et al., ¶ 0027). Therefore, it would be advantageous to share the document within the organization or transmit it to outsiders while still maintaining security over the most important and critical content of the document (see e.g., Redlich et al., ¶ 0060).
As per claim 10, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 9, wherein: the first user is not authorized to use or share the data set that is in the second database; and as (Nagasundaram et al., see e.g., ¶ 0067: as the secure communications network may require a user computer 110 be authorized to access the secure communications network in order to obtain data through the secure communications network or send data outside the secure organization or area 120 to an unsecured organization or area) the second user is not authorized to view, copy, move, share, or release the data set in the quarantine database, as (Nagasundaram et al., see e.g., ¶ 0129: as a requesting system could be a customer service representative, a technician, a third party customer requesting metrics related to certain types of service, or any other interested party that would like access to data originating from a sensitive data record but is not authorized to view personal identifying information or personal account information for consumers.
As per claim 11, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 10, wherein: the data set is received from a data provider; and the data provider is not authorized to release the data set from the quarantine database, as (Nagasundaram et al., see e.g., ¶ 0151: as the determination of whether data is truly necessary for a particular requesting system could be determined by a system administrator, the security or legal agreements of the information provider whose information is being used, a state or federal government, or any other entity associated with the data. Accordingly, anonymization rules may be generated that are consistent with the purpose for the anonymized data).
As per claim 12, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 11, wherein: the data provider is not authorized to write data sets to the second database, as (Nagasundaram et al., see e.g., ¶ 0071: as for recipient computers 140 that are authorized to receive anonymized information (and the private information that may be gained by reversing the anonymization process) from the secure organization 120, the set of privacy rules may be provided to the recipient computer so that some of the private data may be recreated by reversing the anonymization processes applied to the private data).
As per claim 13, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 9 further comprising: transmitting data to display, to the second user, a list of a plurality of data sets in the second database; wherein the list of the plurality of data sets includes the data set; and wherein the list of the plurality of data sets is filtered to exclude any data sets associated with markers that the second user is not authorized to view, as (Nagasundaram et al., see e.g., Fig. 5: as for wherein the list of the plurality of data sets includes the data set; and wherein the list of the plurality of data sets is filtered to exclude any data sets associated with markers that the second user is not authorized to view).
As per claim 14, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 1 further comprising: performing a statistical analysis on the portion of the data set; and transmitting data to display, to a first user, results of the statistical analysis about the portion of the data set, wherein the statistical analysis is indicative of a uniqueness of the portion of the data set, as (Nagasundaram et al., see e.g., Fig. 5, item 512 for displaying the uniqueness of the portion of the data set).
As per claim 15, Nagasundaram et al. as modified by Redlich et al. discloses The computer-implemented method of Claim 14, wherein the statistical analysis includes at least one of: a graph indicating a distribution of values; a histogram; a report about a number of unique entries; or a report about a number of repeated entries, as (Nagasundaram et al., see e.g., ¶ 0153: as the search sub-strings may also flag random data by a predetermined pattern such that the first four digits of each data entry may be saved because the likelihood that another consumer has the same first four digits of each data entry is miniscule. The rest of the data could later be encrypted or masked. In this manner, the anonymized data record could be compared and searched to identify a consumer internally but would not be helpful to a malicious third party in accomplishing a fraudulent transaction or identity theft. However, this embodiment may not provide as much valuable information for later analysis so may be used in only particular situations for record comparison and search).
As per claims 16-18, the claims are rejected under the same premises as the claims 1-3 respectively.
As per claim 19, the claim is rejected under the same premise as the claim 8.
As per claim 20, the claim is rejected under the same premises as the claims 5 and 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2019/0272386 A1 by Ley teaches an integration security tool set integrates a suite of security tools with an organization process and work flow, coordinated and managed by the integrated tool set, to manage server and database security. The integration tool set communicates with different security tools to ensure that different sets of security rules are implemented in the servers and databases in the organization.
US 9,773,227 B2 by Plastina teaches reducing risk of data loss by automatically background scanning data to detect a plurality of candidate sensitive data items. For at least some of those candidate sensitive data items that are deemed not to concretely classified as sensitive, a dissolvable encryption is applied to the data item to at least temporarily protect the data item. When the user requests access to the data item, the system determines that the data item has been dissolvably encrypted and that the user is authorized to define the sensitivity of the data item. In response, the user is allowed to direct the system as to whether the data item is to be concretely encrypted (such as if the user was to confirm the data item as sensitive), or whether the dissolvable encryption of the data item is to be dissolved (such as if the user was to confirm the data item as not sensitive).
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bai D. Vu whose telephone number is (571) 270-1751. The examiner can normally be reached 9:00 - 5:30.
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/BAI D VU/Primary Examiner, Art Unit 2163 7/13/2026
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