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 .
Claims 13-24 have been examined.
Response to Arguments
The 35 U.S.C. 112 (f) interpretation is withdrawn in light of Amendment filed on 8/6/26.
Applicant's arguments filed on 8/6/26 have been fully considered but they are not persuasive.
Regarding Applicant’s remarks, Applicant mainly argues that the prior art of record does not explicitly disclose “counts based on homomorphically encrypted attribute information.” However, the examiner disagrees.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Specifically, Wang discloses generating homomorphically encrypted data to allow plurality of participating entities to perform statistical operations without compromising data privacy of data owners, statistical processing on encrypted data corresponding to common data identifiers in the identifier intersection to obtain encrypted statistical values (Wang: Abstract; [0010]-[0013]: perform homomorphic encryption on pieces of the first data and send it to cooperative data party to obtain statistical values; [0024]: [0073]-[0080]: an example of a statistical value being the sum of a plurality of pieces of first data, it can also be average value of a plurality of pieces of first data; during the data statistics, homomorphically encrypted data may be sent to the cooperative data party, so that the cooperative party can perform statistical processing on the encrypted data…without exposing any data privacy). Although Wang does not explicitly disclose counting the number of encrypted user data items having common attribute value that are encrypted using homomorphic encryption method, McFall addresses the concept of common database operations of sum, mean, or count to generate statistical data associated with different attribute values (McFall: Abstract; [0082]: protecting common identifier and ensuring it is not revealed in the matching process or the resulting joined dataset; [0087]-[0088]). Furthermore, since the claims are recited at a high level of generality, the combination of references teaches or at least suggests performing statistical analysis of data using homomorphically encrypted identifier or attribute information using well-known database operations such as counting or summing values of matching entries.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 13-22 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Wang U.S. 2020/0204342 (hereinafter Wang) in view of McFall et al. U.S. 2020/0327252 (hereinafter McFall).
As per claim 13, Wang discloses an information processing device comprising:
processing circuitry configured to:
obtain user data including a user ID and attribute information related to a user, encrypt the user ID on the basis of an encryption key held by the information processing device itself (Wang: [0047]-[0048]: encrypt data identifier using local private key to avoid exposure of data identifiers and provides more secure protection; [0072]-[0074]: Table 9 shows encrypted user ID/hash of idcard number and encrypted attribute information), and encrypts the attribute information using a homomorphic encryption method to generate encrypted user data (Wang: [0101]: the encrypted data can be obtained by performing the homomorphic encryption on the plurality of pieces of first data); and
generates statistical value based on common attribute information encrypted using homomorphic encryption (Wang: Fig. 2: cooperative data party generates encrypted statistical value; [0073]-[0080]: an example of a statistical value being the sum of a plurality of pieces of first data, it can also be average value of a plurality of pieces of first data; during the data statistics, homomorphically encrypted data may be sent to the cooperative data party, so that the cooperative party can perform statistical processing on the encrypted data…without exposing any data privacy).
Wang does not explicitly disclose counting the number of encrypted user data items having common attribute information based on the attribute information. However, McFall discloses typical database queries that include sum, mean, or count based on privacy preserving queries and computations (McFall: Abstract; [0082]: protecting common identifier and ensuring it is not revealed in the matching process or the resulting joined dataset; [0087]-[0088]). It would have been obvious to one having ordinary skill in the art to count the total numbers of encrypted data based on privacy preserving queries because Wang and McFall are analogous art. The motivation to combine would be that sum and counting based on common identifiers are well-known data queries.
As per claim 14, Wang as modified discloses the information processing device according to claim 13. Wang further discloses wherein the processing circuitry is further configured to:
transmit and receive the encrypted user data to and from a counterpart device (Wang: Fig. 2 statistical party and cooperative data party communicate encrypted data back and forth); and
match the encrypted user data of the information processing device itself generated by the processing circuitry with the encrypted user data of the counterpart device received, and count the number of encrypted user data items having user ID correspondence portions matched with each other as a result of the matching (Wang: [0084]: the encrypted statistical calculation on the encrypted data corresponding to the common data identifiers in an identifier intersection by the cooperative data party).
As per claim 15, Wang as modified discloses the information processing device according to claim 14. Wang further discloses wherein the processing circuitry is configured to perform the matching on a basis of the user ID correspondence portions specified on a basis of predetermined structural information of the user data (Wang: [0084]).
As per claim 16, Wang discloses an information processing device comprising:
processing circuitry configured to:
obtain user data including a user ID, encrypt the user ID on the basis of an encryption key held by the information processing device itself to generate encrypted user data (Wang: Fig. 2; [0047]: encrypt data identifiers/user ID using local private key);
transmit and receive the encrypted user data to and from a counterpart device (Wang: Fig. 2: statistical data party and cooperative data party send and receive encrypted data for statistical purposes);
match the encrypted user data of the information processing device itself generated by the ID encryption unit with the encrypted user data of the counterpart device received (Wang: [0084]: generate encrypted statistical values by performing calculation on the encrypted data corresponding to the common data identifiers in an identifier intersection by the cooperative data party, wherein the identifier intersection includes the common data identifiers corresponding to pieces of second data of the cooperative data party subject to the data statistics and selected from the plurality of data identifiers corresponding to the plurality of pieces of first data), and
generate value based on user ID correspondence portions matched with each other as a result of the matching by the data matching unit (Wang: [0078]-[0079]: statistical values can be sum or average of encrypted user data).
Wang does not explicitly disclose counting the number of encrypted user data items. However, McFall discloses typical database queries that include sum, mean, or count based on privacy preserving queries and computations (McFall: Abstract; [0087]-[0088]). It would have been obvious to one having ordinary skill in the art to count the total numbers of encrypted data based on privacy preserving queries because Wang and McFall are analogous art. The motivation to combine would be that sum and counting based on common identifiers are well-known data queries.
As per claim 17, Wang as modified discloses the information processing device according to claim 16. Wang as modified further discloses wherein the processing circuitry is configured to perform the matching on a basis of the user ID correspondence portions specified on a basis of predetermined structural information of the user data (Wang: [0084]).
As per claim 18, Wang discloses a privacy protection data linkage system comprising a plurality of devices holding user data including a user ID and attribute information related to a user (Wang: Fig. 2: statistical data party and cooperative data party both store user data associated with vehicle owners),
wherein one device among the plurality of devices includes processing circuitry configured to encrypt the user ID on a basis of an encryption key held by the one device itself to generate encrypted user data (Wang: Fig. 2; [0047]: encrypt data identifiers/user ID using local private key);
wherein a counterpart device among the plurality of devices includes processing circuitry configured to encrypt the user ID on a basis of an encryption key held by the counterpart device itself and encrypt the attribute information using a homomorphic encryption method to generate encrypted user data (Wang: Fig. 2: both parties encrypt data identifier/user identifiers based on local private key and encrypted data based on homomorphic encryption),
wherein the processing circuitry of each of the one device is further configured to: transmit and receive the encrypted user data (Wang: Fig. 2; both parties transmit and receive encrypted data from each other), and
wherein the processing circuitry of the one device is further configured to:
match the encrypted user data of the one device generated by the processing circuitry of the one device with the encrypted user data of the counterpart device received (Wang: [0084]: generate encrypted statistical values by performing calculation on the encrypted data corresponding to the common data identifiers in an identifier intersection by the cooperative data party, wherein the identifier intersection includes the common data identifiers corresponding to pieces of second data of the cooperative data party subject to the data statistics and selected from the plurality of data identifiers corresponding to the plurality of pieces of first data), and
generate value based on user ID correspondence portions matched with each other as a result of the matching by the data matching unit (Wang: [0078]-[0079]: statistical values can be sum or average of encrypted user data).
Wang does not explicitly disclose counting the number of encrypted user data items. However, McFall discloses typical database queries that include sum, mean, or count based on privacy preserving queries and computations (McFall: Abstract; [0087]-[0088]). It would have been obvious to one having ordinary skill in the art to count the total numbers of encrypted data based on privacy preserving queries because Wang and McFall are analogous art. The motivation to combine would be that sum and counting based on common identifiers are well-known data queries.
As per claim 19, Wang as modified discloses the privacy protection data linkage system according to claim 18. Wang as modified further discloses wherein the processing circuitry of each of the one device and the counterpart device is further configured to execute a process for privacy protection of the attribute information on the user data held by each device itself before the encryption of the user ID (Wang: [0006]; Fig. 2: retrieve encrypted user data/attribute information based on encrypted data identifier/user identifier).
As per claim 20, Wang as modified discloses the privacy protection data linkage system according to claim 18. Wang further discloses:
wherein the processing circuitry of the one device is further configured to execute a disclosure limitation process on encrypted count data generated by the counting to generate encrypted statistical information (Wang: [0084]: encrypted statistical values),
wherein the processing circuitry of the one device is configured to transmit the encrypted statistical to the counterpart device (Wang: Fig. 2: Cooperative data party transmits encrypted statistical value to statistical data party), and
wherein the processing circuitry of the counterpart device is further configured to decrypt the received encrypted statistical information on the basis of a decryption method corresponding to encryption by the encryption unit (Wang: Fig. 2: statistical data party decrypts homomorphically encrypted data).
As per claim 21, Wang as modified discloses the privacy protection data linkage system according to claim 18. Wang as modified further discloses wherein the processing circuitry of each of the one device and the counterpart device is further configured to execute an irreversible conversion process on the user ID of the user data held by each device itself before the encryption of the user ID (Wang: [0057]: hash of data identifiers/user identifiers).
As per claim 22, Wang as modified discloses the privacy protection data linkage system according to claim 21. Wang as modified further discloses the privacy protection data linkage system according to wherein the irreversible conversion process includes a hashing process (Wang: [0057]: hash of data identifiers/user identifiers).
As per claim 24, Wang discloses a privacy protection data linkage system comprising a plurality of devices holding user data including a user ID (Wang: Fig. 2: statistical data party and cooperative data party both store user data associated with vehicle owners),
wherein processing circuitry of each of one device and a counterpart device among the plurality of devices is configured to:
encrypt the user ID on a basis of an encryption key held by each device itself to generate encrypted user data (Wang: Fig. 2; [0047]: encrypt data identifiers/user ID using local private key); and
transmit and receive the encrypted user data (Wang: Fig. 2), and wherein the processing circuitry of the one device is further configured to:
match the encrypted user data of the one device generated by the processing circuitry of the one device with the encrypted user data of the counterpart device received (Wang: [0084]: generate encrypted statistical values by performing calculation on the encrypted data corresponding to the common data identifiers in an identifier intersection by the cooperative data party, wherein the identifier intersection includes the common data identifiers corresponding to pieces of second data of the cooperative data party subject to the data statistics and selected from the plurality of data identifiers corresponding to the plurality of pieces of first data), and
generate value based on user ID correspondence portions matched with each other as a result of the matching (Wang: [0078]-[0079]: statistical values can be sum or average of encrypted user data).
Wang does not explicitly disclose counting the number of encrypted user data items. However, McFall discloses typical database queries that include sum, mean, or count based on privacy preserving queries and computations (McFall: Abstract; [0087]-[0088]). It would have been obvious to one having ordinary skill in the art to count the total numbers of encrypted data based on privacy preserving queries because Wang and McFall are analogous art. The motivation to combine would be that sum and counting based on common identifiers are well-known data queries.
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of McFall and further in view of Holland et al. U.S. 9,246,686 (hereinafter Holland).
As per claim 23, Wang as modified discloses the privacy protection data linkage system according to 22. Wang as modified does not explicitly disclose wherein processing circuitry of each of the one device and the counterpart device is configured to discard a salt used in the hashing process after executing the hashing process on the user ID. However, Holland discloses generating salt value to hash user identifier and discard the salt value after generation of hash (Holland: col. 9 line 66 – col. 10 line 10). It would have been obvious to one having ordinary skill in the art to generate hash based on salt value and discard salt value after generation of hash because Holland, Wang and McFall are analogous art involving preserving privacy of user data. The motivation to combine would be to prevent unauthorized access in the event the that the computing device becomes compromised (Holland: col. 10 lines 8-10).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang et al. U.S. 2018/0302220 discloses user attribute matching method comprising encrypting user attribute information using homomorphic encryption algorithm.
Joosten U.S. 2017/0161314 discloses data verification in a distributed data processing system.
Meng U.S. 10,929,402 discloses secure join protocol in encrypted databases using homomorphic join operation.
Ren et al. U.S. 2020/0074112 discloses method for maintaining user privacy by using homomorphic encryption to protect user attribute information.
Kamara et al. U.S. 2017/0235969 discloses controlling security in relational databases by performing database queries in encrypted form.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHIN HON (ERIC) CHEN whose telephone number is (571)272-3789. The examiner can normally be reached Monday to Thursday 9am- 7pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynn Feild can be reached at 571-272-2092. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SHIN-HON (ERIC) CHEN/ Primary Examiner, Art Unit 2431
Prosecution Insights