DETAILED ACTION
This is in response to the Information disclosure statement filed 4/20/2026
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The Information disclosure statement filed 4/20/2026 has been considered.
Claim Rejections - 35 USC § 102
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) and/or 102(a)(2) as being anticipated by Liem et al., US PGPub 2021/0397683 A1.
Regarding claim 1, Liem et al., shows a privacy protection information processing method, comprising: sending, by a first communication device, a privacy protection service request message to a second communication device ([0039]-[0041]), wherein the privacy protection service request message comprises an identifier of the first communication device and privacy protection service description information [0042]-[0045]; and receiving, by the first communication device, privacy-protected service data returned by the second communication device (Fig. 1-4, 7, and 8; [0076]-[0079]).
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Regarding claim 2, Liem et al., shows the method according to claim 1, wherein the method further comprises: receiving, by the first communication device, a pre-configured set of privacy protection service description information from the second communication device, wherein the pre-configured set of privacy protection service description information is sent by a third communication device to the second communication device; selecting and storing, by the first communication device, target privacy protection service description information (Fig. 1; [0039]-[0042]), wherein the target privacy protection service description information is at least one piece of privacy protection service description information in the set of privacy protection service description information; and sending, by the first communication device, the target privacy protection service description information to the second communication device ([0080]-[0093] indicate the various privacy protection factors).
Regarding claim 3, Liem et al., shows the method according to claim 1, wherein the privacy protection service description information comprises at least one of the following: a privacy protection service identifier list; a privacy protection level, wherein a higher privacy protection level means that it is more difficult for the first communication device to infer original service data from the privacy-protected service data [0062]; a model training indication, indicating whether the service data requires model training; and a data request indication, indicating data requirements of the service data ([0094] i.e. if user has failed a specified number of time(s) the system may fall back to fail-safe mode; Fig 5 shows the various elements in the SVM).
Regarding claim 4, Liem et al., shows the method according to claim 3, wherein the data request indication comprises at least one of the following: sample type; sample quantity; sample validity period; sample range; and sample collection method ([0098] demonstrates a SVM used with the machine learning user data and valid or invalid data. [0099] shows the various data types).
Regarding claim 5, Liem et al., shows the method according to claim 3, wherein when the model training indication indicates that the service data requires model training, the privacy protection service description information further comprises at least one of the following: model training filter information, comprising at least one of the following: model algorithm type information or identifier information, model algorithm configuration information, model performance, and model data requirements; and a joint training indication, indicating whether the service data requires the first communication device and the third communication device to jointly perform model training (Fig. 2-4;[0045], [0060]-[0069], and [0095]-[0097] describe model training and ANN for algorithm).
Regarding claim 6, Liem et al., shows the method according to claim 2, wherein the first communication device is a third-party network function, the second communication device is a network exposure function, and the third communication device is a core network function ([0076]-[0078]; Identify the various access and handling elements by the devices).
Regarding claim 7, Liem et al., shows a privacy protection information processing method, comprising: receiving, by a second communication device, a privacy protection service request message sent by a first communication device ([0037]-[0041]), wherein the privacy protection service request message comprises an identifier of the first communication device and privacy protection service description information; after verifying that the first communication device is authorized to acquire a privacy protection service, sending, by the second communication device, the privacy protection service request message to a third communication device; receiving, by the second communication device, privacy-protected service data sent by the third communication device ([0064]-[0070]); and sending, by the second communication device, the privacy-protected service data to the first communication device (Fig. 1-4, 7, and 8; [0076]-[0079].
Regarding claim 8, Liem et al., shows the privacy protection information processing method according to claim 7, wherein before the sending the privacy protection service request message to the third communication device, the method further comprises: verifying, by the second communication device, the privacy protection service request message based on previously-stored privacy protection service description information, and determining that the first communication device is authorized to acquire a privacy protection service (Fig. 2-3; [0044]-[0046] and [0060]-[0069]).
Regarding claim 9, Liem et al., shows the privacy protection information processing method according to claim 8, wherein the method further comprises: receiving, by the second communication device, a pre-configured set of privacy protection service description information sent by the third communication device; sending, by the second communication device, the pre-configured set of privacy protection service description information to the first communication device; receiving, by the second communication device, target privacy protection service description information sent by the first communication device, wherein the target privacy protection service description information is at least one piece of privacy protection service description information in the set of privacy protection service description information; storing, by the second communication device, the target privacy protection service description information, and associating the target privacy protection service description information with the identifier of the first communication device; and sending, by the second communication device, association information of the target privacy protection service description information and the identifier of the first communication device to the third communication device (Fig. 1, 2/3, and 8; [0045], [0060]-[0069], [0076]-[0079] and [0095]-[0097]).
Regarding claim 10, Liem et al., shows the privacy protection information processing method according to claim 8, wherein the privacy protection service description information comprises at least one of the following: a privacy protection service identifier list; a privacy protection level, wherein a higher privacy protection level means that it is more difficult for the first communication device to infer original service data from the privacy-protected service data; a model training indication, indicating whether the service data requires model training; and a data request indication, indicating data requirements of the service data (Fig. 2-3; [0044]-[0045] and [0060]-[0069]).
Regarding claim 11, Liem et al., shows the method according to claim 10, wherein if target privacy protection service description information associated with the identifier of the first communication device comprises the privacy protection service description information in the privacy protection service request message, it is determined that the first communication device is authorized to acquire a privacy protection service ([0045], [0060]-[0069], and [0095]-[0097]).
Regarding claim 12, Liem et al., shows the method according to claim 10, wherein the data request indication comprises at least one of the following: sample type; sample quantity; sample validity period; sample range; and sample collection method ([0098] demonstrates a SVM used with the machine learning user data and valid or invalid data. [0099] shows the various data types).
Regarding claim 13, Liem et al., shows the method according to claim 10, wherein when the model training indication indicates that the service data requires model training, the privacy protection service description information further comprises at least one of the following: model training filter information, comprising at least one of the following: model algorithm type information or identifier information, model algorithm configuration information, model performance, and model data requirements; and a joint training indication, indicating whether the service data requires the first communication device and the third communication device to jointly perform model training. Fig. 1,-4 and 8; [0039]-[0045], [0076]-[0079], and [0095]
Regarding claim 14, Liem et al., shows the method according to claim 7, wherein the first communication device is a third-party network function, the second communication device is a network exposure function, and the third communication device is a core network function ([0076]-[0078]; Identify the various access and handling elements by the devices).
Regarding claim 15, Liem et al., shows s privacy protection information processing method, comprising: receiving, by a third communication device, a privacy protection service request message sent by a second communication device, wherein the privacy protection service request message comprises an identifier of a first communication device and privacy protection service description information; parsing, by the third communication device, the privacy protection service request message, collecting service data of a privacy protection service based on the privacy protection service description information, and performing privacy protection for the service data based on a parsing result; and sending, by the third communication device, privacy-protected service data to the second communication device (Fig. 1-4, 7, and 8; [0039]-[0045], [0076]-[0079], and [0095]).
Regarding claim 15, Liem et al., shows the method according to claim 15, wherein the method further comprises: sending, by the third communication device, a pre-configured set of privacy protection service description information to the second communication device; and receiving, by the third communication device, association information of target privacy protection service description information and the identifier of the first communication device, wherein the association information is sent by the second communication device (Fig.1, 7, and 8; [0039]-[0045], [0076]-[0079], and [0095]).
Regarding claim 17, Liem et al., shows the method according to claim 15, wherein the privacy protection service description information comprises at least one of the following: a privacy protection service identifier list; a privacy protection level, wherein a higher privacy protection level means that it is more difficult for the first communication device to infer original service data from the privacy-protected service data; a model training indication, indicating whether the service data requires model training; and a data request indication, indicating data requirements of the service data (Fig. 4 and [0039]-[0045], [0076]-[0079], and [0095]).
Regarding claim 18, Liem et al., shows the method according to claim 17, wherein the data request indication comprises at least one of the following: sample type; sample quantity; sample validity period; sample range; and sample collection method [0075].
Regarding claim 19, Liem et al., shows the method according to claim 17, wherein when the model training indication indicates that the service data requires model training, the privacy protection service description information further comprises at least one of the following: model training filter information, comprising at least one of the following: model algorithm type information or identifier information, model algorithm configuration information, model performance, and model data requirements; and a joint training indication, indicating whether the service data requires the first communication device and the third communication device to jointly perform model training (Fig. 8 and [0039]-[0045], [0076]-[0079], and [0095]).
Regarding claim 20, Liem et al., shows the method according to claim 17, wherein the parsing result comprises at least one of the following: a privacy protection level corresponding to the service data; and whether model training is performed on the service data (Fig. 3; [0072]-[0078] i.e. User device 102, cloud server 104, or service 106 determine contextual data, MLM, and additional variable(s) for authentication levels and related elements).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Laoutaris et al., US PGPub 2017/0142158 A1, is cited for public and private identifier
mapping systems i.e. Fig.1.
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Gandhi et al,. US Patent 10,983,554 B1, is cited for information about network identification
and privacy i.e. Fig.1.
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De Jong et al., US PGPub 2022//0103974 A1, shows multiple device systems involving
shared connectivity and identification systems i.e. Fig. 1A.
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Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAHVOSH J NIKMANESH whose telephone number is (571)270-5549. The examiner can normally be reached M-F 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Yuwen Pan can be reached at (571)272-7855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Seahvosh Nikmanesh/Examiner, Art Unit 2649 /YUWEN PAN/Supervisory Patent Examiner, Art Unit 2649
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