CTNF 18/727,563 CTNF 84535 DETAILED ACTION This action is in response to communication on July 9 th , 2024. Claims 1-20 are currently pending. Claims 1-20 are currently amended via preliminary amendment. And claims 21-28 are canceled via preliminary amendment. The present application is a 371 National Phase Entry of International Application no. PCT/IB2022/052400, filed on March 16 th , 2022, which claims priority to the European Application no. EP22382022.6, filed on January 17 th , 2022. 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-12-aia AIA (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. 07-15-03-aia AIA Claim s 1-3, 9-12, and 18-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Bai et al (U.S. Patent Application Publication no. 2022/0368395, hereinafter Bai) . With respect to claims 1, 10, and 20, Helmsen discloses a method, network node, and computer-readable storage medium, performed by a network data analytics function of a wireless communication network (paragraph [0062], lines 7-15, analyze network traffic data ), of generating realistic synthetic network traffic data (paragraph [0057], lines 1-7, generated synthetic network traffic data ), the method comprising: receiving, from a network function, a request for a SyntheticData analytic (paragraph [0082], lines 1-4, generating the synthetic network traffic data ), the request specifying at least an amount of network traffic data requested and the type of network traffic data requested (paragraph [0082], lines 1-4, applying the generative rule set ); using a Generative Adversarial Network, GAN, model to generate realistic synthetic network traffic data based on actual network traffic collected in the wireless communication network (paragraph [0082], lines 4-7, applying a probabilistic generative model set ); and sending, to the requesting network function, the specified amount of synthetic network traffic data of the specified type (paragraph [0085], lines 1-7, assessment may represent a determination by the discriminative system ). With respect to claims 2 and 11, Helmsen discloses the method of claims 1 and 10, wherein the SyntheticData analytic request further specifies one or more of: an App-ID identifying an application which is a target of the analytic (paragraph [0060], network traffic data which may be indexed or otherwise tagged for use in different applications ); one or more UE-IDs or UE-Group-IDs identifying one or more User Equipment, UE, or defined groups of UEs, respectively, which are targets of the analytic; and a time period for which the analytic applies (paragraph [0073], lines 9-23). With respect to claims 3 and 12, Helmsen discloses the method of claims 1 and 10, wherein the SyntheticData analytic request further specifies one or more filter parameters, including: Data Network Name, DNN; Single-Network Slice Selection Assistance Information, S-NSSAI; Area of Interest (paragraph [0077], classifying synthetic network traffic data ); and Radio Access Technology, RAT, type. With respect to claims 9 and 18, Helmsen discloses the method of claims 1 and 10, wherein sending the synthetic network traffic data to the requesting network function comprises generating a SyntheticData analytic output including: Analytic-Id set to “SyntheticData” (paragraph [0085]); and Analytic-Result including the amount of synthetic network traffic data, of the type, specified in the request for the SyntheticData analytic (paragraph [0086]). With respect to claim 19, Helmsen discloses the network node of claim 10, wherein the processing circuitry is further configured to implement a Data Generator Logical Function, DGLF (paragraph [0089], function as a modified generative adversarial network ) . Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-22-aia AIA Claim s 4-8 and 13-17 are rejected under 35 U.S.C. 103 as being unpatentable over Helmsen as applied to claim s 1 and 10 above, and further in view of Ranganath et al (U.S. Patent Application Publication no. 2024/0259879, hereinafter Ranganath) . With respect to claims 4 and 13, Helmsen discloses the method of claims 1 and 10, further comprising, if a GAN model for the requested parameters does not exist: collecting actual network traffic data from a User Plane Function, UPF, in the wireless communication network (paragraph [0059], lines 1-4, genuine network data store ); and using the collected actual network traffic data to execute analysis and learning processes to obtain a GAN model configured to generate synthetic data according to parameters specified in the SyntheticData analytic request (paragraph [0097], lines 1-11, train one or more network security systems using synthetic network traffic generated using the refined probabilistic generative model ). But Helmsen does not disclose collecting actual network traffic from a User Plane Function, UPF, in the wireless communication network. However, Ranganath discloses collecting actual network traffic from a User Plane Function, UPF, in the wireless communication network (paragraph [0050], generating and provisioning measurement configurations ). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine the generative adversarial networks for use in refining models for synthetic network traffic data of Helmsen with the radio access network intelligent application manager of Ranganath. The motivation to combine being to improve wireless network connectivity. The wireless network connectivity being improved by the collection and analysis of platform telemetry data (abstract: Ranganath). With respect to claims 5 and 14, the combination of Helmsen and Ranganath discloses the method of claims 4 and 13, Helmsen further discloses wherein using the collected actual network traffic data to execute analysis and learning processes to obtain a GAN model comprises: sending the collected actual network traffic data to a model training logical function of a network data analytics function (paragraph [0097]); and receiving a trained GAN model from the model training logical function (paragraph [0097]). With respect to claims 6 and 15, the combination of Helmsen and Ranganath discloses the method of claims 4 and 13, Ranganath further discloses wherein the actual network traffic data collected from the UPF includes one or more of: raw Internet Protocol, IP, packets (paragraph [0094]); flow information including 5-tuples (paragraph [0114]); Uniform Resource Locators, URLs (paragraph [0182]); and Server Name Indication (SNI). With respect to claims 7 and 16, the combination of Helmsen and Ranganath discloses the method of claims 4 and 13, Ranganath further discloses, prior to collecting actual network traffic data from the UPF: instructing one or both of an Application Function, AF, and User Equipment, UE, as the endpoints of communication through the wireless communication network, to generate user plane traffic for the requested application (paragraph [0238]). With respect to claims 8 and 17, the combination of Helmsen and Ranganath discloses the method of claims 7 and 16, Helmsen further discloses mapping the generated data flow between the endpoints with a correspondent label (paragraph [0081], synthetic flow data ) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Xiao Pat. Pub. 2023/0095092 Tong Pat. Pub. 2024/0022927 Cricri Pat. Pub. 2023/0269387 Mohan Pat. Pub. 2022/0312256 Li Pat. Pub. 2024/0045851 Singh Pat. Pub. 2023/0199519 Rezazadegan Pat. Pub. 2026/0162313 Yeh Pat. Pub. 2026/0156535 Wang Pat. Pub. 2023/0325258 Any inquiry concerning this communication or earlier communications from the examiner should be directed to BLAKE J RUBIN whose telephone number is (571)270-3802. The examiner can normally be reached on Monday - Friday, 9am - 5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ario Etienne can be reached on 571-272-4001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. 6/12/26 /BLAKE J RUBIN/Primary Examiner, Art Unit 2457 Application/Control Number: 18/727,563 Page 2 Art Unit: 2457 Application/Control Number: 18/727,563 Page 3 Art Unit: 2457 Application/Control Number: 18/727,563 Page 5 Art Unit: 2457 Application/Control Number: 18/727,563 Page 6 Art Unit: 2457 Application/Control Number: 18/727,563 Page 7 Art Unit: 2457
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