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 .
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-3, 8-10, 15-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shaw et al. (US 2020/0020062) hereafter Shaw in view of Blumenfeld et al. (US 11,182,687) hereafter Blumenfeld.
1. Shaw discloses a computer-implemented method comprising:
determining, utilizing one or more synthetic account detection rules, a first set of synthetic user accounts that includes user accounts of a digital system (para 87-89);
determining a second set of synthetic user accounts that includes additional user accounts of the digital system based on associations between the additional user accounts and the user accounts from the first set of synthetic user accounts (para 23-28, para 94); and
Shaw does not explicitly disclose generating a synthetic account detection machine learning model to identify synthetic user accounts of the digital system by learning model parameters using the first set of synthetic user accounts and the second set of synthetic user accounts. However, in an analogous art, Blumenfeld discloses synthetic identity detection including generating a synthetic account detection machine learning model (col 39, 1-25) to identify synthetic user accounts (col 6, 6-col 7, line 4) of the digital system by learning model parameters using the first set of synthetic user accounts and the second set of synthetic user accounts (col 39, 1-25). It would have been obvious to a person of ordinary skill in the art before the effective filing date to modify the implementation of Shaw with the implementation of Blumenfeld in order to identify, process, and analyze the types of data that hold the most predictive value for detecting synthetic identities (col 5, 1-8).
2. Shaw and Blumenfeld disclose the computer-implemented method of claim 1, further comprising determining the associations between the additional user accounts and the user accounts from the first set of synthetic user accounts by determining, for an additional user account, at least one account feature that is shared between the additional user account and a user account from the first set of synthetic user accounts (Shaw, para 20-22).
3. Shaw and Blumenfeld disclose the computer-implemented method of claim 2, wherein determining the at least one account feature that is shared between the additional user account and the user account from the first set of synthetic user accounts comprises determining that the additional user account and the user account from the first set of synthetic user accounts include a common device ID (Blumenfeld, col 11, 1-col 13, 22, Device fingerprint; Table 1, device ID).
Claims 8-10, 15-17 are similar in scope to claims 1-3 and are rejected under similar rationale.
Claim(s) 4, 11, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shaw and Blumenfeld as applied to claims 3, 8, and 15 above, and further in view of Hyper-parameter Tuning Techniques in Deep Learning by Nabi hereafter Nabi.
4. Shaw and Blumenfeld disclose the computer-implemented method of claim 3, wherein learning the model parameters using the first set of synthetic user accounts and the second set of synthetic user accounts comprises iteratively: generating, utilizing the synthetic account detection machine learning model, a predicted indication that a user account from the first set of synthetic user accounts or the second set of synthetic user accounts is synthetic based on account features associated with the user account (col 39, 1-25; col 6, , 6-col 7, line 4); but do not explicitly disclose determining an error associated with the predicted indication; and modifying the model parameters of the synthetic account detection machine learning model based on the error. However, in an analogous art, Nabi discloses adjusting parameters of machine learning models including determining an error associated with the predicted indication; and modifying the model parameters of the synthetic account detection machine learning model based on the error (Gradient descent, random model parameters and calculate the error for each learning iteration, keep updating the model parameters to move closer to the values that results in minimum cost). It would have been obvious to a person of ordinary skill in the art before the effective filing date to modify the implementation of Shaw and Blumenfeld with the implementation of Nabi in order to find the optimal value (introduction, gradient descent).
Claims 11 and 15 are similar in scope to claim 3 and are rejected under similar rationale.
Claim(s) 5-7, 12-14, 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shaw, Blumenfeld, and Nabi as applied to claims 4, 8, 15 above, and further in view of Freeman et al. (US 10,333,964) hereafter Freeman.
5. Shaw, Blumenfeld and Nabi disclose the computer-implemented method of claim 4, further comprising: generating, utilizing the synthetic account detection machine learning model, an indication that a user account of the digital system is synthetic based on a plurality of account features related to the user account (Blumenfeld, col 11, 1-col 13, 22,); but do not explicitly disclose disabling the user account to prevent one or more actions of the user account on the digital system based on the indication that the user account is synthetic. However, in an analogous art, Freeman discloses fake account identification including disabling the user account to prevent one or more actions of the user account on the digital system based on the indication that the user account is synthetic (col 6, 3-col 7, 4). It would have been obvious to a person of ordinary skill in the art before the effective filing date to modify the implementation of Shaw, Blumenfeld, and Nabi with the implementation of Freeman in order to prevent fake accounts from performing actions (col 6, 4-col 7, 4).
6. Shaw, Blumenfeld, Nabi, and Freeman disclose the computer-implemented method of claim 5, wherein disabling the user account comprises closing the user account (Freeman, col 6, 4-col 7, 4).
7. Shaw, Blumenfeld, Nabi, and Freeman disclose the computer-implemented method of claim 5, wherein disabling the user account comprises suspending the user account and providing a notification to the user account regarding suspension of the user account (Freeman, col 6, 4-col 7, 4).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES R TURCHEN whose telephone number is (571)270-1378. The examiner can normally be reached Monday-Friday: 7-3.
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/JAMES R TURCHEN/ Primary Examiner, Art Unit 2439
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