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 .
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.
Claim(s) 1-3, 5-7, 9-10 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rachlin et al. (US 10,380,351) hereafter Rachlin.
1. Rachlin discloses a computer-implemented method, comprising:
obtaining a first binomial distribution parameter (col 12, line 51-col 13, line 14);
obtaining target differential privacy parameters representing a target level of differential privacy, the target differential privacy parameters comprising a first target differential privacy parameter representing a privacy metric that controls a level of privacy of data (col 12, line 51-col 13, line 14, at block 504 where a first anonymization parameter is specified as well as a desired level for the first anonymization parameter);
for each value of multiple values of a second binomial distribution parameter,
determining, based on the value of the second binomial distribution parameter, an actual value of a first actual differential privacy parameter that represents an actual privacy metric (col 12, line 51-col 13 line 14, in the context of randomization schemes, the first anonymization parameter may comprise either an expected distortion (in which case, the desired level is specified as a maximum expected distortion) or an expected guessing anonymity (in which ease, the desired level is specified as a minimum expected guessing anonymity). By default, selection of the first anonymization parameter automatically sets the second anonymization parameter, i.e., selection of the expected distortion as the first anonymization parameter necessarily implies that guessing anonymity is the second anonymization parameter, whereas selection of the expected guessing anonymity as the first anonymization parameter necessarily implies that distortion is the second anonymization parameter), and
determining whether the actual value of the first differential privacy parameter satisfies the first target differential privacy parameter (col 12, line 51-col 13, line 14, at block 506, the noise parameter value that optimizes the second anonymization parameter (either maximizes guessing anonymity or minimizes distortion) subject to the desired level of the first anonymization parameter is determined. As described above, this is accomplished through evaluation of the guessing inequality in the context of the indicated noise model such that the resulting boundary condition may be employed, along with the desired level as constraint, in the optimization problem);
selecting, from a set of values of the second binomial distribution parameters for which the actual value of the first actual differential privacy parameter satisfies the first target differential privacy parameter, a given value of the second binomial distribution parameter (col 12, line 51-col 13, line 14, at block 506, the noise parameter value that optimizes the second anonymization parameter (either maximizes guessing anonymity or minimizes distortion) subject to the desired level of the first anonymization parameter is determined);
generating differential privacy noise using the first binomial distribution parameter and the given value of the second binomial distribution parameter (col 13, lines 15-24, at block 510, noise based on the noise parameter value is generated and applied to the quasi-identifiers in the structured data); and
applying the differential privacy noise to data to generate noised data (col 13, lines 15-24, at block 510, noise based on the noise parameter value is generated and applied to the quasi-identifiers in the structured data).
2. Rachlin discloses the computer-implemented method of claim 1, further comprising sending the noised data to one or more recipients after applying the differential privacy noise to the data (col 13, lines 15-24, at block 514, the noise perturbed data (potentially with any outlier data values appropriately modified) is provided to a third party, such as a business or academic research organization, or any other entity interested in analyzing anonymized structured data).
3. Rachlin discloses the computer-implemented method of claim 1, wherein the data comprises data for digital components (col 12, line 51-col 13, line 24).
5. Rachlin discloses the computer-implemented method of claim 1, wherein the first binomial distribution parameter comprises a number (n) of experiments parameter and the second binomial distribution parameter comprises a probability (p) parameter (col 10, line 45-col 11, line 29).
6. Rachlin discloses the computer-implemented method of claim 1, wherein obtaining the distribution parameters comprises obtaining the distribution parameters based on an almost concentrated differential privacy (ACDP) approach (col 12, line 51-col 13, line 24).
7. Rachlin discloses the computer-implemented method of claim 1, wherein determining whether the actual value of the first differential privacy parameter satisfies the first target differential privacy parameter comprises determining multiple values of a Renyi divergence order until a stop condition is reached (col 7, lines 18-32).
9. Rachlin discloses the computer-implemented method of claim 1, wherein for each of multiple values of the second binomial distribution parameter, determining, based on the value of the second binomial distribution parameter, the actual value of the first actual differential privacy parameter comprises: performing a first procedure to iterate through the multiple values of the second binomial distribution parameter; and for each iteration of the first procedure, calling a second procedure to determine the actual value of the first actual differential privacy parameter, wherein calling the second procedure comprises providing, as input to the second procedure, the value of the second binomial distribution parameter, a value of the first binomial distribution parameter, and a value of a second target differential privacy parameter that represents a probability of a privacy leakage (col 10, line 45-col 11, line 29).
10. Rachlin discloses the computer-implemented method of claim 9, wherein the second procedure comprises determining a Renyi divergence between two truncated binomial distributions and updating the value of the first actual differential privacy parameter based on the Renyi divergence (col 7, lines 18-32).
Claims 11-13, 15-17, 19-20 are similar in scope to claims 1-3, 5-7, 9-10 and are rejected under similar rationale.
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) 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rachlin as applied to claim 3 and 13 above, and further in view of Kasiviswanathan et al. (US 2018/0181878) hereafter Kasiviswanathan.
4. Rachlin discloses the computer-implemented method of claim 3, but does not explicitly disclose wherein the data for the digital components comprises network data measurement data for the digital components. However, in an analogous art, Kasiviswanathan discloses privacy preserving transformation including wherein the data for the digital components comprises network data measurement data for the digital components (para 63, audience measurements, voice commands, network measurements). It would have been obvious to a person of ordinary skill in the art before the effective filing date to modify the implementation of Rachlin with the implementation of Kasiviswanathan because it would be obvious to substitute one known equivalent (data) for another known equivalent (data) (MPEP 2144.06).
Claim 14 is similar in scope to claim 4 and is rejected under similar rationale.
Claim(s) 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rachlin as applied to claims 1 and 11 above, and further in view of How Much is Enough? Choosing E for Differential Privacy by Lee et al. hereafter Lee.
8. Rachlin discloses the computer-implemented method of claim 1, but does not explicitly disclose wherein determining an actual value of a first actual differential privacy parameter comprises performing a binary search for the first actual differential privacy parameter. However, in an analogous art, Lee discloses choosing a privacy parameter by using a binary search (page 336, we can perform binary search to determine the maximum ϵ that meets the requirement). It would have been obvious to a person of ordinary skill in the art before the effective filing date to modify the implementation of Rachlin with the implementation of Lee in order to find the parameter with speed, scalability, and efficiency of O(logn).
Claim 18 is similar in scope to claim 8 and is rejected under similar rationale.
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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