DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Action is Final and is in response to the claims filed 03/30/2026. Claims 1-14 are currently pending, of which claims 1-14 are currently rejected.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/30/2026 has been entered.
Response to Arguments
Applicant's arguments filed 11/21/2025 have been fully considered but they are not persuasive.
Claim objections: Claim objections have been withdrawn necessitated by amendments.
35 U.S.C. 112(a): Applicant’s arguments regarding the 35 U.S.C. 112(a) rejection have been fully considered and are persuasive. Rejection under 35 U.S.C. 112(a) has been withdrawn.
35 U.S.C. 112(b): Rejections under 35 U.S.C. 112(b) have been withdrawn necessitated by amendments.
35 U.S.C. 103: Applicant’s arguments regarding the 35 U.S.C. 103 rejection have been fully considered, but they are not persuasive.
Applicant argues in page 9 how the cited references do not teach amended claim 1. Applicant specifically argues “Turan is directed to a NIST recommendation that describes software-level algorithms for entropy source health testing. Turan does not describe hardware circuitry, nor does it describe a health test circuit comprising a serial-parallel converter, a repetition count test circuit, and an adaptive proportion test circuit arranged in the manner recited in amended claim 1.”
Examiner respectfully disagrees. Examiner did not state Turan teaches these tests are done in hardware, but are rather software algorithms. Examiner states combination of Herbert in view of Turan teach these algorithms done in hardware. See Final rejection mailed on 12/29/2025.
Applicant further argues in page 10 that Turan teaches an adaptive proportion test does not teach detecting occurrences of n-bit data simultaneously. Applicant specifically argues “With respect to Turan's Adaptive Proportion Test in particular, the test as described in Section 4.4.2 of Turan takes a single sample value and counts how many times that same value recurs within the next W-1 samples in a window. The pseudocode at page 27 of Turan confirms this operation: the test sets A = next(), then iterates through the window and increments a counter B each time A equals the next sample. The test thus tracks only one value per window. This is fundamentally different from the claimed adaptive proportion test circuit, which is configured to receive the n-bit data from the serial-parallel converter and detect a number of occurrences of "each value among 2n values" represented by the n-bit data. That is, the claimed adaptive proportion test circuit simultaneously tracks occurrences of all 2n possible values, not just one value per window as in Turan.”
Examiner respectfully disagrees. Turan teaches an adaptive proportion test that detects the number of occurrences of a sample gathered from a number of samples. Turan explains “Samples collected from the noise source during on demand health tests shall not be available for use until the tests are completed”. See Turan Page 23, Third paragraph. Turan further explains “The test takes a sample from the noise source, and then counts the number of times that the same value occurs within the next W-1 samples”. See Turan Page 26, Section 4.4.2. Hence, more than one sample is received, causing for the adaptive proportion test to determine the number of occurrences of all samples (2n values). See 35 U.S.C. 103 rejection below.
Further, Applicant argues in page 10 that the proposed combination uses impermissible hindsight reasoning. Applicant specifically argues “Furthermore, the combination proposed by the Office appears to be based on impermissible hindsight reasoning, using the present application's own disclosure as a guide. Neither Herbert nor Turan identifies the problem recognized by the present application, namely, that conventional health testing operating on 1-bit samples fails to detect periodic data patterns such as "10101010" that have low randomness but nonetheless pass both the repetition count test and the adaptive proportion test at the 1-bit level.”
Examine respectfully disagrees. Examiner explains in the Final rejection mailed on 12/29/2025 the motivation for combination provided directly from Turan and Tkacik to combine the references.
Claim Rejections - 35 USC § 103
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 1-6 and 9-14 are rejected under 35 U.S.C. 103 as being unpatentable over Herbert et al. (U.S. Patent Application Publication No.: US 20100332574 A1), hereinafter “Herbert”, further in view of Meltem Sönmez Turan in NPL: “Recommendation for the Entropy Sources Used for Random Bit Generation” (nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-90B.pdf), hereinafter “Turan”.
Regarding Claim 1, Herbert teaches:
A semiconductor device comprising: a random number generator that generates random number data which is serial data (Fig. 1, e.g., shows Entropy source 102 (random number generator) and data signal 108 (random number data); ¶0026, e.g., Entropy source 102 generates random bits 108 in series);
a health test circuit for verifying a randomness of the random number data (Fig. 5, e.g., shows The entropy validation module 104 (health test circuit)),
wherein the health test circuit treats the random number data as a data string of n-bit data by dividing the random number data per n bits, where n is an integer larger than or equal to two (¶0048 and ¶0049, e.g., Serial-to-parallel converter module 500 converts (divides) stream of data (random number data) to a plurality of blocks (data strings) with a number (n) of bits in each block. Health check module 502 tests per block (string of n-bits)), …
wherein the health test circuit comprises:
(i) a serial-parallel converter that converts the random number data, which is serial data, into the n-bit data (¶0048, e.g., Serial-to-parallel converter module 500 converts stream of random bits (serial data) into blocks of data (n-bit data); Fig. 5);
wherein the health test circuit is configured to inhibit output of the random number data (¶0051, e.g., Control flow transfer module 504 permits forwarding of data if the health check module 502 indicates that the block passed the health check. Therefore, not passing the health check would prevent (inhibit) output of data) …
Herbert does not teach:
wherein a value of n is set in response to a bit length setting signal,
wherein the health test circuit comprises:
(ii) a repetition count test circuit configured to receive the n-bit data from the serial-parallel converter and detect when the same n-bit data value is generated consecutively; and
(iii) an adaptive proportion test circuit configured to receive the n-bit data from the serial-parallel converter and detect a number of occurrences of each value among 2n values represented by the n-bit data, and
…when a predetermined criterion for the repetition count test or the adaptive proportion test falls outside a predetermined range.
However, Turan teaches:
wherein a value of n is set in response to a bit length setting signal (Page 7, Section 2.3.2 GetNoise: An Interface to the Noise Source, e.g., GetNoise call returns samples with a specified length),
Therefore, it would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to which said subject matter pertains to combine the GetNoise function call to set the bit length as taught by Turan with the serial to parallel converter 500 as taught by Herbert. One would have been motivated to combine these references because both references disclose health testing in physical random number sequencies, and Turan enhances the model of Herbert because “This could be used to obtain raw, digitized outputs from the noise source for use in validation testing or for external health (i.e., testing performed external to the entropy source). While it is not required to be in this form, it is expected that an interface be available that allows noise source data to be obtained without harm to the entropy source.” (Turan: Page 7, Section 2.3.2 GetNoise: An Interface to the Noise Source). Combination would cause for GetNoise function call to set a bit length to be performed in hardware (circuits), hence it would be implemented as a signal.
Turan further teaches:
(ii) a repetition count test [algorithm] configured to … detect when the same n-bit data value is generated consecutively (Page 25, 4.4.1 Repetition Count Test, First paragraph, e.g., Repetition Count Test detects when the source becomes "stuck" on a single output (generated consecutively)); and
(iii) an adaptive proportion test [algorithm] configured to … detect a number of occurrences of each value among 2^n values represented by the n-bit data (Page 26, 4.4.2 Adaptive Proportion Test, Second paragraph, e.g., Adaptive Proportion Test counts the number of times (detects number of occurrences) the same value occurs within the next W-1 samples (2n values)), and
wherein the health test [algorithm] is configured to inhibit output of the random number data when a predetermined criterion for the repetition count test or the adaptive proportion test falls outside a predetermined range (Page 25, Section 4.4.1 Repetition Count Test, e.g., Test fails if a sample of bits is repeated C or more times (predetermined range); Page 25, Section 4.4 Approved Continuous Health Tests, e.g., both the repetition count test and the adaptive proportion test should be included in the health tests).
Therefore, it would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to which said subject matter pertains to include the both the repetition count test and the adaptive proportion test as taught by Turan with the health check module 502 as taught by Herbert. One would have been motivated to combine these references because both references disclose health testing in physical random number sequencies, and Turan enhances the model of Herbert because “This recommendation provides two approved health tests: the Repetition Count test, and the Adaptive Proportion test. If these two health tests are included among the continuous health tests of the entropy source, no other tests are required.” (Turan: Page 25, Section 4.4 Approved Continuous Health Tests). Combination would cause for the repetition count test and the adaptive proportion test to be performed in hardware (circuits), and would cause for each test to receive blocks of data provided by the serial-to-parallel converter module 500 as taught by Herbert.
Regarding Claim 2, Herbert in view of Turan teach:
The semiconductor device according to claim 1, wherein the repetition count test circuit and the adaptive proportion test circuit are configured to have different values of n of the n-bit data (Turan: Page 7, Section 2.3.2 GetNoise: An Interface to the Noise Source, e.g., GetNoise call returns samples with a specified length).
Regarding Claim 3, Herbert in view of Turan teach:
The semiconductor device according to claim 1, wherein the repetition count test circuit is configured to compare the detected consecutive number with a predetermined threshold and generate a fail result when the detected consecutive number exceeds the threshold (Turan: Page 25, Section 4.4.1 Repetition Count Test, e.g., Repetition Count Test detects when the source becomes "stuck" on a single output (generated consecutively), and the Test fails if a sample (number) is repeated C or more times (predetermined range)).
Regarding Claim 4, Herbert in view of Turan teach:
The semiconductor device according to claim 1, wherein the adaptive proportion test circuit detects a number of occurrences of at least one value among 2n values and compares the number of occurrences with a predetermined threshold (Turan: Page 26 Section 4.4.2 Adaptive Proportion Test, e.g., Adaptive Proportion Test fails if a sample (number) is counted to occur more than the cutoff value C (predetermined threshold) within the W-1 samples (2n values)).
Regarding Claim 5, Herbert in view of Turan teach:
The semiconductor device according to claim 4, wherein the adaptive proportion test circuit compares the detected number of occurrences for each of the 2n values with a corresponding predetermined threshold (Turan: Page 26 Section 4.4.2 Adaptive Proportion Test, e.g., Adaptive Proportion Test fails if a sample (number) is counted to occur more than the cutoff value C (predetermined threshold) within the W-1 samples (2n values); Page 23, First and Second Paragraphs, e.g., All samples are tested. Samples are outputted from the entropy source as they are generated).
Regarding Claim 6, Herbert in view of Turan teach:
The semiconductor device according to claim 5, wherein the health test circuit compares a sum of the number of occurrences of sum of the number of occurrences of each of the 2n values with an expected value (Turan: Algorithm in page 27, e.g., Performs B=B+1 (sum of the number of occurrences) of each of the values in the W-1 values (2n values); Page 26, 4.4.2 Adaptive Proportion Test, Second paragraph), and generates a fail result when the sum deviates from the expected value (Turan: Algorithm in page 27, e.g., algorithm signals failure if B ≥ C)
Regarding Claims 9-14, they are method claims practiced by the apparatus of claims 1-6. They are rejected for the same reasons as claims 1-6.
Claims 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Herbert in view of Turan, further in view of Tkacik et al. (U.S. Patent Application Publication No.: US 20140164458 A1), hereinafter “Tkacik”.
Regarding Claim 7, Herbert in view of Turan teach:
The semiconductor device according to claim 1, wherein the random number generator is configured to switch at least one of characteristics of the randomness in response to a characteristic setting signal from the health test circuit (Herbert: ¶0031, e.g., Latch module 200 receives Tune A and Tune B signals (characteristic setting signal) that indicate how to bias the next clock cycle; Fig. 2, e.g., Latch module 200 is inside Entropy Source 102 (Random number generator)),
Herbert in view of Turan do not teach:
wherein the health test circuit transmits the characteristic setting signal to the random number generator when a predetermined criterion for the repetition count test or the adaptive proportion test falls outside a predetermined range.
However, Tkacik teaches:
wherein the health test circuit transmits the characteristic setting signal to the random number generator when a predetermined criterion for the repetition count test or the adaptive proportion test falls outside a predetermined range (¶0040, e.g., Entropy quality testing module (health test circuit) sends signal 270 (characteristic setting signal), to Sampling Parameter setting and retry module to create new sampling parameter value 272 for the entropy bit generator (random number generator); Fig. 2, e.g., Entropy quality Testing Module (Health test circuit) outputs signal 270 (characteristic setting signal)).
Therefore, it would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to which said subject matter pertains to combine signal 270 provided by the entropy quality testing module as taught by Tkacik with the entropy source 102 as taught by Herbert in view of Turan. One would have been motivated to combine these references because both references disclose health testing in physical random number sequencies, and Tkacik enhances the model of Herbert in view of Turan by allowing the entropy source to “produce one or more new sets of test bits without changing the sampling parameter, in order to allow the system to attempt to produce a set of test bits that will pass the tests conducted” (Tkacik: ¶0030).
Regarding Claim 8, Herbert in view of Turan in view of Tkacik teach:
The semiconductor device according to claim 7, wherein the random number generator comprises two logic gates constituting an SR latch (Herbert: ¶0032, e.g., Fig. 3 shows Latch circuit (SR Latch) of Fig. 2; Fig. 3, e.g., shows two inverters ia and ib (two logic gates)) and variably sets bidirectional propagation delay time between the two logic gates in accordance with the characteristic setting signal (Herbert: ¶0031, e.g., Latch Module 200 receives Delayed Clock (propagation delay time); Fig. 3, e.g., clock signal (delayed clock) enables inputs (variably sets) for each inverter (bidirectional)).
Prior Art made of Record
US 20020184273 A1 – teaches using a serial-parallel converter for converting serial digitized serial random number signals to parallel signals. See ¶0044 and Fig. 2.
Conclusion
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/C.H.D./
Carlos H. De La GarzaExaminer, Art Unit 2182 (571)272-0474
/EMILY E LAROCQUE/Primary Examiner, Art Unit 2182
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