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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 02/12/2025 and 06/20/2025 have been made record of and considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 -6 are rejected under 35 USC 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed towards a "computer-readable medium" that comprises “a program” which, when executed by a computing device, cause the computing device to perform a process, which broadly encompasses a computer program per se. Such computer programs, per se, are not, in and of themselves, methods or machines, nor are they physical products of manufacture or compositions of matter. Therefore, such programs do not fall into any of the categories of eligible subject matter define din 35 US C 101 are not, by themselves, eligible for patent protection. Such programs can be eligible for patent protection if claims as embodied on or in a computer-readable storage device or medium, but only if the claim clearly and unambiguously excludes transitory, propagating signals from the full scope of the claimed subject matter, as such signals are not eligible under 35 USC 101. It is suggested that amending the claim language to define the computer program embodied on a "non-transitory computer-readable medium" would satisfy these requirements and would limit the claimed invention to eligible subject matter.
Claim(s) 1 and 6-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental processes (concepts performed in a human mind, including as an observation, evaluation, judgment, opinion, organizing human activity, and/or mathematical concepts and calculations).
Independent claims 1, 7, and 8 recite obtaining and comparing classification information, selecting information based on relationships, comparing certainty information, and making a determination based on a condition. This is collecting information, analyzing and classifying the information, comparing the classification information, and making a determination of validity based on a condition. In other words, a person can classify frames, compare classification results, find that a mathematical condition is not satisfied by the relationship between a first and second classification result, and determine the frames to be invalid. Further, the judicial exception is not integrated into a practical application. The claims disclose that the process is performed by a "A computer-readable recording medium having stored therein a program for causing a computer to execute a process" and is used for a "first and second machine learning classifier" but it does not recite how the system improves patch attack detection in a technical way. The condition that must be satisfied to determine invalidity is ambiguous. The additional recitation of an information processing device, memory, and processor” merely applies the abstract idea using generic computer technology and limits the idea to the field of information processing without reciting a specific improvement to functionality or another technology. Therefore, claims 1 and 6-8 are rejected under 35 USC 101.
Allowable Subject Matter
Claims 1-8 would be allowable if amended to address the 35 U.S.C. 101 rejections above.
As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
The following is an examiner’s statement of reasons for allowance:
Hoory (‘Dynamic Adversarial Patch for Evading Object Detection Models’) discloses methods for dynamic attacks, which may adjust themselves to the situation for optimal results.
Koseki (US 2024/0064157 A1) discloses an attack detection device/system. The device includes “an anomalous pattern detection unit to detect whether an anomalous pattern is included in a time-series recognition score that is time-series data generated using a plurality of recognition scores calculated respectively using a plurality of pieces of image data captured of a range within an image-capture range at mutually different time points within an image-capture time range, the plurality of recognition scores indicating results of detecting objects respectively in the plurality of pieces of image data, the anomalous pattern being a pattern that occurs when an adversarial sample patch attack has been conducted against at least one of the plurality of pieces of image data (¶8).”
Baker (US 2023/0289434 A1) discloses a “diverse set of neural networks trained to be individually robust against adversarial attacks and diverse in a manner that decreases the ability of an adversarial example to fool the full diverse set.”
Neither Hoory, Koseki, nor Baker, neither alone nor in combination, discloses a computer-readable recording medium having stored therein a program for causing a computer to execute a process, the process comprising:
using a first machine learning model and thereby obtaining, for each frame of a series of frames, a first classification result in which a first set of two or more classes into which an object in the each frame is classified is correlated with respective degrees of certainty of the two or more classes of the first set, the first set of the two or more classes being among a plurality of classes, and the first machine learning model calculating, for each class of the plurality of classes, a degree of certainty that the object in the each frame is classified into the each class of the plurality of classes;
using a second machine learning model and thereby obtaining, for the each frame of the series of frames, a second classification result in which a second set of two or more classes into which the object in the each frame is classified is correlated with respective degrees of certainty of the two or more classes of the second set, the second set of two or more classes being of the plurality of classes, and the second machine learning model being different from the first machine learning model and calculating, for the each class of the plurality of classes, a degree of certainty that the object in the each frame is classified into the each class;
based on the obtained first classification result and the obtained second classification result, identifying, among the series of frames, a first frame whose class with a highest degree of certainty is different in the first classification result and the second classification result and differs in the first classification result from that of a second frame whose class with the highest degree of certainty is identical in the first classification result and in the second classification result; and
determining the series of frames to be invalid when a condition is satisfied by a relationship between a first degree of certainty of a first class in the first classification result for the identified first frame and a second degree of certainty of the first class in the first classification result for a third frame that is immediately before or immediately after the identified first frame, and determining the series of frames to be not invalid when the condition is not satisfied by the relationship, the first class being the class, of the second frame, with the highest degree of certainty in the first classification result.
Accordingly, the features identified, in combination with other claim limitations, are neither suggested nor discussed by the prior art of record.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASHLEY HYTREK whose telephone number is (703)756-4562. The examiner can normally be reached M-F 9:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Steve Koziol can be reached at (408)918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ASHLEY HYTREK/Examiner, Art Unit 2665
/Stephen R Koziol/Supervisory Patent Examiner, Art Unit 2665
