CTNF 18/520,753 CTNF 93612 DETAILED ACTION Notice of Pre-AIA or AIA Status 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. This communication is a First Action Non-Final on the merits. Claims 1-20 as originally filed on November 28, 2023, are currently pending and have been considered below. Information Disclosure Statement The information disclosure statement (IDS) submitted on 11/28/2023 and 1/14/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites method for providing unique function identifier. Step 2A – Prong 1 Independent Claims 1, 8 and 15 as a whole recite a method of organizing human activity. The limitations from exemplary Claim 1 reciting “using intermediate representations, extracting functions included; generating dataflows for the extracted functions, respectively; generating dataflow graphs for the generated dataflows, respectively; converting the dataflow graphs into respective sets of embeddings; populating a knowledge base with the sets of embeddings; and using a first similarity function, a second similarity function, and the populated knowledge base, determining that an unlabeled matches” is a method of managing interactions between people, which falls into the certain methods of organizing human activity grouping, additionally mathematical concepts such as mathematical relationships, mathematical formulas or equations and mathematical calculations as the machine learning model can be computed using pen and paper to provide a mathematical creation of unique function using dataflows and identifiers. The mere recitation of a generic computer (computer system, processors, storage media, computer readable code, application binaries, applications and data repository of claim 1; computer program product, computer readable storage media, computer readable program code, processors, computer system, application binaries, applications and data repository of claim 8; computer implemented method, application binaries, applications and data repository of claim 15) does not take the claim out of the methods of organizing human activity grouping. Thus, the claim recites an abstract idea. Step 2A - Prong 2: Claims 1-20 and their underlining limitations, steps, features and terms, are further inspected by the Examiner under the current examining guidelines, and found, both individually and as a whole, not to include additional elements that are sufficient to integrate the abstract idea into a practical application. The limitations are directed to limitations referenced in MPEP 2106.05 that are not enough to integrate the abstract idea into a practical application. Limitations that are not enough include, as a non-limiting or non-exclusive examples, such as: (i) adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions, (ii) insignificant extra solution activity, and/or (iii) generally linking the use of the judicial exception to a particular technological environment or field of use. This judicial exception is not integrated into a practical application because the claim recites the additional elements of (computer system, processors, storage media, computer readable code, application binaries, applications and data repository of claim 1; computer program product, computer readable storage media, computer readable program code, processors, computer system, application binaries, applications and data repository of claim 8; computer implemented method, application binaries, applications and data repository of claim 15). The computer system, processors, storage media, computer readable code, application binaries, applications and data repository of claim 1; computer program product, computer readable storage media, computer readable program code, processors, computer system, application binaries, applications and data repository of claim 8; computer implemented method, application binaries, applications and data repository of claim 15, are recited at a high level of generality and are generically recited computer elements. The generically recited computer elements amount to simply implementing the abstract idea on a computer. The combination of these additional elements are additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use. Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use. Thus, even when viewed as an ordered combination, nothing in the claims add significantly more (i.e. an inventive concept) to the abstract idea. The claims are ineligible. Dependent claims 2-7, 9-14 and 16-20 are also directed to same grouping of methods of organizing human activity. The additional elements of the computer system in claims 2-7, 9-14; processors in claims 2-5, 7, 9-12, 14, 16-19; computer readable code in claims 2-5, 7, 9-12, 14; application binaries in claims 2-3, 9-10, 16-17; computer program product in claims 9-14; computer implemented method in claims 16-20, are additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use. Accordingly, in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. 07-06 AIA 15-10-15 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 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. 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 – 07-08-aia AIA (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. 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, 6, 8-10, 13, 15-17 and 20 are rejected under 35 U.S.C. 102 (a)(2) as being anticipated by Zou et al (CN Publication No. 11346852 - hereinafter Zou) . Re. claim 1, 8 and 15, Zou discloses: A computer system comprising: one or more computer processors; [Zou; Abstract] one or more computer readable storage media; and [Zou; Abstract] computer readable code stored collectively in the one or more computer readable storage media, with the computer readable code including data and instructions to cause the one or more computer processors to perform at least the following operations: [Zou; Abstract] using intermediate representations of application binaries of respective applications, extracting functions included in the application binaries; [Zou; ¶0010 shows obtain number of known vulnerability functions and the vulnerability points of each known vulnerability function, the binary file containing the known vulnerability function]. generating dataflows for the extracted functions, respectively; generating dataflow graphs for the generated dataflows, respectively; [Zou; ¶0010 shows extract the function call graph of each binary file converting the dataflow graphs into respective sets of embeddings and populating a knowledge base in a data repository with the sets of embeddings]. converting the dataflow graphs into respective sets of embeddings; populating a knowledge base in a data repository with the sets of embeddings; and [Zou; ¶0010 shows obtain each known vulnerability function and the parent function and child of the vulnerability function Lightweight feature vector of the function]. using a first similarity function, [Zou; ¶0012 shows 3)traverse the function call graph of the binary file to be detected, and obtain the first potential similarity by calculating the lightweight feature vector distance between each function to be detected and each known vulnerability function]. a second similarity function, and the populated knowledge base, determining that an unlabeled application binary matches one of the application binaries. [Zou; ¶0013 shows "4) According to the function call graph of the binary file to be detected, obtain the lightweight feature vector of the parent function and child function of the first potentially similar vulnerable function, and compare it with the lightweight feature vector of the parent function and child function of each known vulnerable function Compare, get the second potential similar vulnerability function"]. Re. claim 2, 9 and 16, Zou further discloses: wherein the computer readable code including the data and the instructions causes the one or more computer processors to perform the determining that the unlabeled application binary matches one of the application binaries by performing at least the following operations: using the first similarity function, determining measurements of similarity between (i) sets of embeddings associated with an entirety of functions included in the unlabeled application binary and (ii) a set of embeddings included in the populated knowledge base; determining that each of the measurements of similarity does not exceed a threshold similarity measurement; and based on each of the measurements of similarity not exceeding the threshold similarity measurement, designating the set of embeddings included in the populated knowledge base as being dissimilar to each of the sets of embeddings associated with the entirety of functions included in the unlabeled application binary and preventing the designated set of embeddings included in the populated knowledge base from being placed in a subset of the populated knowledge base and from being further processed in an application of the second similarity function, which provides measurements of similarity between the unlabeled application binary and application binaries associated with sets of embeddings included in the subset of the populated knowledge base. [Zou; shows utilizing the threshold such as “In the coarse-grained similar vulnerability function screening stage, each function to be tested in the database is taken out, as shown in Figure 5, and the lightweight feature distance between each function to be tested and known vulnerability functions is calculated. If the distance is less than the preset The threshold value of the candidate function is considered to be a potentially similar vulnerability function, and the next stage of fine-grained similar vulnerability function identification is performed on it, otherwise the function to be tested is discarded. Coarse-grained similar vulnerability function screening includes: First, the set of functions to be tested and its lightweight features are taken out from the database; for each feature in the lightweight features, the distance between the function to be tested and the known vulnerability function on this feature is calculated; the distance of the four features consists of A four-dimensional vector, calculate the weighted Euclidean distance between the four-dimensional vector and the origin, as the lightweight feature distance between the function to be tested and the known vulnerability function; when the distance is greater than the preset threshold, discard the function to be tested, so as to achieve A filter for the collection of functions to be tested”]. Re. claim 3, 10 and 17, Zou further discloses: wherein the computer readable code including the data and the instructions causes the one or more computer processors to perform the determining that the unlabeled application binary matches one of the application binaries by performing at least the following operations: using the first similarity function, determining a measurement of similarity between (i) a set of embeddings associated with a function included in the unlabeled application binary and (ii) a set of embeddings included in the populated knowledge base; determining that a measurement of similarity exceeds a threshold similarity measurement; and based on the measurement of similarity exceeding the threshold similarity measurement, designating the set of embeddings included in the populated knowledge base as being similar to the set of embeddings associated with the function included in the unlabeled application binary and placing the designated set of embeddings included in the populated knowledge base into a subset of the populated knowledge base, the subset of the populated knowledge base being permitted to be further processed in an application of the second similarity function, which provides measurements of similarity between the unlabeled application binary and application binaries associated with sets of embeddings included in the subset of the populated knowledge base. [Zou; shows utilizing the threshold such as “In the coarse-grained similar vulnerability function screening stage, each function to be tested in the database is taken out, as shown in Figure 5, and the lightweight feature distance between each function to be tested and known vulnerability functions is calculated. If the distance is less than the preset The threshold value of the candidate function is considered to be a potentially similar vulnerability function, and the next stage of fine-grained similar vulnerability function identification is performed on it, otherwise the function to be tested is discarded. Coarse-grained similar vulnerability function screening includes: First, the set of functions to be tested and its lightweight features are taken out from the database; for each feature in the lightweight features, the distance between the function to be tested and the known vulnerability function on this feature is calculated; the distance of the four features consists of A four-dimensional vector, calculate the weighted Euclidean distance between the four-dimensional vector and the origin, as the lightweight feature distance between the function to be tested and the known vulnerability function; when the distance is greater than the preset threshold, discard the function to be tested, so as to achieve A filter for the collection of functions to be tested”]. Re. claim 6, 13 and 20, Zou further discloses: wherein the first similarity function determines similarity measurements by employing a Jaccard distance, an L1-norm Manhattan distance and the second similarity function determines similarity measurements by employing a distance selected from the group consisting of a cosine distance, an L2-norm Euclidean distance, an L1-norm Manhattan distance, a dot product distance, and an extended Jaccard distance. [Zou; shows “calculation method of feature distance is: for digital features such as in-degree and out-degree, Manhattan distance is used; for collective features such as import functions and string constants, Jaccard distance is used] . 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. 07-23-aia AIA The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim s 4-5, 11-12 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Zou in view of Ruiz et al (US Patent Application Publication No. 2023260608 - hereinafter Ruiz) . Re. claim 4, 11 and 18, Zou teaches the system of Claim 1. Zou doesn’t teach, Ruiz teaches: wherein the computer readable code including data and instructions causes the one or more computer processors to perform at least the following further operation: capturing information about a structure of a given dataflow graph included in the generated dataflow graphs while ignoring identifiers of nodes and identifiers of edges in the given dataflow graph, wherein the capturing the information includes capturing types of the nodes, types of the edges, total numbers of nodes of one or more of the types of the nodes, and total numbers of edges of one or more of the types of the edges, and wherein the converting the dataflow graphs is based on the captured information about the structure of the given dataflow. [Ruiz; ¶92 shows graph with nodes and edges]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include limitation(s) as taught by Ruiz in the system of Zou, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Re. claim 5, 12 and 19, Zou teaches the system of Claim 1. Zou doesn’t teach, Ruiz teaches: wherein the computer readable code including data and instructions causes the one or more computer processors to perform at least the following further operation: capturing information about a structure of a given dataflow graph included in the generated dataflow graphs by generating, in a pattern rather than in a random order, identifiers of nodes and identifiers of edges in the given dataflow graph, wherein the capturing the information includes capturing type information about a head node and a tail node for a given edge included in the edges in the given dataflow graph and associating the type information about the head and tail nodes with a type of the given edge, and wherein the converting the dataflow graphs is based on the captured information about the structure of the given dataflow. [Ruiz; ¶92]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include limitation(s) as taught by Ruiz in the system of Zou, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable . 07-21-aia AIA Claim s 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Zou in view of Carter et al (US Patent Application Publication No. 20230005312 - hereinafter Carter) . Re. claim 7 and 14, Zou teaches the system of Claim 1. Zou doesn’t teach, Carter teaches: wherein the computer readable code including data and instructions causes the one or more computer processors to perform at least the following further operation: using a given set of embeddings converted from a given dataflow graph generated for a given dataflow for a given function, generating a dataflow-based signature of the given function, wherein the given dataflow specifies data flowing into variables and registers and being passed to and returned from other functions. [Carter; ¶147]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include limitation(s) as taught by Carter in the system of Zou, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to IBRAHIM EL-BATHY whose telephone number is (571)272-7545. The examiner can normally be reached Monday - Friday 9am - 7pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached at 571-270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /IBRAHIM N EL-BATHY/Primary Examiner, Art Unit 3628 Application/Control Number: 18/520,753 Page 2 Art Unit: 3628 Application/Control Number: 18/520,753 Page 3 Art Unit: 3628 Application/Control Number: 18/520,753 Page 4 Art Unit: 3628 Application/Control Number: 18/520,753 Page 5 Art Unit: 3628 Application/Control Number: 18/520,753 Page 6 Art Unit: 3628 Application/Control Number: 18/520,753 Page 7 Art Unit: 3628 Application/Control Number: 18/520,753 Page 8 Art Unit: 3628 Application/Control Number: 18/520,753 Page 9 Art Unit: 3628 Application/Control Number: 18/520,753 Page 10 Art Unit: 3628 Application/Control Number: 18/520,753 Page 11 Art Unit: 3628 Application/Control Number: 18/520,753 Page 12 Art Unit: 3628 Application/Control Number: 18/520,753 Page 13 Art Unit: 3628 Application/Control Number: 18/520,753 Page 14 Art Unit: 3628 Application/Control Number: 18/520,753 Page 15 Art Unit: 3628
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