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 .
DETAILED ACTION
Claims 31-46 are subject to examination. Group I which contains claims 31-34 and 39-42 and Group II which contains claims 35-38 and 43-46. Group II which contains claims 35-38 and 43-46 was not elected by Applicant without traverse and thus are withdrawn. Claims 31-34 and 39-42 are elected by the Applicant without traverse.
This non-final action is in response to election of restriction filed on 10/02/2025. Claims 31-34 and 39-42 are pending, with claims 31 and 39 being independent.
Priority
This application claims the benefit of PCT/IB2021/054489, filed 05/24/2021.
Election/Restriction
REQUIREMENT FOR UNITY OF INVENTION
As provided in 37 CFR 1.475(a), a national stage application shall relate to one invention only or to a group of inventions so linked as to form a single general inventive concept (“requirement of unity of invention”). Where a group of inventions is claimed in a national stage application, the requirement of unity of invention shall be fulfilled only when there is a technical relationship among those inventions involving one or more of the same or corresponding special technical features. The expression “special technical features” shall mean those technical features that define a contribution which each of the claimed inventions, considered as a whole, makes over the prior art.
The determination whether a group of inventions is so linked as to form a single general inventive concept shall be made without regard to whether the inventions are claimed in separate claims or as alternatives within a single claim. See 37 CFR 1.475(e).
When Claims Are Directed to Multiple Categories of Inventions:
As provided in 37 CFR 1.475 (b), a national stage application containing claims to different categories of invention will be considered to have unity of invention if the claims are drawn only to one of the following combinations of categories:
(1) A product and a process specially adapted for the manufacture of said product; or
(2) A product and a process of use of said product; or
(3) A product, a process specially adapted for the manufacture of the said product, and a use of the said product; or
(4) A process and an apparatus or means specifically designed for carrying out the said process; or
(5) A product, a process specially adapted for the manufacture of the said product, and an apparatus or means specifically designed for carrying out the said process.
Otherwise, unity of invention might not be present. See 37 CFR 1.475 (c).
Restriction is required under 35 U.S.C. 121 and 372.
This application contains the following inventions or groups of inventions which are not so linked as to form a single general inventive concept under PCT Rule 13.1.
In accordance with 37 CFR 1.499, applicant is required, in reply to this action, to elect a single invention to which the claims must be restricted.
Group I, claims 31-34 and 39-42, drawn to calculate an optimized configuration parameter based on an indication that at least one of the cognitive functions is suspected for manipulative behavior, classified in H04L 41/0803 {Configuration setting}.
Group II, claims 35-38 and 43-46, drawn to determining cognitive function is suspected for manipulative behavior, classified in H04L 41/147 {for predicting network behaviour}.
The groups of inventions listed above do not relate to a single general inventive concept under PCT Rule 13.1 because, under PCT Rule 13.2, they lack the same or corresponding special technical features for the following reasons:
Group I and II lack unity of invention because even though the inventions of these groups require the technical feature of receiving an indication that at least one of the cognitive functions is suspected for manipulative behavior, this technical feature is not a special technical feature as it does not make a contribution over the prior art in view of Grosse et al. (US2021/0303695). For instance, Grosse teaches a determination is made as to whether the trained machine learning model is vulnerable to specific types of threats/attacks (fig. 18 and para. [0147]) and also teaches an evasion attack on a cognitive computer system, e.g., on the neural network or other machine learning or deep learning computer model (hereafter simply referred to as a “model”) implemented by the cognitive computer system, involves the attacker attempting to fool the model to misclassify a manipulated input and whether the machine learning model can be manipulated in a way to make the statistical test fail (para. [0034&0090]).
Applicant is advised that the reply to this requirement to be complete must include (i) an election of a species or invention to be examined even though the requirement may be traversed (37 CFR 1.143) and (ii) identification of the claims encompassing the elected invention.
The election of an invention or species may be made with or without traverse. To preserve a right to petition, the election must be made with traverse. If the reply does not distinctly and specifically point out supposed errors in the restriction requirement, the election shall be treated as an election without traverse. Traversal must be presented at the time of election in order to be considered timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are added after the election, applicant must indicate which of these claims are readable on the elected invention or species.
Should applicant traverse on the ground that the inventions have unity of invention (37 CFR 1.475(a)), applicant must provide reasons in support thereof. Applicant may submit evidence or identify such evidence now of record showing the inventions to be obvious variants or clearly admit on the record that this is the case. Where such evidence or admission is provided by applicant, if the examiner finds one of the inventions unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other invention.
This restriction is being made FINAL.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/01/2023 and 04/14/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 31-34 and 39-42 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 48, 52 and 54 of Application No. 18561865. Although the claims at issue are not identical, they are not patentably distinct from each other because:
Instant Application
Application No. 18561865
31. (Original) Apparatus comprising:
one or more processors, and
memory storing instructions that, when executed by the one or more processors, cause the apparatus to perform:
providing a configuration parameter and, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function to a behavioral anomaly detection function.
32. (Original) The apparatus according to claim 31, wherein the instructions, when executed by the one or more processors, further cause the apparatus to perform:
calculating an optimized value for the configuration parameter based on the received optimal configuration range sets.
33. (Original) The apparatus according to claim 32, wherein the instructions, when executed by the one or more processors, further cause the apparatus to perform:
monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior;
adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received;
setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received;
applying the final value of the configuration parameter to the system.
34. (Original) The apparatus according to claim 33, wherein the instructions, when executed by the one or more processors, further cause the apparatus to perform:
providing the optimized value of the configuration parameter to a configuration parameter tracking function, wherein the noise is received from a configuration parameter camouflaging function.
39. (Original) Method comprising:
providing a configuration parameter and, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function to a behavioral anomaly detection function.
40. (Original) The method according to claim 39, further comprising:
calculating an optimized value for the configuration parameter based on the received optimal configuration range sets.
41. (Original) The method according to claim 39, further comprising:
monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior;
adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received;
setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received;
applying the final value of the configuration parameter to the system.
42. (Original) The method according to claim 41, further comprising:
providing the optimized value of the configuration parameter to a configuration parameter tracking function, wherein the noise is received from a configuration parameter camouflaging function.
48. Method comprising:
receiving an information on a current state of a system;
retrieving, for each of the one or more cognitive functions, respective one or more stored triples for a configuration parameter of the system;
predicting, for each of the one or more cognitive functions, a respective expected value of the configuration parameter based on the current state of the system and the respective stored triples;
receiving a calculated optimized value for the configuration parameter;
reducing a potential degradation of a performance of the system based on the expected value for at least one of the one or more cognitive functions and the calculated optimized value for the configuration parameter, wherein for each of the one or more cognitive functions, each of the one or more stored triples comprises an information on a respective previous state of the system, a respective applied value of the configuration parameter, and a respective previous optimal configuration range set for the configuration parameter with respect to the respective cognitive function;
for each of the one or more cognitive functions, each of the optimal configuration range sets of the stored triples indicates a respective range of values for the configuration parameter desired previously by the respective cognitive function;
the configuration parameter defines at least a part of a configuration of the system;
the potential deterioration compares a first performance of the system under an assumption that none of the one or more cognitive functions has manipulative behavior with a second performance of the system under an assumption that at least one of the one or more cognitive functions has manipulative behavior.
52. The method according to claim 48, wherein the reducing the degradation comprises:
detecting, for at least one of the one or more cognitive functions, whether or not the calculated optimized value is trackable for the at least one of the cognitive functions based on the respective expected value;
instructing a configuration parameter camouflaging function to set a noise if, for the at least one of the one or more cognitive functions, the calculated optimized value is trackable.
54. The method according to claim 51, further comprising:
inhibiting the instructing the configuration parameter camouflaging function to set the
noise if, for each of the cognitive functions, the respective current triple is not trackable.
Claim Objections
Claims 32-33 and 40-41 objected to because of the following informalities:
Claims 32 and 40, “the received optimal configuration range sets” should be “the received optimal configuration range set”;
Claims 33 and 41, “the system” should be “system”.
Appropriate correction is required.
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 31-34 and 39-42 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
With respect to claim 31, the claim recites providing a configuration parameter and, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function to a behavioral anomaly detection function. The claim merely recites providing configuration parameter and optimal configuration range set from one function to another function. These limitations as a whole read on remote help desk assistance. For instance, the remote help desk assistance can receive the optimal configuration range set; then provide the configuration parameter and the optimal configuration range set for detecting manipulative behavior. These activities are human activities of a remote help desk assistance, which is a tentative abstract idea. Accordingly, the claim recites a judicial exception.
This judicial exception is not integrated into a practical application. The claim also recites additional elements apparatus comprising: one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the apparatus to perform. Apparatus, processors and memory are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component; and therefore, they are insignificant extra-solution activity. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements apparatus comprising: one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the apparatus to perform. Apparatus, processors and memory are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component; and therefore, they are insignificant extra-solution activity; and therefore, they are insignificant extra-solution activity. Therefore, the claim is not patent eligible.
Claim 32 depends on claim 31, thus is having the same issue as shown above. Further, the claim also recites calculating an optimized value for the configuration parameter based on the received optimal configuration range sets. This is an abstract idea including mental processes. For instance, a human can, in the human mind or on paper, calculate/ determine/ compute an optimized value for the configuration parameter based on the received optimal configuration range sets. Therefore, claim 32 also includes limitations are directed to an abstract idea without significantly more as discussed above. The claim does not include additional elements that integrate the abstract idea into a practical application or include additional elements that are sufficient to amount to significantly more than the judicial exception. Therefore, the claim is directed to an abstract idea and is not patent eligible.
Claim 33 depends on claim 32, thus is having the same issue as shown above. Further, the claim also recites monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior; adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received; setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received; applying the final value of the configuration parameter to the system. These elements clarify an abstract idea above, thus, are part of recitation of the abstract idea. Therefore, claim 33 also includes limitations are directed to an abstract idea without significantly more as discussed above.
Claim 34 depends on claim 33, thus is having the same issue as shown above. Further, the claim also recites providing the optimized value of the configuration parameter to a configuration parameter tracking function which merely recites providing optimized value of the configuration parameter to a function. Moreover, these limitations as a whole read on remote help desk assistance. For instance, the remote help desk assistance can provide information/ data/ optimized value of the configuration parameter for detecting manipulative behavior. These activities are human activities of a remote help desk assistance, which is a tentative abstract idea. Accordingly, the claim recites a judicial exception.
This judicial exception is not integrated into a practical application. The claim also recites additional element wherein the noise is received from a configuration parameter camouflaging function. The limitation merely recites receiving data from a function and therefore, they are insignificant extra-solution activity. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element wherein the noise is received from a configuration parameter camouflaging function. The limitation merely recites receiving data from a function and therefore, they are insignificant extra-solution activity. Therefore, the claim is not patent eligible.
With respect to claim 39, the claim recites providing a configuration parameter and, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function to a behavioral anomaly detection function. The claim merely recites providing configuration parameter and optimal configuration range set from one function to another function. These limitations as a whole read on remote help desk assistance. For instance, the remote help desk assistance can receive the optimal configuration range set; then provide the configuration parameter and the optimal configuration range set for detecting manipulative behavior. These activities are human activities of a remote help desk assistance, which is a tentative abstract idea. Accordingly, the claim recites a judicial exception.
This judicial exception is not integrated into a practical application. The claim does not include additional elements that integrate the abstract idea into a practical application or include additional elements that are sufficient to amount to significantly more than the judicial exception. Therefore, the claim is directed to an abstract idea and is not patent eligible.
Claim 40 depends on claim 39, thus is having the same issue as shown above. Further, the claim also recites calculating an optimized value for the configuration parameter based on the received optimal configuration range sets. This is an abstract idea including mental processes. For instance, a human can, in the human mind or on paper, calculate/ determine/ compute an optimized value for the configuration parameter based on the received optimal configuration range sets. Therefore, claim 32 also includes limitations are directed to an abstract idea without significantly more as discussed above. The claim does not include additional elements that integrate the abstract idea into a practical application or include additional elements that are sufficient to amount to significantly more than the judicial exception. Therefore, the claim is directed to an abstract idea and is not patent eligible.
Claim 41 depends on claim 39, thus is having the same issue as shown above. Further, the claim also recites monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior; adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received; setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received; applying the final value of the configuration parameter to the system. These elements clarify an abstract idea above, thus, are part of recitation of the abstract idea. Therefore, claim 41 also includes limitations are directed to an abstract idea without significantly more as discussed above.
Claim 42 depends on claim 41, thus is having the same issue as shown above. Further, the claim also recites providing the optimized value of the configuration parameter to a configuration parameter tracking function which merely recites providing optimized value of the configuration parameter to a function. Moreover, these limitations as a whole read on remote help desk assistance. For instance, the remote help desk assistance can provide information/ data/ optimized value of the configuration parameter to a function for manipulative behavior. These activities are human activities of a remote help desk assistance, which is a tentative abstract idea. Accordingly, the claim recites a judicial exception.
This judicial exception is not integrated into a practical application. The claim also recites additional element wherein the noise is received from a configuration parameter camouflaging function. The limitation merely recites receiving data from a function and therefore, they are insignificant extra-solution activity. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element wherein the noise is received from a configuration parameter camouflaging function. The limitation merely recites receiving data from a function and therefore, they are insignificant extra-solution activity. Therefore, the claim is not patent eligible.
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 of this title, 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 31 and 39 are rejected under 35 U.S.C. 103 as being unpatentable over Presley (US 2003/0105838, Pub. Date: Jun. 5, 2003), Banerjee et al. (NPL: On the Necessity and Design of Coordination Mechanism for Cognitive Autonomous Networks, Pub. Date: Jan. 20, 2020).
As per claim 31, Presley discloses apparatus comprising:
one or more processors (Presley fig. 2, processor of management system 11 and para. [0029], The management system 11 configures, validates and manages the configuration parameters of a plurality of systems interconnected over the internetwork 12), and
memory (Presley fig. 2, memory of management system 11 storing instructions that, when executed by the one or more processors, cause the apparatus to perform:
providing a configuration parameter and, for at least one of plural functions, a configuration range set for the configuration parameter received from the respective function (Presley para. [0036-0037], Upon discovering a new or changed component or server, the management configuration module 35 requests and receives the runtime configuration parameters 41 from the corresponding client module 37 … The configuration parameters 41 are validated against the master document type definitions 39 maintained in the database repository 38; Presley para. [0034], Each DTD 39 identifies individual configuration parameters and defines a value type, value range [configuration range set] and parameter reference relationships) to a behavioral anomaly detection function (Presley fig. 4, a management configuration (mconfig) module 35 para. [0058], Configuration validater and analyzer 67: Ensures runtime configuration parameters are within operating values as specified by retrieved document type definitions 39; Presley para. [0076], the management system 11 can perform an audit (block 133) over all of the configuration parameters to determine the effect of the unvalidated configuration parameter).
Presley does not explicitly disclose:
providing, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function.
Banerjee teaches:
providing, for at least one of plural cognitive functions (Banerjee Abstract: Cognitive Autonomous Networks (CAN) [1] are promoted to advance Self Organizing Network (SON), replacing rule-based SON Functions (SFs) with Cognitive Functions (CFs), which learn optimal behavior by interacting with the network), a optimal configuration range set for the configuration parameter (Banerjee I. Introduction: 1. we mathematically prove, using Prisoner’s Dilemma from Game Theory [5], that coordination mechanism among the CFs is needed for better performance of the system, 2. we design an easily implementable but effective coordination mechanism capable of determining the optimal configuration for a certain state of the network; Banerjee VI. Conclusion And Future Direction: We provide a solution to resolve the possible types of conflicts among the CFs. We build a MAS in Python and show that our proposed solution can be implemented there to resolve the conflicts and obtain the optimal settings for the operational purposes; B. Banerjee Implementation and Observation: in real life there is always a maximum and minimum value for a parameter between which it can be varied).
Note: Presley teaches the configuration parameter received from the respective function (Presley para. [0036-0037]). However, Presley does not explicitly disclose the respective function is the respective cognitive function. Banerjee teaches cognitive function (Banerjee Abstract).
Therefore, it would been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Presley in view of Banerjee in order to apply technique of Presley to environment of Banerjee for providing a configuration parameter and, for at least one of plural cognitive functions, a optimal configuration range set for the configuration parameter received from the respective cognitive function to a behavioral anomaly detection function.
One of ordinary skill in the art would have been motived because it offers the advantage of validate configuration in Cognitive Autonomous Networks.
Per claim 39, it does not teach or further define over the limitations in claim 31. As such, claim 39 is rejected for the same reasons as set forth in claim 31.
Claims 32 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Presley (US 2003/0105838, Pub. Date: Jun. 5, 2003), Banerjee et al. (NPL: On the Necessity and Design of Coordination Mechanism for Cognitive Autonomous Networks, Pub. Date: Jan. 20, 2020), in view of Thennati et al. (US 2024/0020543, Priority Date: Oct. 17, 2020).
As per claim 32, Presley-Banerjee discloses the method according to claim 31, as set forth above, Presley does not explicitly disclose wherein the instructions, when executed by the one or more processors, further cause the apparatus to perform:
calculating an optimized value for the configuration parameter based on the received optimal configuration range sets.
Thennati teaches:
calculating an optimized value for the configuration parameter based on optimal configuration range sets (Thennati para. [0010], the processor is configured to execute the instructions to at least: (i) obtain an indication of: … (b) a hyperparameter search space … (ii) generate a hyperparameter configuration from the hyperparameter search space; Thennati para. [0032], the term "hyperparameter search space" generally refers to a set of values and/or ranges that a particular hyperparameter can take).
It would been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Presley in view of Thennati for calculating an optimized value for the configuration parameter based on the received optimal configuration range sets.
One of ordinary skill in the art would have been motived because it offers the advantage of avoid obviously wrong or ineffective configurations (Thennati para. [0003]).
Per claim 40, it does not teach or further define over the limitations in claim 32. As such, claim 40 is rejected for the same reasons as set forth in claim 32.
Claims 33-34 and 41-42 are rejected under 35 U.S.C. 103 as being unpatentable over Presley (US 2003/0105838, Pub. Date: Jun. 5, 2003), Banerjee et al. (NPL: On the Necessity and Design of Coordination Mechanism for Cognitive Autonomous Networks, Pub. Date: Jan. 20, 2020), in view of Thennati et al. (US 2024/0020543, Priority Date: Oct. 17, 2020), in view of El-Moussa et al. (US 2018/0091531, Pub. Date: Mar. 29, 2018), in view of Tsvetkov et al. (NPL: A Configuration Management Assessment Method for SON Verification; Pub. Date: August 2014).
As per claim 33, Presley-Banerjee-Thennati discloses the method according to claim 32, as set forth above, Presley does not explicitly disclose the instructions, when executed by the one or more processors, further cause the apparatus to perform:
monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior;
adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received;
setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received;
applying the final value of the configuration parameter to the system.
El-Moussa teaches:
monitoring if an indication is received that at least one of functions is suspected for manipulative behavior (Presley para. [0096], at 194, a set of configuration parameters for the target VM are determined. At 195 attack characteristics in the data structure associated with configuration parameters of the target VM are identified as characteristics of attacks to which the target VM is susceptible; El-Moussa para. [0060], Accordingly, on the basis of the reduced set of features determined by learning of the latent factor extractor 130 an indication of susceptibility of a VM configuration can be evaluated, and further a configuration or modifications to a configuration of a VM can be determined);
adding a noise to configuration parameter to obtain a final value of the configuration parameter if the indication is received (El-Moussa para. [0008], each training data item comprises a vector of binary values indicating each indicating a presence or absence of a configuration feature and an attack characteristic of a corresponding training VM; El-Moussa para. [0106], the method reconfigures the target VM by changing one or more VM parameters identified by directed graph as being included in the sequence of parameters for the attack characteristic).
It would been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to further modify Presley in view of El-Moussa for monitoring if an indication is received that at least one of the cognitive functions is suspected for manipulative behavior; and adding a noise to the calculated optimized value to obtain a final value of the configuration parameter if the indication is received.
One of ordinary skill in the art would have been motived because it offers the advantage of determining susceptibility of a target function to security attacks (see El-Moussa para. [0091]).
Presley-El-Moussa does not explicitly disclose:
setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received;
applying the final value of the configuration parameter to the system.
Tsvetkov teaches:
setting the final value of the configuration parameter equal to optimized value (Tsvetkov B. Assessment Decision Phase: The assessment decision phase is an anomaly detection and recommendation process which uses the scope level to detect performance degradation of the cells within the scope. There are two possible outcomes of the process: case passed: it means that the assessment has passed and, therefore, the system recommends the acceptance of the corresponding CM change; Tsvetkov III. Concept Overview: Note that here we refer to CM changes that may include any type of configuration change possible in a mobile network) if the indication is not received (Tsvetkov fig. 2 and A. Performance Evaluation Phase: The performance evaluation phase of our assessment method is an aggregation scheme with the raw KPI values of individual cells at the input side and a scope-wide performance indicator, called the scope level, at the output side. The latter one is devoted to deliver high level performance information about the cells that are in the scope of the CM change being under assessment; Tsvetkov I. Introduction: The resulting scope is then observed whether the included entities are showing anomalous behavior, like a degradation in performance. Based on these observations our CM assessment method generates recommendations to either accept (i.e., CM changes are accepted when no indication of degradation) or undo the corresponding CM changes);
applying the final value of the configuration parameter to the system (Tsvetkov I. Introduction: The resulting scope is then observed whether the included entities are showing anomalous behavior, like a degradation in performance. Based on these observations our CM assessment method generates recommendations to either accept or undo the corresponding CM changes).
It would been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to further modify Presley in view of Tsvetkov for setting the final value of the configuration parameter equal to the calculated optimized value if the indication is not received and applying the final value of the configuration parameter to the system.
One of ordinary skill in the art would have been motived because it offers the advantage of providing an accept configuration changes (see Tsvetkov V. Conclusion).
As per claim 34, Presley-Banerjee-Thennati-El-Moussa-Tsvetkov discloses the method according to claim 33, as set forth above, Thennati-El-Moussa also discloses wherein the instructions, when executed by the one or more processors, further cause the apparatus to perform:
providing the optimized value of the configuration parameter (Thennati para. [0010], the processor is configured to execute the instructions to at least: (i) obtain an indication of: … (b) a hyperparameter search space … (ii) generate a hyperparameter configuration from the hyperparameter search space; Thennati para. [0032], the term "hyperparameter search space" generally refers to a set of values and/or ranges that a particular hyperparameter can take) to a configuration parameter tracking function (El-Moussa fig. 5, a first function of Attack Analysis & Assessment Component), wherein the noise is received from a configuration parameter camouflaging function (El-Moussa fig. 5, a second function of Attack Analysis & Assessment Component; El-Moussa para. [0008], each training data item comprises a vector of binary values indicating each indicating a presence or absence of a configuration feature and an attack characteristic of a corresponding training VM; El-Moussa para. [0106], the method reconfigures the target VM by changing one or more VM parameters identified by directed graph as being included in the sequence of parameters for the attack characteristic).
Similar rationale in claims 32-33 is applied.
Per claims 40-41, they do not teach or further define over the limitations in claims 33-34 respectively. As such, claims 40-41 are rejected for the same reasons as set forth in claim 33-34 respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang et al. (US 2022/0240106) Technique For Generating Synthetic Data For Radio Access Network Configuration Recommendation;
Mwanje et al. (US 2019/0273662) Method And Apparatus For Providing Cognitive Functions And Facilitating Management In Cognitive Network Management Systems;
Stapleton et al. (US 2022/0019663) Machine Learning Model Validation And Authentication.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VINH NGUYEN whose telephone number is (571)272-4487. The examiner can normally be reached Monday-Friday: 7:30 AM - 5:30 PM.
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, KAMAL B DIVECHA can be reached at (571)272-5863. 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.
/VINH NGUYEN/Examiner, Art Unit 2453
/KAMAL B DIVECHA/Supervisory Patent Examiner, Art Unit 2453