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 1, 5, 9, 11, and 20 have been amended
Objection to drawings have been overcome due to applicant’s amendments
Claim objections to claims 1, 9, 11, 19, and 20 have been overcome due to applicant’s filed amendments.
Claims 1-20 are pending
Priority
This application claims no priority. Therefore, the effective filing date of this application is 07/02/2024.
Response to Arguments
Applicant’s arguments filed on 12/17/2025 have been fully considered.
With respect to the objection to the drawings. The objection to the drawings has been overcome due to applicant’s amendments.
With respect to objection to claims 1, 9, 11, 19, and 20. The objections have been overcome due to applicant’s filed amendments.
USC 112(b) rejection for Claims 1 and 11 reciting the limitation " structured data model that is suitable for machine learning analysis" has been overcome due to applicant’s amendments.
USC 112(b) rejection for claims 1, 11, and 20 reciting the limitation "best-performing models" and “best-performing version” has been overcome due to applicant’s amendments.
USC 112(b) rejection for Claims 1 and 11 reciting the limitation " the extracted features contribute meaningfully to detection" has been overcome due to applicant’s amendments.
USC 112(b) rejection for Claims 1 and 11 reciting the limitation " ensuring long-term protection against evolving threats" has been overcome due to applicant’s amendments.
On page 15 of the remarks Applicant’s representative has mentioned the claims have been amended to overcome the rejection under USC 112(b). However, most of the USC 112(b) listed below and in the non-final rejection mailed on 10/01/2025 have not been addressed. The rejection for claims 1-20 under USC 112(b) listed below still stand. Furthermore, the limitations of claim 11 invoke USC 112(f) and the written description fails to disclose the corresponding structure have also not been addressed.
Examiner suggests overcoming all rejections below to place the application in consideration of allowance.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“a data collection module configured to” in claim 11
“a web scraping agent configured to” in claim 11
“a dataset generation module configured to” in claim 11
“… an evaluation module configured to” in claim 11
“a selection module configured to” in claim 11
“a prediction module configured to” in claim 11
“a feature extraction module configured to” in claim 11
“… an evaluation model execution module configured to” in claim 11
“a machine learning module configured to” in claim 11
“a model generation module configured to” in claim 11
“… an integration module configured to” in claim 11
“a feature engineering module configured to” in claim 11
“a real-time processing module configured to” in claim 11
“a decision-making module configured to” in claim 11
“a feedback module configured to” in claim 11
Because these claim limitation(s) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
See specification para. [0047, 0144] for functional support for a data collection module
See specification para. [0047, 0056, 0068] for functional support for a web scraping agent
See specification para. [0047, 0149] for functional support for a dataset generation module
See specification para. [0047, 0052, 0150] for functional support for an evaluation module
See specification para. [0047, 0151] for functional support for a selection module
See specification para. [0047, 0152] for functional support for a prediction module
See specification para. [0047, 0153] for functional support for a feature extraction module
See specification para. [0047, 0154] for functional support for an evaluation model execution module
See specification para. [0047, 0155] for functional support for a machine learning module
See specification para. [0047, 0156] for functional support for a model generation module
See specification para. [0047, 0055, 0157] for functional support for an integration module
See specification para. [0047, 0055, 0158] for functional support for a feature engineering module
See specification para. [0047, 0159] for functional support for a real-time processing module
See specification para. [0047, 0160] for functional support for a decision-making module
See specification para. [0047, 0161] for functional support for a feedback module
If applicant does not intend to have these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 11 recite the limitation "the original unstructured data ". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the downloaded data”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " the … structured data that was newly …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the … structured data model that was newly”. Appropriate correction is required.
Claims 1 and 11 recites the limitation " ensuring that the data is … partitioned ". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “ensuring that data of the after-processing dataset is partitioned …”. Appropriate correction is required.
Claims 1, 11, and 20 recites the limitation " identify specific attributes from the data ". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “identify specific attributes from the new data …”. Appropriate correction is required.
Claims 1, 11, and 20 recite the limitation " to assess the accuracy of the feature extraction …". There is insufficient antecedent basis for “the accuracy” in the claim. For the purpose of examination examiner is interpreting this limitation as “to assess accuracy of the feature extraction”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " a machine learning algorithm to learn from the data ". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “a machine learning algorithm to learn from the evaluation model …”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " ongoing training and updating of the model…". There is insufficient antecedent basis for “the model” in the claim. For the purpose of examination examiner is interpreting this limitation as “ongoing training and updating of the evaluation model”. Appropriate correction is required.
Claims 1 and 11 recites the limitation " trained model is optimized for accuracy and reliability in phishing detection". Accuracy and reliability are relative terms which renders the claim indefinite. Furthermore, the specification does not describe an adequate scope of “accuracy” and “reliability”. For the purpose of examination examiner is interpreting this limitation as “trained model is optimized for phishing detection …”. Appropriate correction is required.
Claims 1, 11, and 20 recite the limitation " using feature engineering to refine the data". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “using feature engineering to refine the incoming emails and messages …”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " involving the selection …". There is insufficient antecedent basis for “the selection” in the claim. For the purpose of examination examiner is interpreting this limitation as “involving selection …”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " the data fed into the model …". There is insufficient antecedent basis for “the model” in the claim. For the purpose of examination examiner is interpreting this limitation as “the data fed into the trained model …”. Appropriate correction is required.
Claims 1 and 11 recites the limitation " ensuring that the data fed into the model is of quality" and “data fed into the model is of the quality”. Quality is a relative term which renders the claim indefinite. Furthermore, the specification does not describe an adequate scope of “quality”. For the purpose of examination examiner is interpreting this limitation as “ensuring that the data fed into the model is refined …”. Appropriate correction is required.
Claims 1 and 11 recite the limitation " the decision trees…". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the multiple decision trees …”. Appropriate correction is required.
Claims 1 and 11 recites the limitation “using trained models” and “using the trained models”. There is insufficient antecedent basis for this limitation in the claim. Furthermore, it is unclear if the trained models are the same as the Random Forest models. For the purpose of examination examiner is interpreting this limitation as “using the Random Forest models”. Appropriate correction is required.
Claims 1, 11, and 20 recites the limitation “retrain an AI model” and “ retrain the AI model”. There is insufficient antecedent basis for this limitation in the claim. Furthermore, it is unclear if the retraining is being done on a new model or the already trained model. For the purpose of examination examiner in interpreting this limitation as “retrain the trained model”
Claims 4 and 14 recites the limitation " structured data format suitable for further analysis". Suitable is a relative term which renders the claim indefinite. Furthermore, the specification does not describe an adequate scope of “suitable”. For the purpose of examination examiner is interpreting this limitation as “structured data format for further analysis…”. Appropriate correction is required.
Claim 15 recite the limitation "making it easier to identify ". Easier is a relative term which renders the claim indefinite. Furthermore, the specification does not describe an adequate scope of “easier”. For the purpose of examination examiner is interpreting this limitation as “labeled features, to identify patterns and anomalies …”. Appropriate correction is required.
Claim 6 recites the limitation " the Random Forest models …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the multiple Random Forest models …”. Appropriate correction is required.
Claims 7 and 17 recites the limitation " isolating specific attributes from the data". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “isolating specific attributes from the new data…”. Appropriate correction is required.
Claims 11 and 20 recites the limitation " storing the downloaded data…". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “storing downloaded data…”. Appropriate correction is required.
Claims 11, 13, and 20 recites the limitation " the stored data…". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the downloaded data…”. Appropriate correction is required.
Claim 11 recites the limitation " the system …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the information-security system …”. Appropriate correction is required.
Claim 11 recites the limitation " ensuring that the model …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “ensuring that the trained model …”. Appropriate correction is required.
Claim 12 recites the limitation " the efficiency of data …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “efficiency of data …”. Appropriate correction is required.
Claim 12 recites the limitation " the prioritization …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “prioritization …”. Appropriate correction is required.
Claim 20 recites the limitation " the original data …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the downloaded data …”. Appropriate correction is required.
Claim 20 recites the limitation " the structured data …". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the structured data model…”. Appropriate correction is required.
Claim 20 recites the limitation " the evaluation results…". There is insufficient antecedent basis for this limitation in the claim. For the purpose of examination examiner is interpreting this limitation as “the evaluation …”. Appropriate correction is required.
Claim 20 recites the limitation “a machine learning algorithm to learn from the data ". It is unclear what data is being referred to in this limitation. For the purpose of examination examiner is interpreting this limitation as “a machine learning algorithm to learn from the evaluation model …”. Appropriate correction is required.
Claims 2-10 and 12-19 depend on claims 1 and 11. Therefore, claims 2-10 and 12-19 inherit the rejection of claims 1 and 11.
Claim limitations:
“a data collection module configured to” in claim 11
“a web scraping agent configured to” in claim 11
“a dataset generation module configured to” in claim 11
“… an evaluation module configured to” in claim 11
“a selection module configured to” in claim 11
“a prediction module configured to” in claim 11
“a feature extraction module configured to” in claim 11
“… an evaluation model execution module configured to” in claim 11
“a machine learning module configured to” in claim 11
“a model generation module configured to” in claim 11
“… an integration module configured to” in claim 11
“a feature engineering module configured to” in claim 11
“a real-time processing module configured to” in claim 11
“a decision-making module configured to” in claim 11
“a feedback module configured to” in claim 11
invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The specification does not disclose of adequate structure to implement the various modules and agent. The specification broadly states in para. 0071 “devices might feature specialized circuits like application-specific integrated circuits (ASICs), microprocessors, cores, or other processing units for executing, accessing, controlling, or implementing various types of software, instructions, data, modules, processes, or routines. “. However, there is no link to show that each module and agent recited in system claim 11 is implemented through a device featuring integrated circuits (ASICs), microprocessors, cores, or other processing units. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Allowable Subject Matter
Claims 1-20 are considered allowable. A reason for allowance will be noted in a notice of allowance once all rejections and objections cited above have been overcome.
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant’s
disclosure.
GREWAL (US-11924245-B2): This prior art teaches of email phishing detection mechanism is provided that utilizes machine learning algorithms. The machine learning algorithms are trained on phishing and non-phishing features extracted from a variety of data sets. Embodiments extract embedded URL-based and email body text-based feature sets for training and testing the machine learning algorithms. Embodiments determine the presence of a phishing message through a combination of examining an embedded URL and the body text of the message for the learned feature sets.
SINGH (US-20230075964-A1): This prior art teaches of generative adversarial network and a reinforcement learning system are combined to generate phishing emails with adaptive complexity. A plurality of phishing emails are obtained from a trained generative adversarial neural network, including a generator neural network and a discriminator neural network. A subset of phishing emails is selected, from the plurality of phishing emails, using a reinforcement learning system trained on user-specific behavior. One or more of the subsets of phishing emails are sent to a user email account associated with a particular user. The reinforcement learning system is then adjusted based on user action feedback to the one or more of the subsets of phishing emails.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AFAQ ALI whose telephone number is (571)272-1571. The examiner can normally be reached Mon - Fri 7:30am - 5:30pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kambiz Zand can be reached on (571)272-3811. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A.A./
01/06/2026
/AFAQ ALI/Examiner, Art Unit 2434
/NOURA ZOUBAIR/Primary Examiner, Art Unit 2434
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