DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception(s) without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a process or product, which is one of the statutory categories of invention (Step 1: YES).
[STEP2A PRONG I] The claims 1, 6 and 11 recite(s):
A processor-implemented method, the method comprising:
receiving, by one or more hardware processors, a browsing behavioral data associated with each of a plurality of potential trainees for a predefined time window, wherein the plurality of potential trainees are identified based on a plurality of training activation prompt in real time, wherein the plurality of training activation prompt comprises at least one of (i) interacting at least one risky Uniform Resource Locator (URL) (ii) when a frequency of interacted URLs associated with each of the plurality of potential trainees is greater than a predefined interaction threshold and (iii) a user initiated training;
analyzing, by the one or more hardware processors, a risk category associated with each URL among a plurality of URLs interacted by each of the plurality of potential trainees, wherein a warning is given to each of the plurality of potential trainees based on the associated risk category;
simultaneously identifying, by the one or more hardware processors, a plurality of trainees from among the plurality of potential trainees based on a training willingness obtained from each of the plurality of potential trainees; identifying, by the one or more hardware processors, a plurality of URL components associated with each of the plurality of interacted URLs using a pattern matching technique, wherein each of the plurality of URL components associated with each of the plurality of interacted URLs is associated with a weight;
initiating training, by the one or more hardware processors, for each of the plurality of trainees by displaying the plurality of URL component based questionnaire and receiving a corresponding answer from each of the plurality of trainees;
iteratively performing, by the one or more hardware processors, until a performance score associated with each of the plurality of trainees is greater than a predefined score threshold:
obtaining, by the one or more hardware processors, an answering pattern associated with each of the plurality of trainees for a predefined number of attempts based on an associated user strike rate;
computing, by the one or more hardware processors, the performance score associated with each of the plurality of trainees based on the corresponding user strike rate associated with each of the plurality of URL components, an overall strike rate of the plurality of URL components and an average time taken to answer the URL component based questionnaire associated with each of the plurality of URL components;
updating, by the one or more hardware processors, the weight corresponding to each of the plurality of URL components based on the answering pattern associated with each of the plurality of trainees for the corresponding plurality of URL components based questionnaire, wherein the weight is decremented if the answer is correct and wherein the weight is incremented if the answer is incorrect, wherein a strike rate based weight is added to the weight if the corresponding user strike rate is less than a predefined strike threshold;
computing, by the one or more hardware processors, a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees; and
dynamically deciding, by the one or more hardware processors, display order associated with each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on the corresponding priority value and the corresponding performance score, wherein the associated plurality of URL components based questionnaire with the priority value above a predefined priority threshold are displayed to the associated plurality of trainees if the associated performance score is less than a predefined score threshold.
6. A system comprising:
at least one memory storing programmed instructions; one or more Input /Output (1/O) interfaces; and one or more hardware processors operatively coupled to the at least one memory, wherein the one or more hardware processors are configured by the programmed instructions to:
receive a browsing behavioral data associated with each of a plurality of potential trainees for a predefined time window, wherein the plurality of potential trainees are identified based on a plurality of training activation prompt in real time, wherein the plurality of training activation prompt comprises at least one of (i) interacting at least one risky Uniform Resource Locator (URL) (ii) when a frequency of interacted URLs associated with each of the plurality of potential trainees is greater than a predefined interaction threshold and (iii) a user initiated training;
analyze a risk category associated with each URL among a plurality of URLs interacted by each of the plurality of potential trainees, wherein a warning is given to each of the plurality of potential trainees based on the associated risk category;
simultaneously identify a plurality of trainees from among the plurality of potential trainees based on a training willingness obtained from each of the plurality of potential trainees;
identify a plurality of URL components associated with each of the plurality of interacted URLs using a pattern matching technique, wherein each of the plurality of URL components associated with each of the plurality of interacted URLs is associated with a weight;
initiate training for each of the plurality of trainees by displaying the plurality of URL component based questionnaire and receiving a corresponding answer from each of the plurality of trainees;
iteratively perform until a performance score associated with each of the plurality of trainees is greater than a predefined score threshold:
obtain an answering pattern associated with each of the plurality of trainees for a predefined number of attempts based on an associated user strike rate;
compute the performance score associated with each of the plurality of trainees based on the corresponding user strike rate associated with each of the plurality of URL components, an overall strike rate of the plurality of URL components and an average time taken to answer the URL component based questionnaire associated with each of the plurality of URL components;
update the weight corresponding to each of the plurality of URL components based on the answering pattern associated with each of the plurality of trainees for the corresponding plurality of URL components based questionnaire, wherein the weight is decremented if the answer is correct and wherein the weight is incremented if the answer is incorrect, wherein a strike rate based weight is added to the weight if the corresponding user strike rate is less than a predefined strike threshold;
compute a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees; and
dynamically decide display order associated with each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on the corresponding priority value and the corresponding performance score, wherein the associated plurality of URL components based questionnaire with the priority value above a predefined priority threshold are displayed to the associated plurality of trainees if the associated performance score is less than a predefined score threshold.
11. One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:
receiving, a browsing behavioral data associated with each of a plurality of potential trainees for a predefined time window, wherein the plurality of potential trainees are identified based on a plurality of training activation prompt in real time, wherein the plurality of training activation prompt comprises at least one of (i) interacting at least one risky Uniform Resource Locator (URL) (ii) when a frequency of interacted URLs associated with each of the plurality of potential trainees is greater than a predefined interaction threshold and (iii) a user initiated training;
analyzing, a risk category associated with each URL among a plurality of URLs interacted by each of the plurality of potential trainees,wherein a warning is given to each of the plurality of potential trainees based on the associated risk category;
simultaneously identifying, a plurality of trainees from among the plurality of potential trainees based on a training willingness obtained from each of the plurality of potential trainees;
identifying, a plurality of URL components associated with each of the plurality of interacted URLs using a pattern matching technique, wherein each of the plurality of URL components associated with each of the plurality of interacted URLs is associated with a weight;
initiating training, for each of the plurality of trainees by displaying the plurality of URL component based questionnaire and receiving a corresponding answer from each of the plurality of trainees;
iteratively performing, until a performance score associated with each of the plurality of trainees is greater than a predefined score threshold:
obtaining, an answering pattern associated with each of the plurality of trainees for a predefined number of attempts based on an associated user strike rate;
computing, the performance score associated with each of the plurality of trainees based on the corresponding user strike rate associated with each of the plurality of URL components, an overall strike rate of the plurality of URL components and an average time taken to answer the URL component based questionnaire associated with each of the plurality of URL components;
updating, the weight corresponding to each of the plurality of URL components based on the answering pattern associated with each of the plurality of trainees for the corresponding plurality of URL components based questionnaire, wherein the weight is decremented if the answer is correct and wherein the weight is incremented if the answer is incorrect, wherein a strike rate based weight is added to the weight if the corresponding user strike rate is less than a predefined strike threshold;
computing, a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees; and
dynamically deciding, display order associated with each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on the corresponding priority value and the corresponding performance score, wherein the associated plurality of URL components based questionnaire with the priority value above a predefined priority threshold are displayed to the associated plurality of trainees if the associated performance score is less than a predefined score threshold.
The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting hardware processors”, “memory storing programmed instruction”; “I/O interface” nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses a teacher observing students’ behaviors and adjusting its instruction/lecture level accordingly.
If a claim limitation, under its broadest reasonable interpretation, covers managing interactions between people, then it falls within the “Organization of Human Activity” grouping of abstract ideas.
Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two.
[STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “hardware processors”, “memory storing programmed instruction”; “I/O interface” in the aforementioned steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES).
[STEP2B] 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 of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept (for example, see paragraph 31-33).
As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The claim is not patent eligible. (Step 2B: NO).
Claims 2-5, 7-9, 12-15 are dependent on supra claim(s) and includes all the limitations of the claim(s). For example, claims 2-4, 7-9 and 12-14 are directed to calculating the risk that a user exhibited (a mental process) and claims 5, 10 and 15 are directed to the use of Generative Artificial Intellegnce model to update the training content (a technological environment)/ Therefore, the dependent claim(s) recite(s) the same abstract idea. The claim recites no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Patel US 20210211452
Provides a teaching of providing training based on the user’s cybersecurity profiles. However, it fails to provide a teaching of “computing, a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees”
Forough US 20220130272
Provides a teaching of just in time training to mitigate user’s cybersecurity risk. However, it fails to provide a teaching of “computing, a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees”
Adams et al US 11914719
Provides a teaching of the calculation of the user’s cybersecurity risk based on the user’s behavior. However, it fails to provide a teaching of “computing, a priority value for each of the plurality of URL components based questionnaire corresponding to each of the plurality of trainees based on a corresponding answering pattern and the updated weight, wherein the priority value is incremented if a URL component based questionnaire is not displayed for a predefined recent number of times, and wherein occurrence of an URL component based questionnaire is stopped for a predefined number of future attempts after the first attempt so that next priority URL components based questionnaire are displayed to the plurality of trainees”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT J UTAMA whose telephone number is (571)272-1676. The examiner can normally be reached 9:00 - 17:30 Monday - Friday.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached at (571)270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
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