DETAILED ACTION
Claims 1-9 have been examined and are pending.
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 § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
The factual inquiries 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-9 are rejected under 35 U.S.C. 103 as being unpatentable over US Pub. No. 2025/0016183 to Sergeev (hereinafter “Sergeev”) and further in view of US Pat. No. 12/652302 to Parikh et al. (hereinafter “Parikh”).
As to Claim 1, Sergeev discloses an information processing apparatus comprising:
at least one memory storing instructions; and at least one processor configured to execute the instructions to:
acquire environment information indicating an environment of communication that is monitored by a monitoring apparatus that monitors communication in a network, for detection information indicating an abnormal event detected by the monitoring apparatus (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query);
transmit inquiry information for inquiring about a factor in the occurrence of the event included in the detection information, to a language model, and acquire response information in response to the inquiry information, from the language model (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query. Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response); and
display the detection information, the environment information, and the response information (Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response. Because LLM 105 outputs a response as natural language text, the request processor 104 uses connected natural language processing libraries, such as SpaCy or NTLK, to highlight the desired terms and phrases. Analysis involves highlighting pre-known phrases or text elements).
Parikh further discloses displaying output from an LLM.
Column 107 lines 25-30 of Parikh disclose used by the monitoring tool 1800 to obtain output from the LLM. Column 8 lines 45-50 of Parikh disclose one or more devices for presenting output to a user.
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to combine LLM security system as disclosed by Sergeev, with displaying the output as disclosed by Parikh. One of ordinary skill in the art would have been motivated to combine to apply a known technique to a known device ready for improvement to yield predictable results. Sergeev and Parikh are directed toward LLM security systems and as such it would be obvious to use the techniques of one in the other. Column 6 lines 50-65 of Parikh disclose a natural language query may be constructed and passed to the LLM 1814 as input (e.g., “retrieve information associated with accessing a known malicious IP address”). In response, the LLM 1814 may process the input, understand its context, and leverage its training data to generate a response (including augmenting it's response with information in a knowledge base such as, for example, pre-existing knowledge about the domain, historical data, or information from external sources).
As to Claim 2, Sergeev-Parikh discloses the information processing apparatus according to claim 1, wherein the one or more processors is further configured to execute the instructions to:
acquires history information indicating a history of anomalies detected by the monitoring apparatus, for the detection information, and displays information that includes the history information (Column 6 lines 50-65 of Parikh disclose a natural language query may be constructed and passed to the LLM 1814 as input (e.g., “retrieve information associated with accessing a known malicious IP address”). In response, the LLM 1814 may process the input, understand its context, and leverage its training data to generate a response (including augmenting it's response with information in a knowledge base such as, for example, pre-existing knowledge about the domain, historical data, or information from external sources).
Examiner recites the same rationale to combine used for claim 1.
As to Claim 3, Sergeev-Parikh discloses the information processing apparatus according to claim 2, further comprising: the one or more processors is further configured to execute the instructions to:
generates a prompt for generating analysis assistance information for assisting in anomaly analysis, using the detection information, the environment information, the history information, and the response information; and transmits the prompt to the language model, and acquiring the analysis assistance information for the prompt, from the language model (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query).
As to Claim 4, Sergeev-Parikh discloses the information processing apparatus according to claim 3, further comprising the one or more processors is further configured to execute the instructions to:
generates control instruction information for avoiding the anomaly based on the analysis assistance information, and control a device that is an anomaly detection target and is provided in the network (Paragraph [0116] of Sergeev discloses Yes, this could be an indicator of compromise. It is possible that the attacker has created a malicious task in the registry to launch PowerShell with a hidden flag and encoded base64 string. This code could potentially execute malicious commands on the system, such as installing malware or stealing data. In order to confirm if this indeed an indicator of compromise, it would be necessary to analyze script further and look for other clues that indicate malicious activity).
As to Claim 5, Sergeev-Parikh discloses the information processing apparatus according to claim 1 wherein anomaly detection set for each of a plurality of monitoring apparatuses in advance is executed, the monitoring apparatuses being provided at a plurality of locations in the network (Paragraph [0025] of Sergeev discloses he components of the system may be realized within a single computing device, or distributed amongst several interconnected computing devices).
As to Claim 6, Sergeev discloses an information processing method comprising:
acquiring, by an information processing apparatus, environment information indicating an environment of communication that is monitored by a monitoring apparatus that monitors communication in a network, for detection information indicating an abnormal event detected by the monitoring apparatus (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query);
transmitting, by the information processing apparatus, inquiry information for inquiring about a factor in the occurrence of the event included in the detection information, to a language model (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query);
acquiring, by the information processing apparatus, response information in response to the inquiry information, from the language model (Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response); and
displaying, by the information processing apparatus, the detection information, the environment information, and the response information, on a display unit (Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response. Because LLM 105 outputs a response as natural language text, the request processor 104 uses connected natural language processing libraries, such as SpaCy or NTLK, to highlight the desired terms and phrases. Analysis involves highlighting pre-known phrases or text elements).
Parikh further discloses displaying output from an LLM.
Column 107 lines 25-30 of Parikh disclose used by the monitoring tool 1800 to obtain output from the LLM. Column 8 lines 45-50 of Parikh disclose one or more devices for presenting output to a user.
Examiner recites the same rationale to combine used for claim 1.
As to Claim 7, Sergeev-Parikh discloses the information processing method according to claim 6, further comprising: acquiring, by the information processing apparatus, history information indicating a history of anomalies detected by the monitoring apparatus, for the detection information; and displaying, by the information processing apparatus, information that includes the history information on a display unit (Column 6 lines 50-65 of Parikh disclose a natural language query may be constructed and passed to the LLM 1814 as input (e.g., “retrieve information associated with accessing a known malicious IP address”). In response, the LLM 1814 may process the input, understand its context, and leverage its training data to generate a response (including augmenting it's response with information in a knowledge base such as, for example, pre-existing knowledge about the domain, historical data, or information from external sources).
Examiner recites the same rationale to combine used for claim 1.
As to Claim 8, Sergeev discloses a non-transitory computer-readable recording medium on which a program is recorded, the program for causing a computer to carry out processing for:
acquiring environment information indicating an environment of communication that is monitored by a monitoring apparatus that monitors communication in a network, for detection information indicating an abnormal event detected by the monitoring apparatus (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query);
transmitting inquiry information for inquiring about a factor in the occurrence of the event included in the detection information, to a language model (Figure 2 of Sergeev discloses collecting additional information and then generating and sending an LLM query);
acquiring response information in response to the inquiry information, from the language model (Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response); and
displaying the detection information, the environment information, and the response information, on a display unit (Paragraph [0093] of Sergeev discloses receives a response from LLM 105 and parses the received response. Because LLM 105 outputs a response as natural language text, the request processor 104 uses connected natural language processing libraries, such as SpaCy or NTLK, to highlight the desired terms and phrases. Analysis involves highlighting pre-known phrases or text elements).
Parikh further discloses displaying output from an LLM.
Column 107 lines 25-30 of Parikh disclose used by the monitoring tool 1800 to obtain output from the LLM. Column 8 lines 45-50 of Parikh disclose one or more devices for presenting output to a user.
Examiner recites the same rationale to combine used for claim 1.
As to Claim 9, Sergeev-Parikh discloses the non-transitory computer-readable recording medium according to claim 8 causing the computer to further execute processing for: acquiring history information indicating a history of anomalies detected by the monitoring apparatus, for the detection information; and displaying information that includes the history information on a display unit (Column 6 lines 50-65 of Parikh disclose a natural language query may be constructed and passed to the LLM 1814 as input (e.g., “retrieve information associated with accessing a known malicious IP address”). In response, the LLM 1814 may process the input, understand its context, and leverage its training data to generate a response (including augmenting it's response with information in a knowledge base such as, for example, pre-existing knowledge about the domain, historical data, or information from external sources).
Examiner recites the same rationale to combine used for claim 1.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kevin S Mai whose telephone number is (571)270-5001. The examiner can normally be reached Monday to Friday 9AM to 5PM.
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/KEVIN S MAI/Primary Examiner, Art Unit 2499
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