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 .
This is a first office action in response to the instant application for letters patent filed on 26 February 2025. Claims 1-20 are presented for examination.
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.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 12294605. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the instant application are arguably broader than the claims of patent “605” which encompass the same metes, bounds, and limitations.
The instant application lacks only the following features “identify relationships between the profile and enterprise resources and wherein the model utilizes a machine learning technique, wherein the model is trained using a set of known security vulnerabilities” which are in claims 1, 8, and 15 of the patent “605”.
It would be obvious to a skill artisan before the effective date of the invention as claimed in patent “605” to incorporate the machine learning features into the claims of the application to facilitate a more effective monitoring and security against social media attack. Therefore, rendering a safer and more reliable system
Application Number: 19064322
Patent Number: 12294605
1. A system, comprising: a processor configured to: monitor a plurality of sites; extract predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyze, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user; io perform an action in response to the one or more detected security vulnerabilities based on a policy; identify a new attack, wherein the new attack is a new social media resource attack and/or a new social engineering type attack; and update the model based on the new attack; and is a memory coupled to the processor and configured to the processor with instructions.
1. A system, comprising: a processor configured to: monitor a plurality of sites; extract predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyze, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user, comprising to: identify relationships between the profile and enterprise resources; determine, using the model, similarities to known security vulnerabilities based on the relationships, wherein the model utilizes a machine learning technique, wherein the model is trained using a set of known security vulnerabilities; and determine whether a security vulnerability to an enterprise resource exists based on the similarities; and perform an action in response to the one or more detected security vulnerabilities based on a policy; and a memory coupled to the processor and configured to the processor with instructions.
2. The system of claim 1, wherein the plurality of sites includes a social media site and/or a people search database.
2. The system of claim 1, wherein the plurality of sites includes a social media site and/or a people search database.
3. The system of claim 1, wherein the analyzing of the profile of the user comprises to: determine, using the model, similarities to known security vulnerabilities; and determine whether a security vulnerability to an enterprise resource exists based on the similarities.
4. The system of claim 1, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email.
3. The system of claim 1, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email.
5. The system of claim 1, wherein the action includes removing one or more pieces of the predetermined user information from the internet.
4. The system of claim 1, wherein the action includes removing one or more pieces of the predetermined user information from the Internet.
6. The system of claim 1, wherein the action includes making private a social media site, so that information associated with the user is not publicly available.
5. The system of claim 1, wherein the action includes making private a social media site, so that information associated with the user is not publicly available.
7. The system of claim 1, wherein the action includes adding multifactor authentication to the one or more enterprise resources associated with the user in the event that the one or more enterprise resources do not already have multifactor authentication.
6. The system of claim 1, wherein the action includes adding multifactor authentication to the one or more enterprise resources associated with the user in the event that the one or more enterprise resources do not already have multifactor authentication.
8. A method, comprising: 5 monitoring a plurality of sites; extracting, using a processor, predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyzing, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated io with the user; performing, using the processor, an action in response to the one or more detected security vulnerabilities based on a policy; identifying a new attack, wherein the new attack is a new social media resource attack and/or a new social engineering type attack; and is updating the model based on the new attack.
8. A method, comprising: monitoring a plurality of sites; extracting, using a processor, predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyzing, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user, comprising: identifying relationships between the profile and enterprise resources; determining, using the model, similarities to known security vulnerabilities based on the relationships, wherein the model utilizes a machine learning technique, wherein the model is trained using a set of known security vulnerabilities; and determining whether a security vulnerability to an enterprise resource exists based on the similarities; and performing, using the processor, an action in response to the one or more detected security vulnerabilities based on a policy.
9. The method of claim 8, wherein the plurality of sites includes a social media site and/or a people search database.
9. The method of claim 8, wherein the plurality of sites includes a social media site and/or a people search database.
10. The method of claim 8, wherein the analyzing of the profile of the user comprises: determining, using the model, similarities to known security vulnerabilities; and 20 determining whether a security vulnerability to an enterprise resource exists based on the similarities.
11. The method of claim 8, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email.
10. The method of claim 8, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email.
12. The method of claim 8, wherein the action includes removing one or more pieces of the predetermined user information from the Internet.
11. The method of claim 8, wherein the action includes removing one or more pieces of the predetermined user information from the Internet.
13. The method of claim 8, wherein the action includes making private a social media site, so that information associated with the user is not publicly available.
12. The method of claim 8, wherein the action includes making private a social media site, so that information associated with the user is not publicly available.
14. The method of claim 8, wherein the action includes adding multifactor authentication to the one or more enterprise resources associated with the user in the event that the one or more enterprise resources do not already have multifactor authentication.
13. The method of claim 8, wherein the action includes adding multifactor authentication to the one or more enterprise resources associated with the user in the event that the one or more enterprise resources do not already have multifactor authentication.
15. A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for: monitoring a plurality of sites; extracting predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyzing, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user; performing an action in response to the one or more detected security vulnerabilities based on a policy; identifying a new attack, wherein the new attack is a new social media resource attack and/or a new social engineering type attack; and updating the model based on the new attack.
15. A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for: monitoring a plurality of sites; extracting predetermined user information for a user from the plurality of monitored sites to generate a profile of the user; analyzing, using a model, the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user, comprising: identifying relationships between the profile and enterprise resources; determining, using the model, similarities to known security vulnerabilities based on the relationships, wherein the model utilizes a machine learning technique, wherein the model is trained using a set of known security vulnerabilities; and determining whether a security vulnerability to an enterprise resource exists based on the similarities; and performing an action in response to the one or more detected security vulnerabilities based on a policy.
16. The computer program product of claim 15, wherein the plurality of sites includes a social media site and/or a people search database.
7. The system of claim 1, the processor further configured to: identify a new social media resource attack and/or a new social engineering type attack; and update the model based on the new social media resource attack and/or the new social engineering type attack.
17. The computer program product of claim 15, wherein the analyzing of the profile of the user comprises: determining, using the model, similarities to known security vulnerabilities; and determining whether a security vulnerability to an enterprise resource exists based on the similarities.
14. The method of claim 8, further comprising: identifying a new social media resource attack and/or a new social engineering type attack; and updating the model based on the new social media resource attack and/or the new social engineering type attack.
18. The computer program product of claim 15, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email.
19. The computer program product of claim 15, wherein the action includes removing one or more pieces of the predetermined user information from the Internet.
20. The computer program product of claim 15, wherein the action includes making private a social media site, so that information associated with the user is not publicly available.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-6, 8-13, and 15-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Pon et al. hereinafter Pon Pub Number 20220070194A1.
As per claim 1, Pon teaches a system, comprising: a processor (see fig 3, computing system 302,
processing unit 312, 314 ...) configured to: monitor a plurality of sites (fig 1, monitor manager
126; par 0005, monitoring website; par 0039, monitoring includes collecting da);
extract predetermined user information for a user from the plurality of monitored sites to generate a profile of the user (see par 0038-0040 and 0068-0069, monitoring involves extracting information to be analyzed, thereby creating a profile); analyze, using a model (concept of model is taught by Pon, see par 0084) , the profile of the user to detect whether one or more security vulnerabilities exist for social engineering attacks for one or more enterprise resources associated with the user (see par 0046, 0088 and 0090); perform an action (action is broad here and can be any action; par 0051 and 0062, taking action to mitigate an active threat) in response to the one or more detected security vulnerabilities based on a policy (see par 0090- 0091, to the extent there has been a confirmed threat; par 0038, rules/policy may be generated based on input requesting to monitor an artifact for an asset); identify a new attack, wherein the new attack is a new social media resource attack and/or a new social engineering type attack (see par 0038 which discusses changes; par 0047 discusses updates); and update the model based on the new attack (see par 0038 which discusses changes; par 0047 discusses updates); and is a memory coupled to the processor and configured to the processor with instructions (see par 0029, memory storage device).
As per claim 2, Pon teaches the system of claim 1, wherein the plurality of sites includes a social media site and/or a people search database (see par 0009, social media; par 0040, notification
about an event that is detected; par 0046, network data stored may be searchable).
As per claim 3, Pon teaches the system of claim 1, wherein the analyzing of the profile of the user comprises to: determine, using the model, similarities to known security vulnerabilities (see par 0083 and 0088); and determine whether a security vulnerability to an enterprise resource exists based on the similarities (see par 0088).
As per claim 4, Pon teaches the system of claim 1, wherein the action includes one or more of the following: generate an alert, generate a report, and/or generate an email (see par 0054, 0056, 0063).
As per claim 5, Pon teaches the system of claim 1, wherein the action includes removing one or more pieces of the predetermined user information from the internet (par 0023, 0052, 0128, updates).
As per claim 6, Pon teaches the system of claim 1, wherein the action includes making private a social media site, so that information associated with the user is not publicly available (par 0024
and 0005).
As per claims per claims 8-13, they are a method of the system claims 1-6 discussed above. Therefore, they are rejected under the same rationale.
As per claims 15-20, they are a computer program product of the system claims 1-6 discussed above. Therefore, they are rejected under the same rationale.
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, 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.
Claim(s) 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Pon and Cunningham et al. hereinafter Cunningham Pub Number 20220006818 A1.
As per claim 7, Pon teaches the system of claim 1, wherein the action includes adding to the one or more enterprise resources associated with the user in the event that the one or more enterprise resources do not already have (see par 0023, client system 104 may provide access to one or more applications 106).
Pon does not discuss multifactor authentication. However, Cunningham teaches all aspects of
the claims invention including authentication factors (see par 0047, 0058, 0093, 0112, and
0119). It would be obvious to a skilled artisan before the effective filing date of the invention to
incorporate the multifactor authentication into Pon's system to enhance the security of the
system.
As per claim 14, it contains the same limitations as discussed in claim 7 above. Therefore, they are rejected under the same rationale.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANTZ B JEAN whose telephone number is (571)272-3937. The examiner can normally be reached 8-5 M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Glenton B. Burgess can be reached at 5712723949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FRANTZ B JEAN/Primary Examiner, Art Unit 2454
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