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 .
Response to Amendment
This office action is responsive to amendment filed on 06/02/2026. The Examiner has acknowledged the amended claims 1, 2, 4, 8 and 15 have been amended. Claims 1-20 have been presented for examination and are rejected.
Response to Arguments
Applicant's argument, filed on 06/02/2026 has been entered and carefully considered.
Applicant's arguments with respect to claims 1-20 have been considered but are moot in view of the new ground of rejection necessitated by Applicant's amendment.
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 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 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 1-5, 8-10, 11-12 and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Fok et al. (WO 2006105301 hereinafter Fok) in view of Khosla Vinod (WO 2022115508 hereinafter Khosla Vinod).
With respect to claims 1, 8 and 15 , Fok teaches a method for providing an anti-spam service, the method comprising:
receiving a message at a user equipment (UE) corresponding to a user (Fok, see FIG. 11 and paragraph [00125] a method of spam detection on a wireless device 102 may include receiving, at step 302, at least a portion of an anti-spam engine 138 onto wireless device 102);
causing display of text corresponding to the message within a text interface of the UE (Fok, see paragraph [00134] although user manager anti-spam module 190 may generate report 205, the user manager 110 and its corresponding components may be operable to present a view of spam related information collected from the wireless device 102 in any form, such as tables, maps, graphics views, plain text, interactive programs or web pages, or any other display or presentation of the data);
receiving a selection, by the user, of a portion of the text corresponding to the message (Fok, see paragraph [0074] all or a selected portion 173 of the given content 160 and/or information associated with the content, including but not limited to: the calculated filter test result 188; the content destination 172; and source information 186 identifying the originator of the content and including, for example, a URL, a telephone number, a MAC address, an E-mail address of the spam generator 122, …Paragraph [0075] discloses furthermore, for content 160 classified as spam content 163 and stored in a separate quarantine folder 188, anti-spam engine 138 may alert a user of wireless device 102 of their presence in order to initiate review of these content );
receiving, at the UE, a response from the anti-spam engine (Fok, see paragraph [00118] at step 381, a message may be received by the wireless device 102 in response to the transmitted spam log 184. The message may comprise a control command 185 instructing the wireless device 102 to receive and upload an update to content filter configuration 170);
causing display of the response from the anti-spam engine within the text interface of the UE, wherein the response comprises an analysis of the portion of the text (Fok, see paragraphs [00134-00135] although user manager anti-spam module 190 may generate report 205 (i.e., report form analysis), the user manager 110 and its corresponding components may be operable to present a view of spam related information collected from the wireless device 102 in any form, such as tables, maps, graphics views, plain text, interactive programs or web pages, or any other display or presentation of the data. For example, user manager anti-spam module 190 may present content authorization related information on a monitor or display device, and/or may transmit this information, such as via electronic mail, …); and
prompting the user, at the text interface of the UE, to select an action to perform corresponding to the message(Fok, see paragraphs [00135-00137] at step 318, an authorized user of operator workstation 114 may analyze report 205 and decide, for example, to contact message center 118. In one aspect, the operator workstation 114 may transmit, at step 320, an appropriately composed message to the user manager 110, to be forwarded, at step 322, to the message center 118...).
Fok yet fails to explicitly discloses forwarding the portion of the text selected by the user to the message to an anti-spam engine to determine if the message is spam,
wherein the anti-spam engine comprises an artificial intelligence-powered language model configured to generate a human-readable response based on the portion of the text;
However, Khosla Vinod discloses forwarding the portion of the text selected by the user to the message to an anti-spam engine to determine if the message is spam (Khosla Vinod, see FIG. 4. and para. [0041] method for generating a response to communication classified as spam using the trained artificial intelligence model. In step 405, the data receiving engine 205 within the spam communication manager apparatus 14 intercepts the communication that sent from one of the plurality of communication sending devices…the communication can include an email, although the communication can include other types or amounts of information. In other examples, the communication be occur via a communication protocol, a conversational artificial intelligence chat (i.e., equivalent to human- readable such as text ), or a series of phone calls),
wherein the anti-spam engine comprises an artificial intelligence-powered language model configured to generate a human-readable response based on the portion of the text (Khosla Vinod, see paragraphs [0019-0020] the spam response engine 220 may include a second set artificial intelligence models that assists with generating a response if the received communication is classified as spam, although the second set of artificial intelligence models may be configured to perform other types or amounts of functions. FIG 2, the memory 20 also includes the response sending engine 225 that assists with sending the generated response from the spam response engine 220 back to the spam sending device, although the response sending engine 225 may be configured to perform other types or amounts of functions);
It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to combine the teaching of Fok with the teaching of Khosla Vinod to provide the method for an AI language model anti-spam engine generates human-readable responses to suspicious messages. This approach offers a major advantage: it allows security systems to interact with automated bots or malicious senders, waste their resources, and trick them into revealing their attack strategies or further phishing links.
With respect to claims 2, 9 and 16, Fok-Khosla Vinod teaches the method, wherein the action selectable by the user comprises at least one of blocking a sender of the message, deleting the message, or reading the message (Leddy, see paragraph [0072] if classified as spam content 163, anti-spam engine 138 may then store the content in quarantine folder 164 and/or may automatically delete the content depending upon storage limit 176. If not classified as spam, then anti-spam engine 138 initiates the delivery of content 160 to the intended content destination 172).
With respect to claims 3, 10 and 17, Fok-Khosla Vinod teaches the method, wherein forwarding text corresponding to the message to an anti-spam engine comprises:
forwarding the text corresponding to the message to a server; and instructing the server to make an application programming interface (API) call to the anti-spam engine, the API call including the text corresponding to the message (Fok, see paragraphs [0057] processing subsystems 150 may include any subsystem components that receive data reads and data writes from API 146 on behalf of the resident anti-spam engine 138 and any other memory resident client application 140).
With respect to claims 5, 12 and 19, Fok-Khosla Vinod teaches the method, further comprising receiving a selection made by the user, at the UE, that causes the text corresponding to the message to be forwarded to the anti-spam engine (Fok, see paragraph [0074] all or a selected portion 173 of the given content 160 and/or information associated with the content, including but not limited to: the calculated filter test result 188; the content destination 172; and source information 186 identifying the originator of the content and including, for example, a URL, a telephone number, a MAC address, an E-mail address of the spam generator 122, and a an identification of the generating client application 140 on the wireless device. Paragraph [0075] discloses furthermore, for content 160 classified as spam content 163 and stored in a separate quarantine folder 188, anti-spam engine 138 may alert a user of wireless device 102 of their presence in order to initiate review of these content).
Claims 4, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Fok et al. (WO 2006105301 hereinafter Fok) in view of Khosla Vinod (WO 2022115508 hereinafter Khosla Vinod) further in view of Kumar et al. (US20170034101 hereinafter Kumar).
With respect to claims 4, 11 and 18, Fok-Khosla Vinod teaches the method, yet fails to explicitly discloses wherein the portion of the text forwarded to the anti-spam engine comprises a user-selected subset of the message that includes at least one of, a hyperlink, an attachment identifier, or a textual excerpt containing less than an entirety of the message.
However, Kumar discloses wherein the portion of the text forwarded to the anti-spam engine comprises a user-selected subset of the message that includes at least one of, a hyperlink, an attachment identifier, or a textual excerpt containing less than an entirety of the message (Kumar, see paragraph [0091] each of filters 1108-1120 may be implemented as an icon, button, or other hyperlink, which may be invoked (e.g., by clicking, placing a cursor over, or otherwise selected) to show a subset of the messages published on shared environment 1102).
It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to combine the teaching of Fok-Khosla Vinod with the teaching of Kumar to provide the method for an anti-spam engine that evaluates a user-selected snippet or specific subset of a message containing a hyperlink allows recipients to isolate, preview, and assess the true destination of embedded links. This targeted inspection prevents accidental clicks on masked malicious URLs while reducing processing overhead.
Claims 6-7, 13-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fok et al. (WO 2006105301 hereinafter Fok) in view of Khosla Vinod (WO 2022115508 hereinafter Khosla Vinod) further in view of Richardson et al. (US 20240314164 hereinafter Richardson).
With respect to claims 6 and 13, Fok-Khosla Vinod teaches the method, yet fails to explicitly discloses further comprising receiving a selection made by the user, at the UE, that causes the text corresponding to the message to be forwarded to a cybersecurity service.
However, Richardson discloses further comprising receiving a selection made by the user, at the UE, that causes the text corresponding to the message to be forwarded to a cybersecurity service (Richardson, see paragraphs [0027-0028] one or more detection models (i.e., interpreted as being equivalent to cybersecurity service) can be trained to accurately identify spear phishing email messages for specific categories of recipients. Multiple models can leverage generative artificial intelligence (AI) to multiple types (or modalities) of content to be included in these training communications, such as may include various AI generators to generate or synthesize text (including hyperlinks), images, and file attachments. … Paragraphs [0211-0217] further discloses the processor of clause, wherein the at least one filtering criterion includes detection of generation by an artificial intelligence (AI) generator or detection as a phishing attempt. Train the spear phishing detection model using a training dataset including the training communication; Provide a received communication as input to the spear phishing model).
It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to combine the teaching of Fok-Khosla Vinod with the teaching of Richardson to provide the method for receiving a user-initiated selection at the User Equipment (UE) to forward message text to a cybersecurity service offers several key advantages, primarily centered on enabling rapid, user-driven threat detection and improving organizational security posture.
With respect to claims 7, 14 and 20, Fok-Khosla Vinod-Richardson teaches the method, further comprising, upon the cybersecurity service being unable to determine if the text corresponding to the message is spam, causing the cybersecurity service to make an application programming interface (API) call to the anti-spam engine, the API call including the text corresponding to the message (Richardson, see paragraphs [0027-0028] one or more detection models (i.e., cybersecurity service) can be trained to accurately identify spear phishing email messages for specific categories of recipients. Content from these various modalities can be combined (or otherwise used) to form sample spear phishing communications, which can then be passed through one or more filters (to check for standard phishing content or AI-generated content) to determine whether the communication can be viewed as a good example of a spear phishing email. Paragraph [0247] further discloses oneAPI and/or oneAPI programming model is utilized to interact with various accelerator, GPU, processor, and/or variations thereof, architectures).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 ELIZABETH KASSA whose telephone number is (571)270-0567. The examiner can normally be reached on Monday -Friday 9 AM -6 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ario Etienne can be reached on 517-272-4001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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08/08/2026
/ELIZABETH KASSA/Examiner, Art Unit 2457 /ARIO ETIENNE/Supervisory Patent Examiner, Art Unit 2457
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