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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/22/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim(s) 1-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Villanueva Canizares et al., US-20250209204-A1 (hereinafter “Villanueva ‘204”) in view of Allen et al., US-20180276393-A1 (hereinafter “Allen ‘393”).
Per claim 1 (independent):
Villanueva ‘204 discloses: An image processing apparatus ([0063], The steps of the automated anonymization are executed by one processor of a personal computer, a laptop, a tablet, a smartphone or any programmable device (an image processing apparatus) providing an interface to input/output documents) comprising:
an image reading portion that reads a document containing personal information;
a control portion that performs an anonymizing process on original image data acquired through reading of the document by the image reading portion, the control portion thereby generating output image data in which the personal information is anonymized; and
a operation/display portion that displays information and that accepts an operation
(FIG. 1, [0027], 100 Anonymization or pseudonymization request: Interaction of the user through a graphical user interface (GUI) ... to input/output a document 10 (reads a document containing personal information – such as personal names, addresses, or phone numbers according to [0004], “in a text document, entities might include personal names, addresses, phone numbers, or other identifiers”); note that the GUI displays information and that accepts an operation, for example, inputting/outputting a document; [0028], 110 Classification of the document 10 to be anonymized according to its format; [0029], 120 Conversion (into original image data acquired through reading of the document by the image reading portion); [0030], 130 Application of optical character recognition (OCR); [0031], 140 Extraction of the content from the document 10 based on its type/format; [0032], 150 Application of a natural language processing (NLP) predictor model to detect personally identifiable information (PII); [0033], 160 Redaction and Masking of the anonymized document; [0034], If the document 10 is in image format 13, a previous step is added: a task of OCR 130 that converts the document content into text through the mixed content plugin 144 ... the redaction plugin corresponding to the detected format 12, retrieves the original document and apply the corresponding modifications (masking, blacklining, tokenization, etc. – an anonymizing process) (performs an anonymizing process on original image data acquired through reading of the document). The modified anonymized document is delivered 17 to the user through the GUI – generating output image data in which the personal information is anonymized);
when generating the output image data, the control portion
extracts text data by an OCR process on the original image data,
extracts the personal information from the text data,
recognizes as a target region a region of the original image data that contains the personal information selected by the information selection operation, and
performs as the anonymizing process a process of anonymizing the personal information in the target region by the anonymizing method
(FIG. 1, [0030], 130 Application of optical character recognition (OCR); [0031], 140 Extraction of the content from the document 10 based on its type/format (extracts text data by an OCR process on the original image data); [0032], 150 Application of a natural language processing (NLP) predictor model to detect personally identifiable information (PII) (extracts the personal information from the text data); [0033], 160 Redaction and Masking of the anonymized document; [0034], If the document 10 is in image format 13, a previous step is added: a task of OCR 130 that converts the document content into text through the mixed content plugin 144 ... the redaction plugin corresponding to the detected format 12 (recognizes as a target region a region of the original image data that contains the personal information selected by the information selection operation, which has been already performed at the step 100 through the GUI), retrieves the original document and apply the corresponding modifications (masking, blacklining, tokenization, etc.) (performs as the anonymizing process a process of anonymizing the personal information, i.e., the PPI, in the target region by the anonymizing method). The modified anonymized document is delivered 17 to the user through the GUI – generating the output image data).
Villanueva ‘204 does not disclose but Allen ‘393 discloses: the operation/display portion accepts
an information selection operation for selecting the personal information to be anonymized and
a method selection operation for selecting an anonymizing method for the personal information;
anonymizing the personal information in the target region by the method selected by the method selection operation
(FIG. 2, [0030], example configuration 200 of application DLP module 113; [0037], Once the specific locations of the sensitive data (the personal information in the target region) have been determined, then annotator 212 can be employed to mark or otherwise flag the sensitive data to a user (selecting the personal information to be anonymized); [0038], A user can be presented with one or more options when a particular annotation is selected ... Popup menu 202 can also include obfuscation options. Selection of one of the obfuscation options (selecting an anonymizing method for the personal information) can produce obfuscated content (anonymizing the personal information in the target region by the method selected by the method selection operation) that maintains a data scheme of the associated user content while maintaining the data scheme of the associated user content).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Villanueva ‘204 with the presentation of graphical annotations for sensitive user data along with selectable obfuscation options to be applied to the sensitive data as taught by Allen ‘393 because it would improve the efficiency and usability of data loss protection, including faster identification of sensitive comments [0018]. Additionally, Allen ‘393 is analogous to the claimed invention because it teaches that enhanced data loss protection (DLP) measures discussed herein can be incorporated to attempt to avoid misappropriation and misallocation of this sensitive data [0015].
Per claim 2 (dependent on claim 1):
Villanueva ‘204 in view of Allen ‘393 discloses the elements detailed in the rejection of claim 1 above, incorporated herein by reference.
Villanueva ‘204 discloses: The image processing apparatus according to claim 1, wherein
the control portion performs a first process and a second process as a process of extracting the personal information from the text data (As illustrated in FIG. 1, steps 140 through 150 correspond to a process of extracting the personal information from the text data),
the first process is a process of extracting as the personal information a character string corresponding to a predetermined regular expression, and
the second process is a process of extracting as the personal information a character string supposed to indicate predetermined information by using a machine learning model for extracting a proper noun
(FIG. 1, [0031], 140 Extraction of the content from the document 10 based on its type/format; [0032], 150 Application of a natural language processing (NLP) predictor model to detect personally identifiable information (PII) (the personal information from the text data); [0034], Once the step 140 is completed by applying the plugin, 141, 142, 143 or 144, corresponding to the detected format 12 of the document 10, the extracted content of the document 10 is loaded into the prediction model (a machine learning model for extracting a proper noun), which labels the PII (a character string to be extracted as the personal information) in the text 15 by using a combination of context-aware NLP detection and a patterns engine. Based on the PII labeling performed in the step 150; [0042], The prediction model itself (the machine learning model) is a neural network with the encoders, embeddings, weights of the network and six neurons, one for each infotype of context-based PII to be detected (person name, dates, company name, address, location and amount – corresponding to a predetermined regular expression and is a proper noun); note that the extracted character string is supplied to the NLP model to detect context-based PII, including a person name, address, and a location by a prediction – supposed to indicate predetermined information).
Per claim 3 (dependent on claim 2):
Villanueva ‘204 in view of Allen ‘393 discloses the elements detailed in the rejection of claim 2 above, incorporated herein by reference.
Villanueva ‘204 discloses: The image processing apparatus according to claim 2, wherein
the regular expression is previously determined based on at least one of character string patterns of telephone number, credit card number, mail address, date, and time
(FIG. 1, [0042], The prediction model itself is a neural network with the encoders, embeddings, weights of the network and six neurons, one for each infotype of context-based PII to be detected (person name, dates (date), company name, address, location and amount – the regular expression)).
Per claim 4 (dependent on claim 2):
Villanueva ‘204 in view of Allen ‘393 discloses the elements detailed in the rejection of claim 2 above, incorporated herein by reference.
Villanueva ‘204 discloses: The image processing apparatus according to claim 2, wherein
the predetermined information at least includes a personal name and a geographical name
(FIG. 1, [0042], The prediction model itself is a neural network with the encoders, embeddings, weights of the network and six neurons, one for each infotype of context-based PII to be detected (person name (a personal name), dates, company name, address (a geographical name), location and amount); note that the extracted character string is supplied to the NLP model to detect context-based PII, including a person name, address, and a location by a prediction – indicating the predetermined information).
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Villanueva ‘204 in view of Allen ‘393 and Kurian, US- 20180338056-A1 (hereinafter “Kurian ‘056”).
Per claim 6 (dependent on claim 1):
Villanueva ‘204 in view of Allen ‘393 discloses the elements detailed in the rejection of claim 1 above, incorporated herein by reference.
Villanueva ‘204 in view of Allen ‘393 does not disclose but Kurian ‘056 discloses: The image processing apparatus according to claim 1, further comprising: an output portion that performs an output process for the output image data (FIG. 1A, [0028], controlling secure printing, copying and/or scanning of a document, file, or the like; [0030], Printing/copying/scanning device 120 (The image processing apparatus) may be any time of document generation, production or reproduction device – performs an output process for the output image data. In some examples, the printing/copying/scanning device 120 may include a computing device controlling one or more aspects of the printing/copying/scanning device 120.),
wherein the output portion is at least either
a printing portion that, as the output process, prints an image based on the output image data on a sheet and
a communication portion that, as the output process, transmits the output image data to an external device
([0095], In some examples, if a user is not authorized to print a document including sensitive information, the document might not print. In other examples, it might print with the sensitive information redacted or otherwise obscured – prints an image based on the output image data on a sheet).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to have modified Villanueva ‘204 in view of Allen ‘393 with the printing of the document including the sensitive information redacted or otherwise obscured if a user is not authorized to print a document as taught by Kurian ‘056 because the document remains usable for its intended purpose without exposing sensitive information to unauthorized users. Additionally, Kurian ‘056 is analogous to the claimed invention because it teaches controlling secure printing, copying and/or scanning of a document, file, or the like [0028].
Allowable Subject Matter
Claim(s) 5 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 5, Villanueva ‘204 in view of Allen ‘393 does not disclose: “The image processing apparatus according to claim 1, wherein the operation/display portion accepts as the method selection operation an operation to select one of blacking-out, initial character extraction, and labeling,
when blacking-out is selected, the control portion performs as the anonymizing process a process of blacking out the personal information in the target region,
when initial character extraction is selected, the control portion performs as the anonymizing process a process of making unrecognizable any character other than an initial character in a character string constituting the personal information in the target region, and
when labeling is selected, the control portion performs as the anonymizing process a process of recognizing a labeling character string associated with a type of the personal information in the target region and replacing the personal information in the target region with the labeling character string” in the recited context.
Villanueva ‘204 teaches only the “blacking-out” anonymization among the three anonymization methods recited in the claim, but fails to disclose the remaining two methods. Moreover, this reference does not explicitly teach all three anonymization methods as selectable options or accepting a user operation to select one of those three methods, as required by the claim. In contrast, Allen ‘393 discloses that one of two obfuscation methods is selected through a GUI. However, it fails to teach any of the three claimed anonymization methods. Accordingly, Villanueva ‘204 in view of Allen ‘393 does not teach or suggest the claimed method selection operation that provides the three recited anonymization methods as selectable options.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
KATO, US-20240265716-A1 – the server receives the masked label image from the digital multifunction peripheral, analyzes the remaining label layout and variable-data fields, and generates label data representing the label format without requiring access the masked personal information.
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/SANGSEOK PARK/Primary Examiner, Art Unit 2499
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