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 is in response to the amendments filed on 07/20/2026. Claims 1-20. Claims 1-20 are currently pending and have been considered below.
Response to Arguments
Claims 1, 10 and 16 have been amended and therefore the objections are withdrawn.
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the
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.
Claim1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Turock et al. (US Publication No. 2024/0212804 A1) in view of Fox et al. (US Publication No. 20130185634 A1)
Regarding Claim 1:
Turock discloses:
A computer-implemented method, comprising: analyzing, using at least one processor, a content of an electronic document using a machine learning model, the machine learning model determines presence of a plurality of sensitive data in the electronic document(Turock, Claim 14, a computer system with a memory and a processor): [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. For example, Classification 111 is a technique used to assign arbitrary labels to input data. [0058], With Object Detection 114, the system can detect a range of objects in the environment, classify them and pinpoint their locations. [0059], determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.)
receiving, using the at least one processor, one or more document entity-based parameters(Turock, [0060], The list of people that need to be notified by Alert 133 can be determined based on involvement, authoritative hierarchy and responsibilities or Caseloads. [0055], Complex intersections of rules may be used to determine which groups in the images should be passed through without redaction and which should be redacted))
and identifying at least one sensitive data in the plurality of sensitive data(Turock, [0059], the condition and information from 121, it determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.,
extracting, using the at least one processor, the at least one sensitive data from the electronic document(Turock, [0080], As Semantic Segmentation 920 identifies objects based on class, it can be used to segment the environment into known classes as Segmented Regions 930. As segmentation enables identification of objects on a granular level);
and transmitting, using the at least one processor, the modified electronic document (Turock, [0007], redacting personally identifiable information for providing care, proof of service, and prevention of abuse and neglect based on that information.[0093], the system triggers a notification. First, identities in the incident are encrypted and deidentified (Deidentify, Encrypt, and Compress Alert Data 1802) according to caseloads and the access of the authorities concerned. The encrypted alert notification is then sent to the Alerting Service 1803, which in turn is sent to the authorities as an Alert 133. [0059], the filtered and privacy preserving information is ready for alerting authority or to record logs.).
Turock does not disclose:
modifying, using the at least one processor, the electronic document to redact the at least one sensitive data from the electronic document and generating a modified electronic document
to the at least one recipient computing device
Fox discloses:
modifying, using the at least one processor, the electronic document to redact the at least one sensitive data from the electronic document and generating a modified electronic document (Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106,… Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document);
to the at least one recipient computing device(Fox, [0024], the computer-based document may be provided to a recipient having the recipient role).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Fox in order to enhance controlled access to redacted electronic documents in a multi-recipient environment. The motivation is to ensure secure dissemination of electronic documents by preventing unauthorized access to sensitive information while still enabling delivery of a usable redacted document to authorized recipients.
Turock in view of Fox do not disclose:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data
as defined by the one or more document entity-based parameters.
Gupta discloses:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data as defined by the one or more document entity-based parameters.(Gupta, [0097], computing devices (e.g., user devices 305 1, . . . , user devices 305 N) are situated in client-side execution environment 380. Such computing devices communicate over the Internet (e.g., over network 311 1, . . . , over network 311 N)… the content object repository may be associated with any number of access parameters that are used to allow or deny or otherwise control whether or not a particular user can perform a particular operation over a particular content objects, [0039], he range of collaborators, their enterprise affiliation, their role in the enterprise, and so on, it sometimes happens that a slightly different document is autogenerated based on (1) the sensitivity level or security level of specific passages of the document…content object deep inspection module detects the presence of such “Eyes Only” clearance-designated passages (e.g., all or portions of the foregoing exhibit), then those “Eyes Only” clearance-designated passages need to be redacted such that those passages are presented only to web meeting participants who have the necessary security clearance, [0100], …the content object deep inspection module detects the presence of PII in the actual contents (e.g., the stored bits) of a content object, a post-process triggering module 304 might trigger redaction of that PII before allowing the PII to be accessed by any one of the participants. In some cases, rather than redacting the PII or other sensitive information, the PII or other sensitive information is rendered in only those user devices where the corresponding users do possess sufficient privileges to be able to view such PII or other sensitive information.).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock in view of Fox’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock in view of Fox’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Gupta in order to enhance recipient-specific control over the disclosure of sensitive information contained in electronic documents. The motivation is to ensure that sensitive information is provided only to recipient computing devices associated with users having the appropriate permissions or security clearance, thereby preventing unauthorized recipients from receiving or accessing sensitive portions of the electronic document.
Regarding Claim 2:
The method of claim 1, Turock in view of Fox in further view of Gupta disclose wherein the machine learning model is configured to determine the one or more document entity-based parameters based on at least one of: the content of the electronic document, a type of the electronic document, one or more parties associated with the electronic document, one or more computing devices sending and/or receiving the electronic document, and any combination thereof(Turock, [0074], the system may only be interested in the actions of a particular person. It may be preferable for the system to monitor that particular person's action so that it can detect any anomalous activity going on in the scene involving that person. [0060], The list of people that need to be notified by Alert 133 can be determined based on involvement, authoritative hierarchy and responsibilities or Caseloads. [0056], Data from Sensors 101 includes both data collected in real time as well as previously recorded sensor data that has been stored in computer memory. The raw sensor data about the environment is then transmitted to Extract, Load, and Transform Sensor Data 102. [0093], The encrypted alert notification is then sent to the Alerting Service 1803, which in turn is sent to the authorities as an Alert 133. An Alert 133 may be communicated by SMS 1811, Email 1812, Push Notifications 1813, Speaker 1814, or Other Means of Communication).
Regarding Claim 3:
The method of claim 2, Turock in view of Fox in further view of Gupta disclose wherein the machine learning model has been trained using at least one of: one or more historical electronic documents, one or more historical document entity-based parameters, content of the one or more historical electronic documents, a type of the one or more historical electronic documents, one or more parties associated with of the one or more historical electronic documents, one or more computing devices sending and/or receiving of the one or more historical electronic documents, and any combination thereof(Turock, [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. [0104], Natural Language Processing (NLP) 2203 is a process of giving computer systems the ability to interpret and process language in Text 2401 format. Sentiment Analysis 2411 predicts the sentiment expressed in a piece of Text 2401… [0104], Document Summarization 2451 summarizes Text 2401 in a concise or abbreviated version. [0067], As the system operates with a wide range of Sensors 101, It needs to be adapted to different modalities of data including Spatial Data 301, Tabular Data 302, Audio Data 303, Biometric Data 304 and Others 305. Spatial data are generated mainly from Cameras 201. Microphones 203 generate Audio Data 303, Biometric Sensors 206 generate Biometric Data 304, and so on).
Regarding Claim 4:
The method of claim 1, Turock in view of Fox in further view of Gupta disclose wherein a first document entity-based parameter in the one or more document entity-based parameters is associated with a first recipient computing device and is used by the machine learning model to identify at least one first sensitive data in the electronic document(Fox, [0023], A permission selector 110 is configured to identify one or more predefined permission expressions responsive to a recipient role and the value resulting from the expression selector 106 evaluation of the logic expression, [0022], An expression selector 106 is configured to identify one or more predefined logic expressions that are associated with redaction elements of the type identified by redaction candidate identifier 100 and that operate on evaluation elements of the type identified by evaluation element identifier 104.[0002], a set of predefined rules, such as where a rule dictates that a number that appears to be a credit card number be redacted from a document before it is provided to a recipient. Such rules may be further adapted based on the role of the recipient);
and a second document entity-based parameter in the one or more document entity-based parameters is associated with a second recipient computing device and is used by the machine learning model to identify at least one second sensitive data in the electronic document(Fox, [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role “visiting nurse.” Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles.);
wherein the first recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one second sensitive data, and the second recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one first sensitive data(Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles., [0023], a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role…) .
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 5:
The method of claim 4, Turock in view of Fox in further view of Gupta disclose wherein the modifying includes modifying the electronic document to redact the at least one first sensitive data from the electronic document and generating a first modified electronic document and modifying the electronic document to redact the at least one second sensitive data from the electronic document and generating a second modified electronic document(Turock, [0059], The redaction can be applied by replacing person pixels in an image data with black pixels or blurring or distorting the pixels… the filtered and privacy preserving information is ready for alerting authority or to record logs. [0061], Elements of the environment will be redacted from the display of viewers who are not supposed to see them.);
Regarding Claim 6:
The method of claim 5, Turock in view of Fox in further view of Gupta disclose wherein the first modified electronic document is transmitted to the first recipient computing device but not to the second recipient computing device, and the second modified electronic document is transmitted to the second recipient computing device but not to the first recipient computing device(Fox, [0002], a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0024], A document processor 114 is configured to apply the redaction directive identified by permission selector 110 to the candidate redaction element within the computer-based document, whereupon the computer-based document may be provided to a recipient having the recipient role).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 7:
The method of claim 1, Turock in view of Fox in further view of Gupta disclose further comprising generating a preview of the modified electronic document on a graphical user interface prior to the transmitting(Turock, [0059], the filtered and privacy preserving information is ready for alerting authority or to record logs. [0060], According to the type of event, concerned people are notified through Alert 133, the event is logged 132 and appropriate visualization of the environment is prepared in Display 131. [0056], The raw sensor data about the environment is then transmitted to Extract, Load, and Transform Sensor Data 102. At this stage, the system decrypts, extracts, loads data into computer memory, and transforms the sensor data fit for consumption by various machine learning models.)
Regarding Claim 8:
The method of claim 1, Turock in view of Fox in further view of Gupta disclose wherein the plurality of sensitive data includes at least one of the following: a text, an image, a graphic, a video, an audio, a clause in the electronic document, a sentence in the electronic document, a paragraph in the electronic document, a predetermined number of characters in the electronic document, and any combination thereof(Turock, [0067], As the system operates with a wide range of Sensors 101, It needs to be adapted to different modalities of data including Spatial Data 301, Tabular Data 302, Audio Data 303, Biometric Data 304 and Others 305. Spatial data are generated mainly from Camera 201. Microphones 203 generate Audio Data 303, Biometric Sensors 206 generate Biometric Data 304, and so on. [0104], Text Classification 2431 classifies text 2401 into predetermined labels. Optical Character Recognition (OCR) 2441 identifies characters in Text 2401 and can be useful to extract characters in documents and images).
Regarding Claim 9:
The method of claim 1, Turock in view of Fox in further view of Gupta disclose wherein the machine learning model includes at least one of the following: a generative artificial intelligence (AI) model, a large language model, and any combination thereof(Turock, [0104], Natural Language Processing (NLP) 2203 is a process of giving computer systems the ability to interpret and process language in Text 2401 format… Text Classification 2431 classifies text 2401 into predetermined labels. Optical Character Recognition (OCR) 2441 identifies characters in Text 2401 and can be useful to extract characters in documents and images... Document Summarization 2451 summarizes Text 2401 in a concise or abbreviated version. [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. For example, Classification 111 is a technique used to assign arbitrary labels to input data).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Fox in order to enhance controlled access to redacted electronic documents in a multi-recipient environment. The motivation is to ensure secure dissemination of electronic documents by preventing unauthorized access to sensitive information while still enabling delivery of a usable redacted document to authorized recipients.
Regarding Claim 10:
Turock discloses:
A system, comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the at least one processor to determine, using a machine learning model, presence of a plurality sensitive data in an electronic document based on a content of the electronic document(Turock, Claim 14, a computer system with a memory and a processor, [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. For example, Classification 111 is a technique used to assign arbitrary labels to input data. [0058], With Object Detection 114, the system can detect a range of objects in the environment, classify them and pinpoint their locations. [0059], determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.);
identify at least one sensitive data in a plurality of sensitive data based on one or more document entity-based parameters(Turock, [0059], the condition and information from 121, it determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.),
and transmit the modified electronic document(Turock, [0007], redacting personally identifiable information for providing care, proof of service, and prevention of abuse and neglect based on that information.[0093], the system triggers a notification. First, identities in the incident are encrypted and deidentified (Deidentify, Encrypt, and Compress Alert Data 1802) according to caseloads and the access of the authorities concerned. The encrypted alert notification is then sent to the Alerting Service 1803, which in turn is sent to the authorities as an Alert 133. [0059], the filtered and privacy preserving information is ready for alerting authority or to record logs.);
Turock does not disclose:
modify the electronic document to redact the at least one sensitive data from the electronic document and generate a modified electronic document
to the at least one recipient computing device
Fox discloses:
to the at least one recipient computing device(Fox, [0024], the computer-based document may be provided to a recipient having the recipient role).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Fox in order to enhance controlled access to redacted electronic documents in a multi-recipient environment. The motivation is to ensure secure dissemination of electronic documents by preventing unauthorized access to sensitive information while still enabling delivery of a usable redacted document to authorized recipients.
modify the electronic document to redact the at least one sensitive data from the electronic document and generate a modified electronic document(Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106,… Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document);
Turock does not disclose:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data as defined by the one or more document entity-based parameters
Gupta discloses:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data as defined by the one or more document entity-based parameters.(Gupta, [0097], computing devices (e.g., user devices 305 1, . . . , user devices 305 N) are situated in client-side execution environment 380. Such computing devices communicate over the Internet (e.g., over network 311 1, . . . , over network 311 N)… the content object repository may be associated with any number of access parameters that are used to allow or deny or otherwise control whether or not a particular user can perform a particular operation over a particular content objects, [0039], he range of collaborators, their enterprise affiliation, their role in the enterprise, and so on, it sometimes happens that a slightly different document is autogenerated based on (1) the sensitivity level or security level of specific passages of the document…content object deep inspection module detects the presence of such “Eyes Only” clearance-designated passages (e.g., all or portions of the foregoing exhibit), then those “Eyes Only” clearance-designated passages need to be redacted such that those passages are presented only to web meeting participants who have the necessary security clearance, [0100], …the content object deep inspection module detects the presence of PII in the actual contents (e.g., the stored bits) of a content object, a post-process triggering module 304 might trigger redaction of that PII before allowing the PII to be accessed by any one of the participants. In some cases, rather than redacting the PII or other sensitive information, the PII or other sensitive information is rendered in only those user devices where the corresponding users do possess sufficient privileges to be able to view such PII or other sensitive information.).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock in view of Fox’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock in view of Fox’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Gupta in order to enhance recipient-specific control over the disclosure of sensitive information contained in electronic documents. The motivation is to ensure that sensitive information is provided only to recipient computing devices associated with users having the appropriate permissions or security clearance, thereby preventing unauthorized recipients from receiving or accessing sensitive portions of the electronic document.
Regarding Claim 11:
The system of claim 10, Turock in view of Fox in further view of Gupta disclose wherein the machine learning model is configured to determine the one or more document entity-based parameters based on at least one of: the content of the electronic document, a type of the electronic document, one or more parties associated with the electronic document, one or more computing devices sending and/or receiving the electronic document, and any combination thereof(Turock, [0074], the system may only be interested in the actions of a particular person. It may be preferable for the system to monitor that particular person's action so that it can detect any anomalous activity going on in the scene involving that person. [0060], The list of people that need to be notified by Alert 133 can be determined based on involvement, authoritative hierarchy and responsibilities or Caseloads. [0056], Data from Sensors 101 includes both data collected in real time as well as previously recorded sensor data that has been stored in computer memory. The raw sensor data about the environment is then transmitted to Extract, Load, and Transform Sensor Data 102. [0093], The encrypted alert notification is then sent to the Alerting Service 1803, which in turn is sent to the authorities as an Alert 133. An Alert 133 may be communicated by SMS 1811, Email 1812, Push Notifications 1813, Speaker 1814, or Other Means of Communication).
Regarding Claim 12:
The system of claim 11, Turock in view of Fox in further view of Gupta disclose wherein the machine learning model has been trained using at least one of: one or more historical electronic documents, one or more historical document entity-based parameters, content of the one or more historical electronic documents, a type of the one or more historical electronic documents, one or more parties associated with of the one or more historical electronic documents, one or more computing devices sending and/or receiving of the one or more historical electronic documents, and any combination thereof(Turock, [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. [0104], Natural Language Processing (NLP) 2203 is a process of giving computer systems the ability to interpret and process language in Text 2401 format. Sentiment Analysis 2411 predicts the sentiment expressed in a piece of Text 2401… [0104], Document Summarization 2451 summarizes Text 2401 in a concise or abbreviated version. [0067], As the system operates with a wide range of Sensors 101, It needs to be adapted to different modalities of data including Spatial Data 301, Tabular Data 302, Audio Data 303, Biometric Data 304 and Others 305. Spatial data are generated mainly from Cameras 201. Microphones 203 generate Audio Data 303, Biometric Sensors 206 generate Biometric Data 304, and so on).
Regarding Claim 13:
The system of claim 10, Turock in view of Fox in further view of Gupta disclose wherein a first document entity-based parameter in the one or more document entity-based parameters is associated with a first recipient computing device and is used by the machine learning model to identify at least one first sensitive data in the electronic document(Fox, [0023], A permission selector 110 is configured to identify one or more predefined permission expressions responsive to a recipient role and the value resulting from the expression selector 106 evaluation of the logic expression, [0022], An expression selector 106 is configured to identify one or more predefined logic expressions that are associated with redaction elements of the type identified by redaction candidate identifier 100 and that operate on evaluation elements of the type identified by evaluation element identifier 104.[0002], a set of predefined rules, such as where a rule dictates that a number that appears to be a credit card number be redacted from a document before it is provided to a recipient. Such rules may be further adapted based on the role of the recipient);
and a second document entity-based parameter in the one or more document entity-based parameters is associated with a second recipient computing device and is used by the machine learning model to identify at least one second sensitive data in the electronic document(Fox, [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role “visiting nurse.” Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles.);
wherein the first recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one second sensitive data, and the second recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one first sensitive data(Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles., [0023], a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role…) .
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 14:
The system of claim 13, Turock in view of Fox in further view of Gupta disclose wherein modification of the electronic document includes modifying the electronic document to redact the at least one first sensitive data from the electronic document and generating a first modified electronic document; and modifying the electronic document to redact the at least one second sensitive data from the electronic document and generating a second modified electronic document(Turock, [0059], The redaction can be applied by replacing person pixels in an image data with black pixels or blurring or distorting the pixels… the filtered and privacy preserving information is ready for alerting authority or to record logs. [0061], Elements of the environment will be redacted from the display of viewers who are not supposed to see them.).
Regarding Claim 15:
The system of claim 14, Turock in view of Fox in further view of Gupta disclose wherein the first modified electronic document is transmitted to the first recipient computing device but not to the second recipient computing device, and the second modified electronic document is transmitted to the second recipient computing device but not to the first recipient computing device(Fox, [0002], a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0024], A document processor 114 is configured to apply the redaction directive identified by permission selector 110 to the candidate redaction element within the computer-based document, whereupon the computer-based document may be provided to a recipient having the recipient role).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 16:
Turock discloses:
A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by at least one processor, cause the at least one processor to: determine, using a machine learning model, presence of a plurality of sensitive data in an electronic document based on a content of the electronic document(Turock, [0057], Pretrained machine learning models can be used to make predictions about the environment of events/actions that might be useful for the application. For example, Classification 111 is a technique used to assign arbitrary labels to input data. [0058], With Object Detection 114, the system can detect a range of objects in the environment, classify them and pinpoint their locations. [0059], determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.);
identify at least one sensitive data in a plurality of sensitive data based on one or more document entity-based parameters(Turock, [0059], the condition and information from 121, it determines which individual should be redacted and which data should be redacted. It redacts any information by which the individual can be identified.),
generate a preview of the modified electronic document on a graphical user interface(Turock, [0059], the filtered and privacy preserving information is ready for alerting authority or to record logs. [0060], According to the type of event, concerned people are notified through Alert 133, the event is logged 132 and appropriate visualization of the environment is prepared in Display 131. [0056], The raw sensor data about the environment is then transmitted to Extract, Load, and Transform Sensor Data 102. At this stage, the system decrypts, extracts, loads data into computer memory, and transforms the sensor data fit for consumption by various machine learning models.);
and transmit the modified electronic document (Turock, [0007], redacting personally identifiable information for providing care, proof of service, and prevention of abuse and neglect based on that information.[0093], the system triggers a notification. First, identities in the incident are encrypted and deidentified (Deidentify, Encrypt, and Compress Alert Data 1802) according to caseloads and the access of the authorities concerned. The encrypted alert notification is then sent to the Alerting Service 1803, which in turn is sent to the authorities as an Alert 133. [0059], the filtered and privacy preserving information is ready for alerting authority or to record logs.);
Turock does not disclose:
generate a modified electronic document by modifying the electronic document to redact the at least one sensitive data from the electronic document
to the at least one recipient computing device
Fox discloses:
generate a modified electronic document by modifying the electronic document to redact the at least one sensitive data from the electronic document (Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106,… Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document);
to the at least one recipient computing device(Fox, [0024], the computer-based document may be provided to a recipient having the recipient role)
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Fox in order to enhance controlled access to redacted electronic documents in a multi-recipient environment. The motivation is to ensure secure dissemination of electronic documents by preventing unauthorized access to sensitive information while still enabling delivery of a usable redacted document to authorized recipients.
Turock in view of Fox does not disclose:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data as defined by the one or more document entity-based parameters
Gupta discloses:
wherein at least one recipient computing device in a plurality of computing devices is prevented from receiving the electronic document containing the at least one sensitive data as defined by the one or more document entity-based parameters(Gupta, [0097], computing devices (e.g., user devices 305 1, . . . , user devices 305 N) are situated in client-side execution environment 380. Such computing devices communicate over the Internet (e.g., over network 311 1, . . . , over network 311 N)… the content object repository may be associated with any number of access parameters that are used to allow or deny or otherwise control whether or not a particular user can perform a particular operation over a particular content objects, [0039], he range of collaborators, their enterprise affiliation, their role in the enterprise, and so on, it sometimes happens that a slightly different document is autogenerated based on (1) the sensitivity level or security level of specific passages of the document…content object deep inspection module detects the presence of such “Eyes Only” clearance-designated passages (e.g., all or portions of the foregoing exhibit), then those “Eyes Only” clearance-designated passages need to be redacted such that those passages are presented only to web meeting participants who have the necessary security clearance, [0100], …the content object deep inspection module detects the presence of PII in the actual contents (e.g., the stored bits) of a content object, a post-process triggering module 304 might trigger redaction of that PII before allowing the PII to be accessed by any one of the participants. In some cases, rather than redacting the PII or other sensitive information, the PII or other sensitive information is rendered in only those user devices where the corresponding users do possess sufficient privileges to be able to view such PII or other sensitive information.).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock in view of Fox’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock in view of Fox’s systems for transmitting a modified electronic document to a recipient computing device after redaction to ensure that sensitive data identified within the document is removed prior to delivery to a recipient as taught by Gupta in order to enhance recipient-specific control over the disclosure of sensitive information contained in electronic documents. The motivation is to ensure that sensitive information is provided only to recipient computing devices associated with users having the appropriate permissions or security clearance, thereby preventing unauthorized recipients from receiving or accessing sensitive portions of the electronic document.
Regarding Claim 17:
The non-transitory computer-readable storage medium of claim 16, Turock in view of Fox in further view of Gupta disclose wherein a first document entity-based parameter in the one or more document entity-based parameters is associated with a first recipient computing device and is used by the machine learning model to identify at least one first sensitive data in the electronic document(Fox, [0023], A permission selector 110 is configured to identify one or more predefined permission expressions responsive to a recipient role and the value resulting from the expression selector 106 evaluation of the logic expression, [0022], An expression selector 106 is configured to identify one or more predefined logic expressions that are associated with redaction elements of the type identified by redaction candidate identifier 100 and that operate on evaluation elements of the type identified by evaluation element identifier 104.[0002], a set of predefined rules, such as where a rule dictates that a number that appears to be a credit card number be redacted from a document before it is provided to a recipient. Such rules may be further adapted based on the role of the recipient);
and a second document entity-based parameter in the one or more document entity-based parameters is associated with a second recipient computing device and is used by the machine learning model to identify at least one second sensitive data in the electronic document(Fox, [0023], permission selector 110 may be configured to identify a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role “visiting nurse.” Permission selector 110 is also preferably configured to evaluate the permission expression, where the evaluation results in a redaction directive that determines whether or not the candidate redaction element is redacted from the computer-readable document, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles.);
wherein the first recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one second sensitive data, and the second recipient computing device in the plurality of computing devices is prevented from receiving the electronic document containing the at least one first sensitive data(Fox, [0002], Such rules may be further adapted based on the role of the recipient, such where a rule dictates that a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles., [0023], a permission expression that is associated with the logic expression identified by expression selector 106, that operates on the value resulting from the evaluation of the logic expression, and that is associated with the recipient role…) .
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 18:
The non-transitory computer-readable storage medium of claim 17, Turock in view of Fox in further view of Gupta disclose wherein modification of the electronic document includes modifying the electronic document to redact the at least one first sensitive data from the electronic document and generating a first modified electronic document; and modifying the electronic document to redact the at least one second sensitive data from the electronic document and generating a second modified electronic document(Turock, [0059], The redaction can be applied by replacing person pixels in an image data with black pixels or blurring or distorting the pixels… the filtered and privacy preserving information is ready for alerting authority or to record logs. [0061], Elements of the environment will be redacted from the display of viewers who are not supposed to see them.).
Regarding Claim 19:
The non-transitory computer-readable storage medium of claim 18, Turock in view of Fox in further view of Gupta disclose wherein the first modified electronic document is transmitted to the first recipient computing device but not to the second recipient computing device, and the second modified electronic document is transmitted to the second recipient computing device but not to the first recipient computing device(Fox, [0002], a credit card number be left in a document that is provided to an accounts receivable clerk and redacted from the document before the document is provided to recipients in other roles. [0024], A document processor 114 is configured to apply the redaction directive identified by permission selector 110 to the candidate redaction element within the computer-based document, whereupon the computer-based document may be provided to a recipient having the recipient role).
Before the effective filing date of the claimed invention, it would have been obvious to one with ordinary skill in the art to modify Turock’s automated non-invasive artificial intelligence machine learning method and system for identifying and redacting personally identifiable information by enhancing Turock’s systems for using recipient-specific parameters to determine which sensitive data is identified and redacted for different recipients to ensure that different portions of sensitive data are selectively withheld based on the intended recipient as taught by Fox in order to enhance role-based access control and generation of different redacted versions of an electronic document for different recipients. The motivation is to ensure that each recipient is prevented from accessing sensitive data not authorized for that recipient while allowing access to other permitted portions of the document, thereby preventing unauthorized disclosure of sensitive information in multi-recipient environments.
Regarding Claim 20:
The non-transitory computer-readable storage medium of claim 16, Turock in view of Fox in further view of Gupta disclose wherein the plurality of sensitive data includes at least one of the following: a text, an image, a graphic, a video, an audio, a clause in the electronic document, a sentence in the electronic document, a paragraph in the electronic document, a predetermined number of characters in the electronic document, and any combination thereof(Turock, [0067], As the system operates with a wide range of Sensors 101, It needs to be adapted to different modalities of data including Spatial Data 301, Tabular Data 302, Audio Data 303, Biometric Data 304 and Others 305. Spatial data are generated mainly from Camera 201. Microphones 203 generate Audio Data 303, Biometric Sensors 206 generate Biometric Data 304, and so on. [0104], Text Classification 2431 classifies text 2401 into predetermined labels. Optical Character Recognition (OCR) 2441 identifies characters in Text 2401 and can be useful to extract characters in documents and images).
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 MAYASA SHAAWAT whose telephone number is (571)272-3939. The examiner can normally be reached on M-F, 8 AM TO 5 PM.
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/MAYASA SHAAWAT/
Examiner, Art Unit 2433
/JEFFREY C PWU/Supervisory Patent Examiner, Art Unit 2433
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