Hide sensitive information in text

Abstract

Disclosed herein are systems, methods, and software for presenting sensitive information according to a concealment level. In an implementation, an object including text having sensitive information is identified. Then, a contextual privacy setting for the sensitive information and a context surrounding the presentation of the object are identified. A concealment level for the sensitive information in the text is determined based on the contextual privacy setting and the context surrounding the presentation of the object. The object including the text is presented, wherein the sensitive information included in the text is revealed according to the concealment level.

Description

Technical Field

[0001] Aspects of the present disclosure relate to computing hardware and software techniques, and in particular to revealing sensitive information included in text according to a level of concealment. Background Art

[0002] Many software applications provide users with the ability to create and recall documents and digital notes. These software applications include related utilities that provide user interface technologies for inserting and storing various user information. In some scenarios, the user information may include user sensitive information, such as passwords and credit card numbers. When accessing user information stored in previously created documents and digital notes, the user may not want to present the sensitive information to the user visually or audibly along with the rest of the information, especially when the user is not in a secure environment. In addition, users who share their documents or digital notepads with other users or between other devices may not want to share user sensitive information with other users or on unsafe devices and networks.

[0003] In order to display user information in an unsafe environment, the user may be required to manually parse the document or digital notepad to identify user sensitive data and delete or obfuscate the characters of the user sensitive information. Even if the user sensitive data is identified, the user may not be able to dynamically assign which environments are safe enough to present the user sensitive information to the user. In addition, there may be certain users and devices that are authorized to view or eavesdrop on user sensitive information, while other users and devices may not be. Unfortunately, software applications for presenting user content in documents or digital notes do not allow users to dynamically assign environments where sensitive information may be included in the text when presenting the content of the document or digital note to the user. Summary of the invention

[0004] Disclosed herein are enhanced systems, methods, and software applications that improve hiding of sensitive information contained in text. In an implementation, an object including text having sensitive information is identified. Then, a contextual privacy setting for the sensitive information and a context surrounding the presentation of the object are identified. Based on the contextual privacy setting and the context surrounding the presentation of the object, a level of hiding for the sensitive information in the text is determined. Then, the object including the text is presented. The sensitive information included in the text is revealed based on the level of hiding.

[0005] This summary is provided to introduce some concepts in a simplified form, which will be further described in the detailed description below. This summary is neither intended to identify the key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Additional aspects, features and / or advantages of the examples will be set forth in part in the description below, and in part will be apparent from the description, or may be learned through practice of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Many aspects of the present disclosure can be better understood with reference to the following drawings. Although several implementations are described in conjunction with these drawings, the present disclosure is not limited to the implementations disclosed herein. On the contrary, it is intended to cover all alternatives, modifications and equivalent forms.

[0007] Figure 1 An operational architecture for implementing an enhanced application to reveal sensitive information included in text according to a hiding level is illustrated.

[0008] Figure 2A-2B The diagram illustrates a secure presentation process used in implementing an enhanced application to reveal sensitive information included in a text according to a hiding level.

[0009] Figure 3 The data structure in the process of implementing an enhanced application to reveal sensitive information included in a text according to a hiding level is illustrated.

[0010] Figure 4 An operational architecture in implementing an enhanced application to reveal sensitive information included in text according to a hiding level is illustrated.

[0011] Figure 5 Illustrated are alternative operational architectures in implementing an enhanced application to reveal sensitive information included in text according to a level of concealment.

[0012] Figure 6 Illustrated are alternative operational architectures in implementing an enhanced application to reveal sensitive information included in text according to a level of concealment.

[0013] Figure 7 Illustrated are alternative operational architectures in implementing an enhanced application to reveal sensitive information included in text according to a level of concealment.

[0014] Figure 8 Illustrated are alternative operational architectures in implementing an enhanced application to reveal sensitive information included in text according to a level of concealment.

[0015] Fig. 9A computing system suitable for implementing the techniques disclosed herein is illustrated, including any of the architectures, processes, operating scenarios, and operating sequences illustrated in the figures and discussed in the technical description that follows. DETAILED DESCRIPTION

[0016] The example of the present disclosure describes an application for hiding sensitive information included in text. In an implementation, an object including text having sensitive information is identified. Then, a contextual privacy setting for the sensitive information and a context surrounding the presentation of the object are identified. Based on the contextual privacy setting and the context surrounding the presentation of the object, a hiding level for the sensitive information in the text is determined. Then, the object including the text is presented. The sensitive information included in the text is revealed according to the hiding level.

[0017] The technical effect that can be appreciated from this discussion is the improved efficiency in the process of determining which information in an object is sensitive based on the type of environment in which the information is accessed. For example, a user may not want some parts of the text to be presented in an unsafe environment (e.g., auditorily reciting sensitive information, accessing sensitive information through a public network or an unsafe device, sharing text including sensitive information with other users, etc.). Another technical effect that can be appreciated from this discussion is the improved efficiency, which allows users to dynamically specify which types of information should be assigned as sensitive based on several factors that constitute the environment (e.g., user type, user identity, access network, presentation mode, synchronization device, etc.). The application described in this article also improves efficiency, which allows third-party administrators to generate privacy settings for sensitive information that may be of interest to third parties (e.g., company security settings regarding what types of content may be accessed in an unsafe environment or shared with unauthorized users).

[0018] In addition, the examples herein describe receiving user input including text before identifying an object including text. Then, the text is identified for sensitive information. Further in this example, contextual privacy settings are configured for sensitive information. Then, the contextual privacy settings are stored in association with the object including text with sensitive information. In some scenarios, the text is checked for sensitive information by identifying at least one of a keyword, symbol, user indication, or formatting style associated with the sensitive information. In other scenarios, the text is checked for sensitive information by tracking indicators associated with the sensitive information to be ingested by a machine learning system to identify sensitive information in a cloud-based data repository.

[0019] In some scenarios, the context of presentation around an object can be identified based on a request to share the object with at least one additional user or device. For example, the object can be accessed by displaying text from the object in a presentation mode or using a desktop screen sharing application. In other scenarios, the context of presentation around the object can be identified based on a request to present the object auditorily to a user. For example, a digital note including text can be requested for reading aloud by a user. In this example, sensitive information can be determined to be omitted based on a determination that the digital note is being presented in an unsafe environment.

[0020] In some implementations, the context surrounding the presentation of an object may be identified based on a request to access the object over an unsecured network. For example, an email accessed at a coffee shop using a public network may be determined to be an unsecured environment for displaying confidential information in the message. In other implementations, the context surrounding the presentation of an object may be identified based on a request to access the object using at least one of a user-configured fingerprint or facial recognition. For example, when a user uses facial recognition technology to unlock a device presenting sensitive information, it may be determined that a digital notepad is being accessed in a secure environment.

[0021] In yet another example, the sensitive information included in the text is revealed according to the level of hiding by blurring the sensitive information, confusing the sensitive information, flipping the digital content card including the sensitive information, omitting the sensitive information. For example, if the level of hiding is high, the sensitive information can be hidden by flipping the digital content card on the user's home screen of the user's device to prevent display viewing. If the level of hiding is low, such as when the user opens the object including the text with an authorized fingerprint, the sensitive information included in the text can be fully revealed to the user. In another aspect, the level of hiding can be determined to be medium. In this example, the sensitive information included in the text can be disclosed to a specified degree, such as by distorting the sensitive information using blurring techniques, aliases, rearranging characters, confusing sensitive information, etc.

[0022] With reference to the accompanying drawings, Figure 1 An exemplary operating environment 100 is illustrated in connection with processing operations for managing an exemplary augmented system with which aspects of the present disclosure may be practiced. The operating environment 100 includes a computing system 101 having an application 103. The application 103 employs a secure rendering process 200 in the context of generating a view in a user interface 105. The user interface 105 displays an object including text that includes sensitive information generated by the computing system 101.

[0023] Computing system 101 represents any device capable of running applications locally or in the context of a web browser, streaming applications, or executing applications in any other manner. Examples of computing system 101 include, but are not limited to: a personal computer, a mobile phone, a tablet computer, a desktop computer, a laptop computer, a wearable computing device, or any other form factor including any combination of computers or variations thereof. Computing system 101 may include various hardware and software elements in a supporting architecture suitable for executing secure presentation process 200. In Fig. 9 One such representative architecture is illustrated in FIG. 9 with respect to computing system 901 .

[0024] Application 103 includes a software application or application component that is capable of revealing sensitive information included in the text based on the level of concealment according to the process described herein. Examples of software applications include, but are not limited to, note-taking applications, document drafting applications, spreadsheet applications, presentation applications, messaging applications (e.g., email and text messaging), and any other types of combinations or variations thereof. The software application can be implemented as a locally installed and executed application, a web application hosted in the context of a browser, a streamed or streaming application, a mobile application, or any variation or combination thereof.

[0025] User interface 105 includes a representative view 110 that can be generated by application 103. Representative view 110 can present an object including text. Sensitive information included in the text is revealed according to the level of hiding. End users can use user interface 105 to interface with application 103 to view objects including text with sensitive information visual representation 110. Users can use input instruments such as stylus, mouse device, keyboard, touch gestures and any other suitable input device to interface with application 103 through user interface 105. Users can initiate commands to add user input including text, which can be stored in contextual privacy settings associated with objects including sensitive information. Then, users can initiate commands to access or view stored objects including text, which include sensitive information. In enhancement, application 103 provides users with the ability to initiate commands to assign a portion of the text in an object as sensitive information. Users or third parties (e.g., company administrators) can also initiate commands to assign what type of environment is safe for each portion of the text including sensitive information.

[0026] More specifically, Figure 2A-2BThe secure presentation process 200 is illustrated, which, as mentioned above, can be used by the application 103 to reveal sensitive information included in the text according to the level of concealment described herein. Some or all of the steps of the secure presentation process 200 can be implemented as program instructions in the context of one or more components of the application for performing the secure presentation feature. The program instructions direct the computing system 101 to operate as follows, with reference to Figure 1 in the context of Figure 2A steps.

[0027] Figure 2A Can be used with Figure 1 1 at time 1 in the application 103. In operation, the application 103 receives a user input including text 130 contained in the object 120 (step 201). The application 103 may use an input instrument such as a stylus, a mouse device, a keyboard, a touch gesture, and any other suitable input device to receive the user input including the text 130. The object 120 may be a digital note page, a digital note, a document, a spreadsheet, a presentation slide, an electronic message (i.e., a text message or an email message), or any other file item or formatted data that allows the user to enter the text 130. For example, the user may enter the text into a virtual note. In this scenario, the virtual note may include the object 120, and the text may include the text 130. The text 130 may include various information in a range of sensitivity levels. For example, the text 130 includes a title of the virtual note (i.e., money management), a web page to be accessed related to the subject of the virtual note, and a user name and password for accessing a user portal on the web page. In this example, the title and the web page may not be assigned as sensitive information, while the user name and password are assigned as sensitive information.

[0028] Then, application 103 checks text 130 for sensitive information 140 (step 202). Application 103 can check text 130 for sensitive information 140 by identifying that a portion of text 130 contains keywords or symbols indicating that the portion of text 130 includes sensitive information 140. For example, application 103 can identify the words "username" and "password" to determine that the portion after each keyword in text 130 includes sensitive information 140. In other scenarios, application 103 can check text 130 for sensitive information 140 by identifying that a portion of text 130 contains a pattern or formatting style indicating that the portion of text includes sensitive information. For example, application 103 can determine that when a number is in a format similar to a social security number (e.g., 00-00-0000), the number may be a social security number. In another example, application 103 can determine that a portion of text 130 containing a combination of letters, numbers, and symbols (e.g., Lky9x#) indicates that the portion of text 130 may be a password. In some implementations, the user can enter additional data indicating which portions of text 130 include sensitive information 140. For example, the user can select / highlight a portion of text 130 and mark that portion as sensitive information for application 103.

[0029] In other cases, text 130 is checked for sensitive information 140 by tracking indicators associated with sensitive information 140 in a cloud-based data repository. The tracked indicators are then ingested by a machine learning system to identify sensitive information 140. The machine learning system may analyze text 130 in real time or at a later time to determine sensitive information 140. Computing system 101 may transmit object 120 including text 130 to be checked by the machine learning system. Computing system 101 may then receive data indicating which portions of text 130 include sensitive information.

[0030] Alternatively, the algorithms used in the machine learning environment can be transferred to the computing system 101 and used locally by the application 103 to check the text 130 for sensitive information 140. Advantageously, this can ensure that the sensitive information 140 is not transferred to an external system before it is checked. In some scenarios, the application 103 can be implemented in part or in whole as a locally installed and executed application, a web application hosted in the context of a browser, a streamed or streaming application, a mobile application, or any variation or combination thereof. Therefore, it should be noted that the inspection can be performed locally by the application 103, by an application service external to the computing system 101, or by a combination of a locally installed and executed application, a web application, a streaming application, a mobile application, etc.

[0031] In the next operation, the application 103 configures contextual privacy settings for the sensitive information 140 (step 203). The contextual privacy settings for the sensitive information 140 may include classifying the sensitive information 140 as a type of sensitive information (e.g., confidential work information, private personal information, access-restricted group information, etc.). The contextual privacy settings may also include a sensitivity measurement. For example, information related to secret work may be marked as highly sensitive information. However, an employee's phone number may be marked as mildly sensitive information. The contextual privacy settings may be determined by the application 103 using a machine learning algorithm that is established using contextual privacy settings for tracking of similar types of sensitive information. The application 103 may also determine the contextual privacy settings based on preferences associated with the type of sensitive information. For example, an administrator of a company may set a highly confidential product name as highly sensitive information.

[0032] Once the contextual privacy settings have been configured, the application 103 stores the contextual privacy settings in association with the object 120 including the text 130 having the sensitive information 140 (step 204). The application 103 may store the contextual privacy settings in association with the object 120 by including a flag indicating that a portion of the text 130 is sensitive, the type of sensitive information that the sensitive information 140 includes, and the level of sensitivity associated with the sensitive information 140. In some examples, the contextual privacy settings may be stored using metadata, key-value pairs, strings, or any other data associated with the object 120, the text 130, and / or the sensitive information 140.

[0033] Figure 2B Can be used with Figure 1 Attached to the representative view 110 at time 2 in Figure 1 Reference in context Figure 2B In the steps in , application 103 identifies object 120 including text 130 with sensitive information 140 (step 205). Application 103 can identify object 120 in response to receiving a request to view text 130 contained in object 120. For example, a user can request to open a virtual note while using a presentation mode on a user device. In another example, a user can request to read text 130 to the user using a smart speaker enabled by a virtual assistant. In other scenarios, object 120 can be identified by application 103 in response to being attached to an email or text message. For example, a user can view object 120 directly without requesting. However, object 120 can still be identified in response to a user selecting an object 120 to be shared with other users. In some implementations, application 103 can identify object 120 in a passive mode, such as when a digital note is displayed on the home screen of a computing device.

[0034] In the next operation, the application 103 identifies the contextual privacy setting for the sensitive information 140 (step 206). As previously discussed, the contextual privacy setting for the sensitive information 140 can be indicated by metadata, key-value pairs, strings, or other data associated with the object 120, the text 130, and / or the sensitive information 140. Based on a flag or any other type of assignment method that allows the application 103 to identify the contextual privacy setting for the sensitive information 140, the application 103 can determine that the sensitive information 140 is present in the object 120, that the portion of the text 130 includes the sensitive information 140, and the type and level of sensitivity associated with the sensitive information 140.

[0035] Then, the application 103 identifies the context surrounding the presentation of the object 120 (step 207). In some scenarios, the context surrounding the presentation of the object 120 may be identified based on a request to share the object 120 with at least one additional user or device. For example, the application 103 may be instructed to share a screen display object 120 to be viewed by other users with an additional user device. In addition, the context surrounding the presentation of the object 120 may be determined based on the identity of the additional user or device sharing the screen with the computing system 101.

[0036] For example, if the screen display object 120 is shared with authorized users, the context of presentation around the object 120 may be determined to be safe. Alternatively, a general instruction to display the object 120 including the text 130 in a general presentation mode may indicate that the context of presentation around the object 120 is unsafe. Figure 1 , application 103 has been directed to display in a presentation mode an object 120 that may be viewed by an additional user. In other scenarios, application 103 may be directed to synchronize the latest version of object 120 with other devices accessible to the user of computing device 101 or additional users.

[0037] In some implementations, the context surrounding the presentation of the object 120 may be identified based on a request to audibly present the object 120 to a user. For example, a digital note including the text 130 may be requested to be read aloud by a virtual assistant-enabled smart speaker. In another example, the application 103 may also be directed to determine the number of additional users located within a close distance from the computing system 101. For example, in addition to being directed to audibly recite the text 130 of the object 120, the application 103 may also be instructed to determine how many additional users will likely eavesdrop on the audible presentation of the object 120. If too many additional users are located within a close enough distance from the computing device 101, the context surrounding the presentation of the object 120 may be determined to be unsafe.

[0038] Application 103 may determine that additional users are in the same vicinity of computing system 101 based on detection of additional speech generating audio input to computing system 101, detection of additional computing systems (e.g., based on signal strength), detection of signals from Internet of Things (IoT) devices indicating the presence of additional users, or any other indicator that additional users are located close enough to computing device 101 to hear the auditory recitation of text 130 in object 120. For example, application 103 may determine the number of additional users located in close enough vicinity to computing device 101 by detecting three additional speech using audio input data received in the area of ​​computing device 101. In another example, application 103 may determine that ten additional users are located in close enough vicinity to computing device 101 by receiving signaling and data from ten additional computing devices (e.g., detected personal hotspots, Bluetooth signaling, cellular network signaling, WIFI signaling, global positioning system (GPS) coordinates, etc. received from the additional computing devices).

[0039] In some examples, the context surrounding the presentation of object 120 may be identified based on the type of network through which the request accesses object 120. For example, the context surrounding the presentation of object 120 may be identified as unsecure based on a request to remotely access object 120 through a public network and view text 130. In another example, the context surrounding the presentation of object 120 may be identified as secure based on a request to access object 120 through a work private network instead of a personal private network, and vice versa.

[0040] In other implementations, the context surrounding the presentation of object 120 may be identified based on a request to access object 120 using a user-configured fingerprint, facial recognition, retinal scan, password, voice recognition, or some other technique that verifies the user's identity when accessing object 120. For example, when a user unlocks computing device 101 presenting object 120 using facial recognition technology, it may be determined that a digital notepad is being accessed in a secure environment. In another example, the context surrounding the presentation of object 120 may be identified based on whether access to computing system 101, application 103, and / or object 120 requires execution of an authentication method. For example, if application 103 requires the user to authenticate their voice to open object 120, application 103 may determine that the context surrounding the presentation of object 120 is secure.

[0041] In response to identifying the contextual privacy setting for sensitive information 140 and the context surrounding the presentation of object 120, application 103 determines a hiding level for sensitive information 140 in text 130 (step 208). It should be noted that different contextual privacy settings may result in different levels of hiding levels depending on the context surrounding the presentation of object 120. For example, when object 120 having a high-sensitivity contextual privacy setting is displayed in a secure context surrounding the presentation of object 120, object 120 may be associated with a low level of hiding. On the other hand, when object 120 has a high-sensitivity contextual privacy setting but is presented around in an unsafe context, sensitive information 140 in text 130 may be completely hidden from view or omitted from the audio presentation.

[0042] In some scenarios, the level of hiding can indicate the degree of hiding that should be applied to sensitive information 140 when included in text 130. For example, sensitive information 140 can be hidden only to a certain extent by blurring sensitive information, rearranging characters, obfuscating information, using aliases or code words representing sensitive information, flipping virtual content cards including sensitive information 140, etc. The level of hiding can indicate how sensitive information 140 should be displayed, what types of sensitive information 140 should be displayed, and which additional users can view / hear sensitive information 140. For example, a password stored in a digital note that is not opened using facial recognition of the user can be fully displayed to the user. Therefore, the level of hiding will be low. Alternatively, text including a confidential company name can have a high level of hiding when accessed using an unauthorized user or on a public network.

[0043] In the final operation, the application 103 presents an object 120 including text 130, wherein the sensitive information 140 contained in the text 130 is revealed according to the level of hiding (step 209). The sensitive information 140 can be revealed to the user according to the level of hiding by blurring the sensitive information, confusing the sensitive information, flipping the digital content card including the sensitive information, or omitting the sensitive information. For example, a digital note listing the username and password for the user can be displayed on the desktop screen for the user. If the level of hiding is high, the digital note can be placed upside down to prevent additional users from viewing the sensitive information. In another example, when the application 103 is directed to present the text 130 auditorily from the object 120, the application 103 can determine to omit the sensitive information 140 when presenting the text 130 auditorily based on the determined high level of hiding.

[0044] Figure 3 A data structure 300 is illustrated, which represents a data structure that determines the level of concealment associated with confidential product information for a company. Figure 3, data structure 300 includes columns 301-304. In particular, column 301 includes access networks. Private access networks can be associated with high, medium, or low concealment levels. However, using a public network to access confidential product information will always result in a high concealment level. Column 302 includes a list of authorized users. For example, user A is authorized to view confidential product information, so user A may have a low or medium concealment level. Alternatively, user B is unauthorized. Therefore, even if user B is using a private network to access confidential product information, the concealment level of the confidential product information when accessed by user B is high.

[0045] In the next column, column 303 indicates the display mode used to present the confidential product information to the user. For example, when user A accesses the confidential product information using an isolated screen, the concealment level associated with the confidential product information is low. When user A accesses the confidential product information using a shared screen environment, the concealment level associated with the confidential product information is medium. However, when user A accesses the confidential product information using an auditory presentation method, the concealment level associated with the confidential product information is high. Column 304 indicates the associated concealment level based on the contextual privacy setting for the confidential product information and the context surrounding the presentation of the confidential product information.

[0046] Figure 4 An exemplary operational architecture for revealing sensitive information included in text according to levels of concealment that may be used in one or more scenarios of the present technology is illustrated. Figure 4 An operational scenario 400 is illustrated relating to what happens when a user requests that text from a digital note be audibly read to the user. The operational scenario 400 includes an application service 401, a user interface 410, a digital note 420, text 430, and sensitive information 440. The operational scenario 400 also includes a user device 402, a user device 403, an additional user 404, and an additional user 405.

[0047] In operation, at time 1, application service 401 receives user input including text 430 contained in digital note 420. In this scenario, text 430 includes a list of items (i.e., buy milk and pick up medicine Y). Once text 430 has been entered into digital note 420, application service 401 checks text 430 for sensitive information 440. In this exemplary scenario, the user has marked the name of the prescription drug (drug Y) as sensitive information. Based on this indication from the user, application service 401 configures contextual privacy settings for sensitive information 440. The contextual privacy settings can be determined by the user when marking sensitive information 440. However, in other scenarios, contextual privacy settings can be determined by application service 401 based on previous user preferences, administrative security settings, machine learning algorithms, or some other methods of determining contextual privacy settings. Once the contextual privacy settings have been configured, application service 401 stores the contextual privacy settings in association with the digital note 420 including text 430 with sensitive information 440.

[0048] In the next operation, at time 2, the application service 401 identifies a digital note 420 including text 430 with sensitive information 440. In this example, the user of the user device 402 requests that the information be read aloud to the user using a virtual assistant-enabled smart speaker. The application service 401 then identifies contextual privacy settings for the sensitive information 440. For example, the application service 401 may determine that the sensitive information 440 has a medium level of concealment and, therefore, should be aurally recited only in a secure environment, omitted in an unsecure environment, and aurally recited using a code name or alias in a semi-secure environment.

[0049] Next, application service 401 identifies the context surrounding the auditory presentation of digital note 420. In this scenario, application service 401 requests additional user information from user device 402 to determine the context surrounding the auditory presentation of digital note 420. For example, user device 402 may detect a wireless signal from user 403 indicating that another user may be present. Additionally, user device 402 may receive voice data of audio input from additional users 404-405 indicating that the additional users may be in close proximity to user device 402. Although not in Figure 4 , but in some scenarios, the user device 402 may also be configured to determine the identity of the additional user based on an identifier of the additional user device, an identity associated with the additional user's voice, an identifier associated with the additional user's facial recognition profile, etc. The user device 402 may then transmit the additional user information to the application service 401 to determine the context surrounding the auditory presentation of the digital note 420.

[0050] In response to identifying the contextual privacy setting for sensitive information 440 and the context surrounding the presentation of digital note 420, application service 401 determines a level of concealment for sensitive information 440 in text 430. For example, application service 401 may determine that when text 430 is aurally recited in a semi-secure environment, sensitive information 440 should be aurally recited using a code word. The code word may be pre-configured by application service 401, identified using machine learning techniques, assigned by the user, pre-configured by the manufacturer of the user device, and the like. In this example, application service 401 also analyzes the number (and possible identities) of additional users to determine whether sensitive information 440 should be aurally recited to the user of user device 402. In a final operation, user device 402 aurally presents digital note 420 including text 430. In this example, sensitive information 440 included in text 430 is revealed to the user to a certain extent according to the level of concealment. For example, a list of items from digital note 420 is aurally recited to the user with the name "Drug Y" replaced by the alias "Prescription".

[0051] Figure 5 An exemplary operational architecture for revealing sensitive information included in text according to levels of concealment that may be used in one or more scenarios of the present technology is illustrated. Figure 5 Illustrated is an operational scenario 500 relating to what occurs when a stack of digital content cards is shared between other users. The operational scenario 500 includes an application service 501, a user environment 508, a user interface 510, a user environment 509, and a user interface 511. The operational scenario 500 also includes digital content cards 520-521.

[0052] In operation, at time 1, application service 501 receives user input including text contained in digital content cards 520-521. In this example, digital content card 520 includes text indicating an order number, and digital content card 521 includes text indicating a credit card number. Application service 501 then checks the text in each of digital content cards 520-521 for sensitive information. In this example, application service 501 determines that digital content card 521 includes sensitive information (i.e., a credit card number). In response, application service 501 configures contextual privacy settings for the sensitive information in digital content card 521. Once the contextual privacy settings have been configured, application service 501 stores the contextual privacy settings in association with digital content card 521 including the sensitive information.

[0053] In the next operation, at time 2, the application service 501 identifies a digital content card 521 including text with sensitive information. In this example, the application service 501 may identify the digital content card 521 in response to receiving a request from the user in the user environment 508 to share the stack of digital content cards 520-521 with the user in the user environment 509. Next, the application service 501 identifies the contextual privacy settings for the sensitive information and the context surrounding the presentation of the digital content card 521. For example, the application service 501 may determine that the stack of digital content cards 520-521 is being shared with unauthorized users. Therefore, in response to identifying the contextual privacy settings for the sensitive information and the context surrounding the presentation of the digital content card 521, the application service 501 determines the hiding level for the sensitive information. In the final operation, at time 3, the application service 501 presents the digital content cards 520-521 to the user in the user environment 509. The sensitive information is revealed to the user according to the hiding level. In this example, digital content card 520 is fully revealed and flipped upside down when presented on user interface 511 in user environment 509 .

[0054] Figure 6 Illustrated are additional operational architectures for revealing sensitive information included in text according to a level of concealment that may be used in one or more scenarios of the present technology. Figure 6 An operational scenario 600 is illustrated relating to what happens when sensitive information is identified using machine learning techniques. The operational scenario 600 includes an application service 601, a user environment 608, a user interface 610, a data repository 607, and a machine learning engine 609. The operational scenario 600 also includes a spreadsheet 620, text 630, and sensitive information 640.

[0055] In a first operation, application service 601 receives user input including text 630 contained in spreadsheet 620. In this example, spreadsheet 620 includes text 630 indicating patient data. In a second operation, application service 601 checks text 630 in spreadsheet 620 for sensitive information 640. To check text 630, spreadsheet 620 is transferred to application service 601. Application service 601 then queries machine learning engine 609 to identify sensitive information 640. In response to receiving the query, machine learning engine 609 retrieves previously stored spreadsheets stored in data repository 607 that have been marked to indicate previously identified sensitive information.

[0056] In a fifth operation, the machine learning engine 609 processes a previously stored spreadsheet from the data repository 607 and determines that a social security number is included in the patient data based on the format of the numbers contained in the social security number. Thus, in a sixth operation, the application service 601 receives a flag indicating that the sensitive information 640 includes a social security number. In response, the application service 601 configures a contextual privacy setting for the sensitive information 640 in the spreadsheet 620. In a final operation, the application service 601 stores the contextual privacy setting in association with the spreadsheet 620 including the sensitive information 640.

[0057] Figure 7 The diagram shows Figure 6 The following alternative operating framework is used to reveal sensitive information included in text according to the level of concealment that can be used in one or more scenarios of the present technology. Figure 7 An operational scenario 700 is illustrated relating to what happens when a user synchronizes a version of a spreadsheet that includes user sensitivity with other devices. The operational scenario 700 includes an application service 701, a user environment 708, a user interface 710, a data repository 707, and additional devices 702-704. The operational scenario 700 also includes a spreadsheet 720, text 730, and sensitive information 740.

[0058] In a first operation, application service 701 identifies a spreadsheet 720 including text 730 having sensitive information 740. In this example, application service 701 may identify spreadsheet 720 in response to receiving a request from a user in user environment 708 to synchronize a latest version of spreadsheet 720 with user devices 702-704. In a second operation, application service 701 identifies contextual privacy settings for sensitive information 740 by querying data repository 707 and the context surrounding the presentation of spreadsheet 720. For example, application service 601 may determine that spreadsheet 720 is being synchronized with an unsecured device.

[0059] In response to identifying the contextual privacy setting for sensitive information and the context surrounding the presentation of the electronic form 720, the application service 701 determines a hiding level for the sensitive information 740. In a fourth operation, the application service 701 initiates synchronization of the user devices 702-704 with the latest version of the electronic form 720. In a final operation, when the text 730 contained in the electronic form 720 is presented to the user of the user device 704, the electronic form 720 is presented by obfuscating the sensitive information 740 (the social security number).

[0060] Figure 8 An exemplary operational architecture for revealing sensitive information included in text according to levels of concealment that may be used in one or more scenarios of the present technology is illustrated. Figure 8 An operational scenario 800 is illustrated relating to what happens when a corporate document including confidential information is opened using a security method. The operational scenario 800 includes a computing system 801, an application 803, a user interface 805, and a visual representation 810. The operational scenario 800 also includes a corporate document 820 including text 830 with sensitive information 840.

[0061] In operation, at time 1, application 803 receives user input including text 830 contained in company document 820. In this example, company document 820 includes text 830 indicating confidential company information 840. Then, application 803 checks text 830 to identify confidential company information 840. In this exemplary scenario, the company's management has assigned confidential company information 840 as sensitive. By searching all employee communications and document sharing for a product name, confidential company information 840 can be identified as any sensitive information. Then, all information associated with the product name will be configured with contextual privacy settings, which will be used to determine the level of hiding later. In response, application 803 configures contextual privacy settings for confidential company information 840 in company document 820. Once the contextual privacy settings have been configured, application 803 stores the contextual privacy settings in association with company document 820 including confidential company information 840.

[0062] In the next operation, at time 2, the application 803 identifies a corporate document 820 including text 830 with confidential corporate information 840. In this example, the application 803 may identify the corporate document 820 in response to receiving a request from the user to view the text 830 of the corporate document 820 on the user interface 805 of the mobile device. Next, the application 803 identifies the contextual privacy setting for the confidential corporate information 840 and the context surrounding the presentation of the corporate document 820. For example, the application 803 may determine to open the corporate document 820 using an authorized user fingerprint. Therefore, in response to identifying the contextual privacy setting for the confidential corporate information 840 and the context surrounding the presentation of the corporate document 820, the application 803 determines the hiding level for the confidential corporate information 840. In the final operation, the application 803 presents the corporate document 820 opened using the authorized fingerprint of the user on the screen of the mobile phone. In this scenario, since the hiding level is determined to be low in response to determining that an authorized user is accessing the corporate document 820, the confidential corporate information 840 is fully revealed along with the text 830.

[0063] Fig. 9A computing system 901 is illustrated, which represents any system or visual representation of a system in which the various applications, services, scenarios, and processes disclosed herein may be implemented. Examples of computing system 901 include, but are not limited to: server computers, rack servers, web servers, cloud computing platforms, data center equipment, and any other type of physical or virtual server machines, containers, and any variations or combinations thereof. Other examples may include: smartphones, laptops, tablet computers, desktop computers, hybrid computers, gaming consoles, virtual reality devices, smart televisions, smart watches and other wearable devices, and any variations or combinations thereof.

[0064] The computing system 901 may be implemented as a single device, system or apparatus, or may be implemented as multiple devices, systems or apparatuses in a distributed manner. The computing system 901 includes, but is not limited to, a processing system 902, a storage system 903, software 905, a communication interface system 907, and a user interface system 909. The processing system 902 is operatively coupled with the storage system 903, the communication interface system 907, and the user interface system 909.

[0065] Processing system 902 loads and executes software 905 from storage system 903. Software 905 includes process 906, which represents the above Figure 1-8 The processes discussed include the secure presentation process 200. When executed by the processing system 902 to enhance the application, the software 905 directs the processing system 902 to operate as described herein for the various processes, operating scenarios, and sequences discussed in at least the foregoing implementations. The computing system 901 may optionally include additional devices, features, or functions that are not discussed for the sake of brevity.

[0066] Still reference Fig. 9 , the processing system 902 may include a microprocessor and other circuits that retrieve and execute software 905 from a storage system 903. The processing system 902 may be implemented within a single processing device, but may also be distributed across multiple processing devices or subsystems that collaborate to execute program instructions. Examples of the processing system 902 include general-purpose central processing units, graphics processing units, special-purpose processors and logic devices, and any other type of processing device, combination, or variation.

[0067] The storage system 903 may include any computer-readable storage medium that is readable by the processing system 902 and capable of storing the software 905. The storage system 903 may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Examples of storage media include: random access memory, read-only memory, disk, optical disk, flash memory, virtual memory and non-virtual memory, cassettes, tapes, disk storage or other magnetic storage devices, or other suitable storage media, in addition to propagating signals. The storage system 903 can be implemented as a single storage device, but it can also be implemented across multiple storage devices or subsystems that are co-located or distributed relative to each other. The storage system 903 may include additional elements that can communicate with the processing system 902 or possible other systems, such as a controller.

[0068] The software 905 may be implemented in program instructions and, among other functions, when executed by the processing system 902, may direct the processing system 902 to operate as described with respect to the various operational scenarios, sequences, and processes illustrated herein. The software 905 may include program instructions for implementing the presentation process 200.

[0069] In particular, the program instructions may include various components or modules that cooperate or otherwise interact to perform various processes and operation scenarios described herein. Various components or modules may be embodied in the instructions compiled or interpreted, or may be embodied in some other variations or combinations of instructions. Various components or modules may be executed serially or in parallel in a single-threaded environment or multithreaded in a synchronous or asynchronous manner, or may be executed according to any other suitable execution paradigm, variation or combination thereof. In addition to process 906 or including process 906, software 905 may also include additional processes, programs or components, such as operating system software, virtual machine software or other application software. Software 905 may also include firmware or some other forms of machine-readable processing instructions that can be executed by processing system 902.

[0070] Typically, when software 905 is loaded into processing system 902 and executed, a suitable device, system or equipment (represented by computing system 901) can be converted as a whole from a general computing system to a special computing system to enhance application services so as to reveal sensitive information contained in the text according to the hidden level. In fact, the encoding software 905 on storage system 903 can convert the physical structure of storage system 903. The specific conversion of physical structure can depend on various factors in different implementations of this description. Such factors may include, but are not limited to: the technology of the storage medium for implementing storage system 903, and whether the computer storage medium is characterized as primary storage or auxiliary storage, and other factors.

[0071] If the computer-readable storage medium is implemented as a semiconductor-based memory, then when program instructions are encoded therein, the software 905 can transform the physical state of the semiconductor memory, such as by transforming the state of transistors, capacitors, or other discrete circuit elements that make up the semiconductor memory. Similar changes may occur with respect to magnetic or optical media. Other transformations of the physical medium are possible without departing from the scope of this specification, and the foregoing examples are provided only to facilitate the present invention.

[0072] The communication interface system 907 may include communication connections and devices that allow communication with other computing systems (not shown) through a communication network (not shown). Examples of connections and devices that together allow inter-system communication may include: network interface cards, antennas, power amplifiers, RF circuits, transceivers, and other communication circuits. The connections and devices may communicate over a communication medium to exchange communications with other computing systems or systems networks, such as metal, glass, air, or any other suitable communication medium. The aforementioned media, connections, and devices are well known and need not be discussed in detail herein.

[0073] The user interface system 909 may include: a keyboard, a mouse, a voice input device, a touch input device for receiving touch gestures from a user, a motion input device for detecting non-touch gestures and other movements of a user, and other similar input devices and associated processing elements capable of receiving user input from a user. Output devices such as displays, speakers, tactile devices, and other types of output devices may also be included in the user interface system 909. In some cases, input devices and output devices may be combined in a single device, such as a display capable of displaying images and receiving touch gestures. The aforementioned user input and output devices are well known in the art and do not need to be discussed in detail here. The user interface system 909 may also include associated user interface software, which can be executed by the processing system 902 to support the various user input and output devices discussed above.

[0074] The communication between the computing system 901 and other computing systems (not shown) can occur over one or more communication networks and according to various communication protocols, combinations of protocols, or variations thereof. Examples include an intranet, the Internet, a local area network, a wide area network, a wireless network, a wired network, a virtual network, a software-defined network, a data center bus, a computing backplane, or any other type of network, combination of networks, or variations thereof. The communication networks and protocols mentioned above are well known and need not be discussed in detail here.

[0075] In any of the above examples of exchanging data, content, or any other type of information, the exchange of information can occur according to any of a variety of protocols, including: FTP (File Transfer Protocol), HTTP (Hypertext Transfer Protocol), HTTPS, REST (Representational State Transfer), WebSocket, DOM (Document Object Model), HTML (Hypertext Markup Language), CSS (Cascading Style Sheets), HTML5, XML (Extensible Markup Language), JavaScript, JSON (JavaScript Object Notation) and AJAX (Asynchronous JavaScript and XML), as well as any other suitable protocols, variations, or combinations thereof.

[0076] From the foregoing disclosure, certain inventive aspects can be understood, and the following are various examples.

[0077] The functional block diagrams, operation scenarios and sequences and flow charts provided in the accompanying drawings represent exemplary systems, environments and methods for executing the novel aspects of the present disclosure. Although for the purpose of simplifying the description, the methods included in this article can be in the form of functional diagrams, operation scenarios or sequences or flow charts, and can be described as a series of actions, it should be understood and appreciated that these methods are not limited by the order of actions, because some actions can occur and / or occur simultaneously with other actions in an order different from the actions shown and described in this article. Those skilled in the art will understand and appreciate that the method can be represented as a series of interrelated states or events instead, such as in a state diagram. In addition, for novel implementations, all actions illustrated in the method may not be required.

[0078] Example 1. A computing device comprising: one or more computer-readable storage media; one or more processors operably coupled to the one or more computer-readable storage media; and program instructions stored on the one or more computer-readable storage media, the program instructions, when read and executed by the one or more processors, directing the one or more processors to at least: identify an object including text having sensitive information; identify contextual privacy settings for the sensitive information; identify a context surrounding the presentation of the object; determine a hiding level for the sensitive information in the text based on the contextual privacy settings and the context surrounding the presentation of the object; and present the object including the text, wherein the sensitive information included in the text is revealed according to the hiding level.

[0079] Example 2. A computing device of Example 1, wherein the program instructions are further configured to: receive user input including the text; check the text for the sensitive information; configure the contextual privacy setting for the sensitive information; and store the contextual privacy setting in association with the object including the text having the sensitive information.

[0080] Example 3. A computing device of Examples 1-2, wherein, in order to check the text for the sensitive information, the program instructions direct the one or more processors to: identify one or more portions of the text based on at least one of keywords, symbols, user instructions, or formatting styles associated with the sensitive information.

[0081] Example 4. A computing device of Examples 1-3, wherein, in order to check the text for the sensitive information, the program instructions direct the one or more processors to: track indicators associated with the sensitive information in a cloud-based data repository to be ingested by the machine learning system to identify the sensitive information.

[0082] Example 5. The computing device of Examples 1-4, wherein, to identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to share the object with at least one additional user device.

[0083] Example 6. The computing device of Examples 1-5, wherein, to identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to audibly present the object to the user.

[0084] Example 7. The computing device of Examples 1-6, wherein, to identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to access the object over a public network.

[0085] Example 8. A computing device of Examples 1-7, wherein, in order to identify the context of presentation surrounding the object, the program instructions direct the one or more processors to: determine a request to access the object using at least one of a user-configured fingerprint, voice recognition, or facial recognition.

[0086] Example 9. A computing device of Examples 1-8, wherein, in order to present the sensitive information to the user in the user interface according to the hiding level, the program instructions direct the one or more processors to perform at least one of the following: blurring the sensitive information, rearranging characters contained in the sensitive information, obfuscating the sensitive information, using an alias representing the sensitive information, reversing a digital content card including the sensitive information, or omitting the sensitive information according to the hiding level.

[0087] Example 10. A method comprising: identifying an object including text having sensitive information; identifying a contextual privacy setting for the sensitive information; identifying a context surrounding the presentation of the object; determining a concealment level for the sensitive information in the text based on the contextual privacy setting and the context surrounding the presentation of the object; and presenting the object including the text, wherein the sensitive information included in the text is revealed according to the concealment level.

[0088] The method of Example 11 and Example 10 also includes: receiving user input including the text; checking the text for the sensitive information; configuring the contextual privacy setting for the sensitive information; and storing the contextual privacy setting in association with the object including the text having the sensitive information.

[0089] Example 12, the method of Examples 10-11, wherein checking the text for the sensitive information includes: identifying one or more portions of the text based on at least one of keywords, symbols, user instructions, or formatting styles associated with the sensitive information.

[0090] Example 13. The method of Examples 10-12, wherein checking the text for the sensitive information includes tracking indicators associated with the sensitive information in a cloud-based data repository to be ingested by a machine learning system to identify the sensitive information.

[0091] Example 14. The method of Examples 10-13, wherein identifying the context surrounding the presentation of the object comprises identifying a request to share the object with at least one additional user device.

[0092] Example 15. The method of Examples 10-14, wherein identifying the context surrounding the presentation of the object comprises: identifying a request to audibly present the object to the user.

[0093] Example 16. The method of Examples 10-15, wherein identifying the context surrounding the presentation of the object comprises identifying a request to access the object over a public network.

[0094] Example 17, the method of Examples 10-16, wherein, in order to identify the context of presentation surrounding the object, the program instructions direct the one or more processors to: determine a request to access the object using at least one of a user-configured fingerprint, voice recognition, or facial recognition.

[0095] Example 18, the method of Examples 10-17, wherein the sensitive information included in the text is revealed according to the hidden level by at least one of: blurring the sensitive information, rearranging characters contained in the sensitive information, obfuscating the sensitive information, using an alias representing the sensitive information, reversing a digital content card including the sensitive information, or omitting the sensitive information according to the hidden level.

[0096] Example 19. A computing device comprising: one or more computer-readable storage media; one or more processors operably coupled to the one or more computer-readable storage media; and program instructions stored on the one or more computer-readable storage media, which, when read and executed by the one or more processors, direct the one or more processors to at least: receive user input comprising text; check the text for sensitive information; configure contextual privacy settings for the sensitive information; and store the contextual privacy settings in association with an object comprising the text having the sensitive information.

[0097] Example 20. A computing device of Example 20, wherein the program instructions are further configured to: identify the object including the text having the sensitive information; identify the contextual privacy setting for the sensitive information; identify the context surrounding the presentation of the object; determine a hiding level for the sensitive information in the text based on the contextual privacy setting and the context surrounding the presentation of the object; and present an object including the text, wherein the sensitive information included in the text is revealed according to the hiding level.

Claims

1. A computing device, comprising: one or more computer-readable storage media; one or more processors operatively coupled to the one or more computer-readable storage media; as well as Program instructions stored on the one or more computer-readable storage media, which, when read and executed by the one or more processors, direct the one or more processors to at least: Identify objects that include text containing sensitive information; identifying a contextual privacy setting for the sensitive information; determining, based on environmental factors including a network type and a number of persons present near the object, whether a context surrounding the presentation of the object includes at least one of: a secure environment, an unsecure environment, and a semi-secure environment; determining a level of concealment for the sensitive information in the text based on the contextual privacy setting and the context surrounding the presentation of the object; as well as presenting the object including the text, wherein the sensitive information included in the text is revealed according to the hiding level, wherein the contextual privacy setting is different for different surrounding contexts, and The hiding level is different between at least two surrounding contexts among the different surrounding contexts.

2. The computing device according to claim 1, wherein: The program instructions are also configured to: receiving user input including the text; checking the text for the sensitive information; configuring the contextual privacy setting for the sensitive information; and The contextual privacy setting is stored in association with the object including the text having the sensitive information.

3. The computing device according to any one of claims 1 to 2, wherein: In order to check the text for the sensitive information, the program instructions direct the one or more processors to: identify one or more portions of the text based on at least one of keywords, symbols, user instructions, or formatting styles associated with the sensitive information, and wherein the environmental factors also include presentation mode and authentication type.

4. The computing device according to any one of claims 1 to 2, wherein: To check the text for the sensitive information, the program instructions direct the one or more processors to: track indicators associated with the sensitive information in a cloud-based data repository to be ingested by a machine learning system to identify the sensitive information.

5. The computing device according to any one of claims 1 to 2, wherein: To identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to share the object with at least one additional user device.

6. The computing device according to any one of claims 1 to 2, wherein: To identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to audibly present the object.

7. The computing device according to any one of claims 1 to 2, wherein: To identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to: identify a request to access the object over a public network.

8. The computing device according to any one of claims 1 to 2, wherein: To identify the context surrounding the presentation of the object, the program instructions direct the one or more processors to determine a request to access the object using at least one of a user-configured fingerprint, voice recognition, or facial recognition.

9. The computing device according to any one of claims 1 to 2, wherein: In order to present the object including the text, the program instructions direct the one or more processors to at least: blur the sensitive information, rearrange characters contained in the sensitive information, obfuscate the sensitive information, use an alias representing the sensitive information, reverse a digital content card including the sensitive information, or omit the sensitive information based on the hiding level.

10. A method for presenting sensitive information, comprising: Identify objects that include text containing sensitive information; identifying a contextual privacy setting for the sensitive information; determining, based on environmental factors including a network type and a number of persons present near the object, whether a context surrounding the presentation of the object includes at least one of: a secure environment, an unsecure environment, and a semi-secure environment; determining a level of concealment for the sensitive information in the text based on the contextual privacy setting and the context surrounding the presentation of the object; as well as presenting the object including the text, wherein the sensitive information included in the text is revealed according to the hiding level, wherein the contextual privacy setting is different for different surrounding contexts, and The hiding level is different between at least two surrounding contexts among the different surrounding contexts.

11. The method according to claim 10, further comprising: receiving user input including the text; checking the text for the sensitive information; configuring the contextual privacy setting for the sensitive information; as well as The contextual privacy setting is stored in association with the object including the text having the sensitive information.

12. The method according to claim 11, wherein: Checking the text for the sensitive information includes identifying one or more portions of the text based on at least one of keywords, symbols, user instructions, or formatting patterns associated with the sensitive information, and wherein the environmental factors also include presentation mode and authentication type.

13. The method according to any one of claims 11 to 12, wherein: Checking the text for the sensitive information includes tracking indicators associated with the sensitive information in a cloud-based data repository to be ingested by a machine learning system to identify the sensitive information.

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