FIG. 3 is a block diagram of an environment 300 in which a system 350 for automatically censoring sensitive data on a computing device 304 is used in accordance with embodiments of the present disclosure. The environment 300 includes a computing device 304 including the system 350, a user 308 of computing device 304 and an unauthorized person 312 (e.g., “a shoulder surfer”) that may engage in unauthorize viewing of the computing device 304. As illustrated in FIG. 3, the computing device 304 includes input/output systems such as a camera 316 and a screen or display 334 that displays information 338. The computing device 304 further includes the system 350 including a sensitive data protection module 354. The sensitive data protection module 354 includes an image acquisition and comparison unit 358, a notification unit 382, an event detector 386, a censoring unit 390 and user security parameters 374. In a specific embodiment of the present disclosure, the sensitive data protection module 354 may be implemented in a mobile application program or application. The application program may be available for download on a mobile application marketplace or distribution platform. The sensitive data protection module 354 can execute as a background service or application to help protect the information 338 being displayed on the screen 334 by another application program.

The front surface of the computing device 304 includes the screen 334 and the camera 316 (e.g., a front-facing camera). The information 338 is displayed on the screen 334 so that the user 308 can view the information 338. In many cases, the user 308 may be using the computing device 304 in public. For example, the user 308 may be holding and using the computing device 304 while on a bus, a train, an airplane, or while waiting in line to make a purchase. The user 308 may have set the computing device 304 on a table such as on a table in a coffee shop or restaurant. Public spaces can often be crowded with other people including strangers. Because the computing device 304 may be used in close proximity to strangers, it can be very easy for a stranger (e.g., a shoulder surfer 312) to look at the information 338 being shown on the user's computing device 304.

According to one embodiment of the present disclosure, the images captured by the camera 316 (e.g., images that monitor the environment in proximity to the screen 334) are not displayed on the screen 334 of the computing device 304. According to an alternative embodiment of the present disclosure, the images captured by the camera 316 may be displayed within a small window on the screen 334 along with the information 338.

The image acquisition and comparison unit 358 includes stored images 362, reference images 366, target images 370, a facial recognition unit 392 and an image comparison engine 378. The image acquisition and comparison unit 358 is responsible for obtaining the reference images 366 and the target images 370 from the camera 316 when comparing the reference images 366 to the target images 370 when the user 308 starts operating the computing device 304 at a location. According to one embodiment of the present disclosure, the user 308 prior to beginning work, holds the computing device 304 while the camera 316 captures reference images 366 of the environment in proximity to the screen 334. Because the camera 316 is a front-facing camera, the reference images 366 typically will include a representation of the user 308 in the foreground of the reference images 366 and other objects within a field of view of the camera 316. These other objects will be in the background of the reference images 366. The objects will include things behind or indirectly behind the user 308. The other objects making up the background of the reference images 366 depend on the area or environment in which the user 308 is using the computing device 304. For example, if the user 308 is in a hotel lobby, the background objects may include lounge furniture, tables, wall art, people, luggage, plants, and so forth.

After the user 308 begins work on the computing device 304, the target image 370 is acquired. As discussed above, because the camera 316 is a front-facing camera, the target image 370 typically will include another representation of the user 308 in a foreground of the target image 370, and other objects in a background of the target image 370. The image comparison engine 378 compares the background of the target image 370 with the background of the reference image 366 to detect any changes. For example, the background of the target image 370 may include a person (e.g., stranger or shoulder surfer) who was not present in the reference image 366. The image comparison engine 378 can identify the background change.

Alternatively, the image acquisition and comparison unit 358 may use stored images 362 and the image comparison engine 378 compares the stored image 362 to the target image 370. The stored images 370 include images of people and/or background images. Images of people may include images of work colleagues, supervisors, and/or clients of the user. Moreover, images of people may include images of the user's partner, children, relatives or friends. Background images may include, for example, background settings for the user's office, office conference rooms, home offices, rooms in the user's house, semi-private locations, etc. For example, a stored image of the background of the user's office can be generated and compared with a target image (e.g., after the user 308 begins work on the computing device 304) of the background of the user's office to determine differences in the images. The differences in the images may be associated with a time frame or a distance, for example. According to an embodiment of the present disclosure, the image comparison unit 378 may determine a period of time that the differences between the images exists. Moreover, the image comparison unit 378 may determine a difference in distances of objects between the images.

According to a further embodiment of the present disclosure, the camera 316, may be positioned such that only the background is captured and there is no image of the user 308 in the foreground.

When recognizing individuals in the background, the facial recognition unit 392 compares stored images 362 of individuals or reference images 366 of individuals with the target images 370 of individuals for facial recognition. According to one embodiment of the present disclosure, facial recognition can be performed locally on the computing device 304 or remotely using the one or more server(s) 112 and the one or more database(s) 108 as illustrated in FIG. 1. Because of vast number of resources, performing facial recognition at the one or more server(s) 112 and the one or more database(s) 108 can provide for more accurate results as compared to facial recognition at the computing device 304.

Whether a facial database is stored at the computer device 304, the one or more server(s) 112 and the one or more database(s) 108, or both can depend on factors such as computing resources available on the computing device 304, desired accuracy, application of the system, and others. According to an embodiment of the present disclosure, one or more of the components of the sensitive data protection module 354 reside on the computing device 304. In another embodiment of the present disclosure, one or more components of the sensitive data protection module 354 are distributed between the computing device 304 and the one or more server(s) 112 and the one or more database(s) 108.

The facial recognition unit 392 may incorporate a facial recognition algorithm that identifies facial features by extracting landmarks, or features, from an image of the subject's face. For example, an algorithm may analyze the relative position, size, and/or shape of the eyes, nose, cheekbones, and jaw. These features can then be used to search for other previously stored images with matching features. For example, facial recognition unit 392 may compare stored images 362 and/or reference images 366 of the user's work colleagues, supervisors, clients, partner, children, relatives and/or friends with target images 370 of these individuals.

The facial recognition unit 392 may include a geometric recognition algorithm. This algorithm looks at distinguishing features. Instead or additionally, a photometric recognition algorithm may be used. The algorithm provides a statistical approach that distills an image into values and compares the values with templates to eliminate variances. Other examples of recognition algorithms that may instead or additionally be used include principal component analysis using eigenfaces, linear discriminate analysis, elastic bunch graph matching using the Fisherface algorithm, the Hidden Markov model, and the neuronal motivated dynamic link matching.

Another example of a facial recognition technique that may be used includes three-dimensional face recognition. This technique uses 3D sensors to capture information about the shape of a face. This information is then used to identify distinctive features on the surface of a face, such as the contour of the eye sockets, nose, and chin. One advantage of 3D facial recognition is that it is not affected by changes in lighting like other techniques. It can also identify a face from a range of viewing angles, including a profile view. Three-dimensional data points from a face improve the precision of facial recognition.

Another example of a facial recognition technique that may be used includes skin texture analysis. This technique uses the visual details of the skin to turn the unique lines, patterns, and spots apparent in a person's skin into a mathematical space. The facial recognition unit 392 may include a single recognition technique or a combination of recognition techniques. For example, skin texture analysis may be used in combination with other recognition techniques to provide accurate recognition.

According to an embodiment of the present disclosure, the facial recognition unit 392 may determine a period of time that one or more recognized or unrecognized images of individuals appear in the image of the environment of the computing device 304. Moreover, the facial recognition unit 392 may determine a distance to the user 308 of one or more recognized or unrecognized images of individuals that appear in the image of the environment of the computing device 304.

The user security parameters 374 include preselected information by the user 308 identifying sensitive data from the information 338 that is to be displayed on the screen 334 of the computing device 304. User security parameters 374 may include, for example, identified location parameters (e.g., home, office, private, public, semi-private, semi-public etc.), personal information parameters (e.g., name, telephone number, personal email address, date of birth, social security number, banking details, height, weight, place of birth, home address, work address, marital status, verification information, one time passwords, pin numbers, etc.), work information parameters (e.g., security codes, salary, business email address, project information, software details, updates to software or project information, PDF views, programming applications, chat applications, Word documents, etc.). As an example, the identified location parameter is used to determine what information is to be displayed or censored based on the location determined by the image comparison engine 378. Therefore, if it is determined that the user is located in the user's office and an individual is not recognized in the background by the facial recognition unit 392, then personal information such as work address may not be censored as compared to the work address being censored when it is determined the user is located in a public place and an individual is not recognized in the background by the facial recognition unit 392. Other examples may include not censoring a telephone number, marital status, home address or place of birth, if the image comparison engine 378 determines that the user is at home and a family member is not recognized in the background by the facial recognition unit 392, censoring a PDF view, project information or software details, when it is determined the user is located in a semi-public place (e.g., office cafeteria) and an individual is not recognized in the background by the facial recognition unit 392, etc.

The event detector 386 determines if a particular event has taken place. According to one embodiment of the present disclosure, an event could be a change in background, unrecognition (e.g., via facial recognition) individual in the background, etc. A detected threshold event would be a change in background within a predetermined period of time. For example, if the background change is within a predetermined period of time, the threshold event is detected and if the background change is not within the predetermined period of time, then the threshold event is not detected. As another example, a threshold event is detected if an individual is not recognized within a predetermined period of time or within a predetermined distance to the user and the threshold event is not detected if an individual is not recognized outside of the predetermined period of time or not within the predetermined distance to the user.

The censoring unit 390 censors sensitive data based on a detected event or a detected threshold event and the user security parameters as discussed above. The censoring unit 390 censors the sensitive data by masking a field such as a field label, an input field, or both. According to embodiments of the present disclosure, the system 350 permits or displays values input by a user 308 into an input field, determines an event has taken place such that backgrounds of the stored image 362 or reference image 366 and the target image 370 have changed, an individual is not recognized by the facial recognition unit 392 in the background or determines a detected threshold event has taken place within a predetermined time or a predetermined location or both and after determining that the detected event has taken place or the detected threshold event has taken place and based on the user security parameters, mask the input values (e.g., replacing the displayed input values with asterisks or other marks).

The alteration to the input values may also include reducing the visibility of information displayed on the screen. Moreover, a graphical region may be generated that overlays, (e.g., is superimposed over, or covers) all or at least a portion of the information shown on the screen. For example, the information shown on the screen may include sensitive data (e.g., social security number) and non-sensitive information (e.g., the name of a country). The system 305 can position the graphical region over the sensitive data, but leave the non-sensitive data exposed or not covered. This allows the user to continue viewing the non-sensitive data but protects the sensitive data from the prying eyes of a potential shoulder surfer.

According to another embodiment of the present disclosure, the change in background, the unrecognized individuals, for a prescribed distance or length of time may also trigger an alert from the notification unit 382. The notification unit 382 is responsible for alerting the user 308 for detected events and detected threshold events. The alert can include displaying a message on the screen 334 to inform the user 308 of the background change, and/or unrecognized individuals, for a prescribed distance or length of time, capturing an image of the change and displaying the image of the change on the screen, or both. For example, the image of the change can include a picture of the individual present in the target image, but not present in the reference image or the stored image. Alternatively, the image can include the unrecognized individual, the unrecognized individual after a predetermined period of time or the unrecognized individual after the unrecognized individual is within a predetermined distance of the user 308.

The notification unit provides a list of the various types of alerts that may be generated. In an embodiment of the present disclosure, alerting the user includes altering the graphical user interface that is displayed on the screen. In another embodiment of the present disclosure, the system 305 can reposition information 338 displayed on the screen 334. In this embodiment of the present disclosure, upon determining that the detected event or the threshold detected event the sensitive data may be moved from a first location (or original location) on the screen 338 to a second location (or new location) on the screen 338, different from the first location. The second location can be a location where it will be more difficult than the first location for the shoulder surfer 312 to watch the screen 338 than the first location. The second location can be a location where it is easier than the first location for the user to cover the screen 338.

The first location may be a center of the screen 338, and the second location may be a corner of the screen 338, a bottom of the screen 338, a top of the screen 338, or combinations of these (e.g., a bottom corner of the screen 338 or top corner of the screen). The first location may be a side of the screen 338 (e.g., left-hand side) and the second location may be a different side of the screen 338 (e.g., right-hand side).

In another embodiment of the present disclosure, the system 350 can capture an image of the detected event or the detected threshold event (e.g., shoulder surfer 312 appearing in background). The captured image can then be displayed on the screen 334.

In another embodiment of the present disclosure, the system 350 may display a notification message on the screen 334. The notification message may include text to indicate to the shoulder surfer 312 that the user 308 is aware of the spying. It should be appreciated that the system 250 can implement a combination of operations or actions to help keep the user's information private (e.g., capture image of shoulder surfer and display notification).

In another embodiment of the present disclosure, the system 305 may provide a silent or coded alert. Such an alert can inform the user 308 that there is a potential shoulder surfer 312 watching the screen, but not alert the shoulder surfer 312 that the user 308 is aware of their presence. For example, the system 305 may cause the computing device 304 to vibrate, generate an audio alert, display an alert code, or combinations of the above-identified alerts. For example, the combination of masking a field and generating an audio alert provides better protection.

The type of alert provided by the system can be user-configurable. For example, one user may select an alert type that captures an image of the background change (e.g., shoulder surfer 312 appearing in background) and displays the image on the screen 334 for both the user 308 and shoulder surfer 312 to see. Alternatively, another user 308 may select an alert type that provides a silent alert. It should be appreciated that an alert may be a visual alert (e.g., display message, flicker screen, darken screen, blank out screen, or apply graphical overlay), audio alert (e.g., beeping, or siren), or both.

As discussed above, the alerts are provided along with the censoring the sensitive information and based on the user security parameters.

FIG. 4A illustrates the provision of a user identification and authorization dialog in accordance with embodiments of the present disclosure. As illustrated in FIG. 4A, a username 404 and a password 408 are required to access the system 350. After “Joe User” 412 is provided as the username 404, the user 308 is required to provide the corresponding password 408 for authentication to the system 350. Proper authentication will allow the user to access the user security parameters for example.

FIG. 4B illustrates a list of user security parameters 420 used for automatically censoring sensitive data in accordance with embodiments of the present disclosure. As discussed above, the user security parameters 420 include preselected information by the user 308 identifying sensitive data from the information 338 that is to be displayed on the screen 334 of the computing device 304. User security parameters 420 may include, for example, identified location parameters 430 (e.g., home, office, private, public, semi-private, semi-public etc.), personal information parameters 440 (e.g., name, telephone number, personal email address, date of birth, social security number, banking details, height, weight, place of birth, home address, work address, marital status, verification information, one time passwords, pin numbers, etc.) and work information parameters 450 (e.g., security codes, salary, business email address, project information, software details, updates to software or project information, PDF views, programming applications, chat applications, Word documents, etc.).

FIGS. 5A-5H are diagrams of example embodiments of graphical user interface (GUI) s used for preventing unwanted viewing of sensitive data by unauthorized persons in accordance with embodiments of the present disclosure. GUI elements described herein can be or may include any type of user interface element that can be displayed/sounded by a browser such as a button, a window, a pane, panel, a menu, a menu item, an icon, a tab, a text object, a text entry object, a scroll bar, a slider, a cursor, a picture, a video, a sound object, a vibration object, and/or the like.

When a user accesses a webpage using the browser, webpage code may be uploaded from a webserver or other network location. For example, when the user enters a Uniform Resource Locator (URL) in the browser, code from the webpage associated with the URL may be uploaded to the browser.

As illustrated in FIG. 5A, a webpage may include a GUI 500 displayed on one or more computing device(s) 104. The GUI 500 may include an outer window 504 containing a number of GUI elements. The outer window 504 may include a browser window 508 displaying information 338. The GUI 500 may include a series of GUI buttons such as a file button 512, a settings button 516, a home button 520, and/or a help button 524. The GUI 500 may also include a navigation bar 526 enabling users to select a URL to visit in the browser window 508.

The browser window 508 may be configured to display the contents of a webpage accessed from a network location. The navigation bar 526 may be used to enable users to select a URL to visit in the browser window 508. Entering a URL and submitting or clicking an enter or go button may begin a downloading of contents from the URL into the browser window 508.

The outer window 504 may include a series of user interface buttons 512, 516, 520, 524 enabling users to interact with the webpage. For example, the file button 512 may present a dropdown menu providing a number of options such as exit, new window, etc. The settings button 516 may present a pop-up or modal window listing a series of options for user-customizable settings. The home button 520 may direct the user to the homepage of the webpage. The help button 524 provides assistance or help to the user. The information 338 may be personal information which includes, for example, input fields and data, as follows: First Name “John”, Middle Initial “J.”, Last Name “Smith”, Address “150 Main Street”, Apt/Suite “123”, City “Anytown”, State/Providence “U.S.A.”, Postal Code “12345-6789”, Phone “(202) 555-1212”, email “John.J.Smith@gmail.com”, Social Security Number (SSN) “555-42-4231”, Date of Birth (DOB) “Jan. 1, 1959”, Bank Account Number “12345-12345” and “Routing Number “0440782324”.

As illustrated in FIG. 5B, a GUI 530 may display personal information 338 with various input fields and data censored or masked. As illustrated, the Address “150 Main Street”, Apt/Suite “123”, Social Security Number (SSN) “555-42-4231”, Date of Birth (DOB) “Jan. 1, 1959”, Bank Account Number “12345-12345” and “Routing Number “0440782324” input fields and data are censored by blocking out this information. The other input fields and data remain uncensored since this information has been predetermined by the user as not being sensitive based on the user security parameters.

According to embodiments of the present disclosure, the information may be censored based on user security parameters and detected events or detected threshold events. For example, if the user is in a public location and the user security parameter indicates a public location, when a detected event occurs (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device) or when a detected threshold event occurs (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a predetermined period of time or at a predetermined distance to the user), these input fields and data a censored based on the user security parameters preselected by the user.

As illustrated in FIG. 5C, a GUI 540 may display the personal information 338 with various input fields and data censored or masked. As illustrated, the Address “150 Main Street”, Apt/Suite “123”, Social Security Number (SSN) “555-42-4231”, Date of Birth (DOB) “Jan. 1, 1959”, Bank Account Number “12345-12345” and “Routing Number “0440782324” input fields and data are further censored by being further reduced in visibility. According to embodiments of the present disclosure, the further censoring may be based on a threshold detected event. For example, if a first threshold for a threshold event is reached (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a first predetermined period of time or at a first predetermined distance to the user) the censoring is at a first reduced visibility and if a second threshold for a threshold event is reached (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a second predetermined period of time which is greater than the first predetermined period of time or at a second predetermined distance to the user which is less than the first predetermined distance) the censoring is at a second reduced visibility greater than the first reduced visibility.

As illustrated in FIG. 5D, a GUI 550 may display the personal information 338 with various input fields and data censored or blocked out. As illustrated, the Address “150 Main Street”, Apt/Suite “123”, Social Security Number (SSN) “555-42-4231”, Date of Birth (DOB) “Jan. 1, 1959”, Bank Account Number “12345-12345” and “Routing Number “0440782324” input fields and data are further censored by completely blocking out this information. According to embodiments of the present disclosure, further blocking may be based on a final threshold event being detected. For example, if the final threshold event is detected (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device at the greatest predetermined period of time or at the least predetermined distance to the user), these input fields and data a censored based on the user security parameters preselected by the user.

As illustrated in FIG. 5E, a GUI 560 may display work information 338 with various input fields and data as follows: Disclosure Number “D24-0007”, status date “15 Dec. 2022”, Disclosure Status “Draft”, Disclosure Date “20 May 2023”, Disclosure Title “Making Sensitive Data on Detecting Presence of Non-Authorized User”, Inventor “Pragati Dhumal” and “Inventor “Tanvi Sharma”.

As illustrated in FIG. 5F, a GUI 570 may display work information 338 with various input fields and data censored or masked. As illustrated, the Disclosure Title “Making Sensitive Data on Detecting Presence of Non-Authorized User”, Inventor “Pragati Dhumal” and “Inventor “Tanvi Sharma” input fields and data are censored by masking this information. The other input fields and data remain uncensored since this information has been predetermined by the user as not being sensitive based on the user security parameters.

According to embodiments of the present disclosure, the information may be censored based on user security parameters and detected events or detected threshold events. For example, if the user is in a semi-private location such as an office cafeteria and the user security parameter indicates a semi-private location such as an office cafeteria, when a detected event occurs (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device) or when a detected threshold event occurs (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a predetermined period of time or at a predetermined distance to the user), these input fields and data a censored based on the user security parameters preselected by the user.

As illustrated in FIG. 5G, a GUI 580 may display work information 338 with various input fields and data censored or masked. As illustrated, the Disclosure Title “Making Sensitive Data on Detecting Presence of Non-Authorized User”, Inventor “Pragati Dhumal” and “Inventor “Tanvi Sharma” input fields and data are further censored by being further reduced in visibility. According to embodiments of the present disclosure, the further censoring may be based on a threshold detected event. For example, if a first threshold for a threshold event is reached (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a first predetermined period of time or at a first predetermined distance to the user) the blocking is at a first resolution and if a second threshold for threshold event is reached (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device for a second predetermined period of time which is greater than the first predetermined period of time or at a second predetermined distance to the user which is less than the first predetermined distance) the blocking is at a second resolution greater than the first resolution.

As illustrated in FIG. 5H, a GUI 590 may display work information 338 with various input fields and data censored or blocked out. As illustrated, the Disclosure Title “Making Sensitive Data on Detecting Presence of Non-Authorized User”, Inventor “Pragati Dhumal” and “Inventor “Tanvi Sharma” input fields and data are further censored by blocking out this information by completely blocking out this information. According to embodiments of the present disclosure, further blocking may be based on a final threshold event being detected. For example, if the final threshold event is detected (e.g., an unrecognized individual is in the background image of an environment in proximity to the display of the computing device at the greatest predetermined period of time or at the least predetermined distance to the user), these input fields and data a censored based on the user security parameters preselected by the user.

FIG. 6A-6C depict the identification of an unauthorized person in automatically censoring sensitive data in accordance with embodiments of the present disclosure. As illustrated in FIG. 6A an image 600 depicts a user 308 and an unauthorized person 312 in the environment in proximity to the display of the computing device. As illustrated in FIG. 6B an image 620 depicts the user 308 and the unauthorized person 312 in the environment in proximity to the display of the computing device at a closer distance to the user. As illustrated in FIG. 6C, a GUI 630 may display work information 338 with various input fields and data censored or masked. As illustrated, the Disclosure Title “Making Sensitive Data on Detecting Presence of Non-Authorized User”, Inventor “Pragati Dhumal” and “Inventor “Tanvi Sharma” input fields and data are further censored by completely blocking out this information. The image 620 which depicts the user 308 and the unauthorized person 312 in the environment in proximity to the display of the computing device at a closer distance to the user is also provided to the user. The image 620 serves as a notification or an alert to the user.

FIG. 7 represents a flow diagram depicting method 700 for updating user security parameters in accordance with embodiments of the present disclosure. While a general order of the steps of method 700 is shown in FIG. 7, method 700 can include more or fewer steps or can arrange the order of the step differently than those shown in FIG. 7. Further, two or more steps may be combined in one step. Generally, method 700 starts at a START operation at step 704 and ends with an END operation at step 724. Method 700 can be executed as a set of computer-executable instructions executed by a computer system (e.g., the one or more computing device(s) 104, the one or more server(s) 112, the processor 204, etc.) and encoded or stored on a computer readable medium (e.g., memory 208, etc.). Hereinafter, method 700 shall be explained with reference to the systems, components, modules, applications, software, data structures, user interfaces, etc. described in conjunction with FIGS. 1-6.

As illustrated in FIG. 7, method 700 begins at the START operation at step 704 and proceeds to step 708, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives user login credentials. According to embodiments of the present disclosure, the received login credentials may include, for example, a username and a user password as illustrated in FIG. 4A

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives the user login credentials at step 708, method 700 proceeds to step 712, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 presents user security parameters to the user. According to embodiments of the present disclosure, the user security parameters may include, for example identified location parameters (e.g., home, office, private, public, semi-private, semi-public etc.), personal information parameters (e.g., name, telephone number, personal email address, date of birth, social security number, banking details, height, weight, place of birth, home address, work address, marital status, verification information, one time passwords, pin numbers, etc.), work information parameters (e.g., security codes, salary, business email address, project information, software details, updates to software or project information, PDF views, programming applications, chat applications, Word documents, etc.).

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 presents user security parameters to the user at step 712, method 700 proceeds to step 716, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives values for the user security parameters.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives values for the user security parameters at step 716, method 700 proceeds to step 720, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 updates the user security parameters with the received values.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 updates the user parameters with the received values at step 720, method 700 ends with the END operation at step 724.

FIGS. 8A and 8B represent a flow diagram depicting method 800 for automatically censoring sensitive data in accordance with embodiments of the present disclosure. While a general order of the steps of method 800 is shown in FIGS. 8A and 8B, method 800 can include more or fewer steps or can arrange the order of the step differently than those shown in FIGS. 8A and 8B. Further, two or more steps may be combined in one step. Generally, method 800 starts at a START operation at step 804 and ends with an END operation at step 852. Method 800 can be executed as a set of computer-executable instructions executed by a computer system (e.g., the one or more computing device(s) 104, the one or more server(s) 112, the processor 204, etc.) and encoded or stored on a computer readable medium (e.g., memory 208, etc.). Hereinafter, method 800 shall be explained with reference to the systems, components, modules, applications, software, data structures, user interfaces, etc. described in conjunction with FIGS. 1-6.

As illustrated in FIG. 8A, method 800 begins at the START operation at step 804 and proceeds to step 808, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives information that is to be displayed on a display of a computing device.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 receives information that is to be displayed on a display of a computing device at step 808, method 800 proceeds to step 812, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 analyzes the received information based on user security parameters. According to embodiments of the present disclosure, the user security parameters may include, for example, identified location parameters (e.g., home, office, private, public, semi-private, semi-public etc.), personal information parameters (e.g., name, telephone number, personal email address, date of birth, social security number, banking details, height, weight, place of birth, home address, work address, marital status, verification information, one time passwords, pin numbers, etc.), work information parameters (e.g., security codes, salary, business email address, project information, software details, updates to software or project information, PDF views, programming applications, chat applications, Word documents, etc.).

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 analyzes the received information based on the user security parameters at step 812, method 800 proceeds to step 816, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 identifies sensitive data and non-sensitive data from the received information based on the user security parameters.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 identifies sensitive data and non-sensitive data from the received information based on the user security parameters at step 816, method 800 proceeds to step 820, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 displays the received information on the display of the computing device.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 displays the received information on the display of the computing device at step 820, method 800 proceeds to step 824, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 obtains image data depicting a monitored environment in proximity to the display of the computing device.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 obtains image data depicting a monitored environment in proximity to the display of the computing device at step 824, method 800 proceeds to step 828 where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 analyzes the image data to identify a detected event in the monitored environment.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 analyzes the image data to identify a detected event in the monitored environment at step 828, method 800 proceeds to decision step 832 as illustrated in FIG. 8B, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines if there is a detected event. If the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines that there is a detected event (YES) at decision step 832, method 800 proceeds to decision step 836, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines if the detected event exceeds a predetermined threshold. If the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines that the detected event exceeds the predetermined threshold (YES) at decision step 836, method 800 proceeds to step 840, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 censors regions of the displayed information where the identified sensitive data was displayed.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 censors regions of the displayed information where the identified sensitive data was displayed at step 840, method 800 proceeds to decision step 844 where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines if an event is still being detected. If the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines that an event is still being detected (YES) at decision step 844, method 800 returns to step 840 where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 continues to censor regions of the displayed information where the identified sensitive data was displayed. If the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 determines that an event is not still being detected (NO) at decision step 844, method 800 proceeds to step 848, where the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 ceases censoring regions of the displayed information where the identified sensitive data was displayed.

After the processor 204 of the one or more computing device(s) 104 or the one or more server(s) 112 ceases censoring regions of the displayed information where the identified sensitive data was displayed at step 848, method 800 ends with the END operation at step