Method and electronic device for managing privacy of screen view

Abstract

A method for managing privacy of a screen view on an electronic device is provided. The method includes displaying content on a screen view of the electronic device, where the content includes one or more private objects; determining an upcoming event of a user of the electronic device and an associated user intent to share the displayed content during execution of at least one upcoming event; determining one or more privacy parameters of the displayed content related to the upcoming event; and modifying a screen view of the electronic device based on the one or more privacy parameters during execution of the upcoming event, where the modified screen view excludes some or more private objects that are not necessary to execute the upcoming event.

Description

Technical Field

[0001] The present disclosure relates to an electronic device and more particularly to a method for managing the privacy of a screen view on an electronic device and an electronic device. Background Art

[0002] Mobile phones are classified as personal electronic devices. However, in everyday life, users need to share mobile phones or mobile screens with other users, which can create security risks because other users can intentionally or unintentionally access the user's personal information. Most of the time, all personal information is not required to complete a task / event (e.g., booking a hotel room).

[0003] Figure 1A and Figure 1B Some methods of keeping personal information secure from being shared with other users when sharing an electronic device according to the related art are shown.

[0004] Reference Figure 1A Consider the following scenario (1), wherein a user of an electronic device (10) wishes to book a hotel room (11). In addition, the hotel staff requires the user to show his identity (ID) card for verification purposes (12). In this case, the user of the electronic device (10) searches (13a) for a digital ID (e.g., driver's license) stored in the electronic device (13), and shows the digital ID (14) to the hotel staff to complete the verification and book a hotel room. In this scenario, the digital ID contains personal information, such as the user's driver's license number (DL number), driver's license number validity, user name, user date of birth (DOB), user address, and user signature. Booking a hotel room does not require all personal information. The user's DL number and name are sufficient. However, the user inadvertently shares additional personal information (e.g., user DOB, address, and signature) with the hotel staff, creating a security risk.

[0005] Some methods of the related art keep personal information safe from being shared with other users when sharing an electronic device (10) or the screen of an electronic device (10). Blurring and / or covering personal information and modifying application content are two examples of methods of the related art.

[0006] Reference Figure 1BConsider the following scenario (2), in which a second user asks a first user of an electronic device (10) for help in booking a taxi because the second user has left her mobile phone at home (21). Therefore, the first user gives his mobile phone to the second user (22). However, before sharing the electronic device (10) with the second user, the first user notices that the taxi booking application (23, 24) contains some personal information (e.g., saved location, payment method). Therefore, the first user uses a method of the related art (e.g., obfuscation method (25a and 25b)) (25) to prevent personal information from being shared with the second user when sharing the electronic device (10) or the screen of the electronic device (10).

[0007] However, the method of the related art has some limitations (e.g., blurring and / or covering personal information). Regardless of the intent of the task, the method of the related art / electronic device (10) covers / blurs all personal information by default. Not all blur shapes (such as circles) are ideal for covering all types of content (e.g., personal information). As a result, there is a high risk of data leakage. In addition, there are also various tools and techniques for removing image blur, such as Photo Enhancer AI. Users can take screenshots / click on pictures and then deblur the content, thereby exposing their personal information. In addition, the method of the related art uses covering / blurring on static content, and personal information that may be required to complete an event is sometimes also blurred. In addition, when sharing content in real time, the current method does not take into account user privacy or event relevance. In addition, due to application permissions, the method of the related art cannot modify the user interface (UI) elements of the running application.

[0008] Some methods of the related art keep personal information safe from being shared with other users by modifying the application content when sharing an electronic device (10) or the screen of an electronic device (10). However, a major drawback of this solution is that the user / solution may require application modification permissions, which not all applications provide.

[0009] Thus, it would be desirable to address the above-mentioned or other disadvantages or at least provide a useful alternative for managing the privacy of screen views.

[0010] The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no statement is made, as to whether any of the above might be applicable as prior art with respect to the present disclosure. Summary of the invention

[0011] Aspects of the present disclosure are to at least solve the above-mentioned problems and / or disadvantages and to provide at least the advantages described below. Therefore, one aspect of the present disclosure is to provide a method and an electronic device for managing the privacy of a screen view on an electronic device by intelligently modifying the screen view of the electronic device based on one or more privacy parameters (e.g., region of interest (RoI), sensitivity index, event relevance score, etc.) during the execution of an upcoming event (e.g., ticket booking). The modified screen view excludes one or more private objects that are not necessary / not non-sensitive user interface (UI) components for executing at least one upcoming event. Non-sensitive UI components are necessary (minimum required UI components) for executing the upcoming event. As a result, the method executes the upcoming event with the necessary non-sensitive UI components and protects the user's privacy without enhancing the hardware components or framework associated with the electronic device.

[0012] Another aspect of the present disclosure is to intelligently enable one or more screen views on an electronic device and / or a connected electronic device (e.g., a smart television (TV)) to display a modified screen view during the execution of an upcoming event. For example, in the case of a "foldable electronic device / flip electronic device" or the like, one screen (main screen or first display) is used as a "user view / screen" and another screen (second display) is used as a "security view / screen" to utilize various available features of the electronic device to execute the upcoming event. As a result, when the electronic device shares the displayed content in real time, user privacy or event relevance is taken into account.

[0013] Additional aspects will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the presented embodiments.

[0014] According to one aspect of the present disclosure, a method for managing the privacy of a screen view (e.g., a user-friendly interface) on an electronic device is provided. The method includes: displaying content on the screen view of the electronic device by the electronic device, wherein the content includes one or more private objects; determining, by the electronic device, an upcoming event of a user of the electronic device and an associated user intent to share the displayed content during the upcoming event; determining, by the electronic device, one or more privacy parameters of the displayed content associated with the upcoming event; and modifying, by the electronic device, the screen view of the electronic device based on the one or more privacy parameters during the upcoming event, wherein the modification includes modifying at least one of the number and position of one or more private objects included in the content based on the one or more privacy parameters.

[0015] In an embodiment of the present disclosure, the screen view of the electronic device is displayed on a first screen of the electronic device.

[0016] In an embodiment of the present disclosure, the modified screen view of the electronic device is displayed on a second screen of the electronic device and / or a screen of a connected electronic device.

[0017] In an embodiment of the present disclosure, determining by the electronic device an upcoming event of the electronic device and a user intent associated with sharing displayed content during execution of the upcoming event includes: determining by the electronic device a plurality of event parameters of the displayed content; applying by the electronic device the plurality of event parameters to a pre-trained on-device machine learning (ML) model to determine the upcoming event in real time; determining by the electronic device an upcoming event of the electronic device; determining by the electronic device whether a security view is compatible with the upcoming event based on the displayed content on a screen view of the electronic device, wherein the security view excludes one or more private objects that are not necessary for executing the upcoming event; in response to determining that the security view is compatible with the upcoming event, displaying by the electronic device a notification message on the screen view of the electronic device to share the displayed content; and receiving by the electronic device the user intent to share the displayed content when the notification message is displayed on the screen view of the electronic device.

[0018] In an embodiment of the present disclosure, the multiple event parameters include but are not limited to: one or more screen context information, timestamp information, location information, and information associated with an application currently running on the electronic device.

[0019] In an embodiment of the present disclosure, the upcoming event includes but is not limited to: a payment event, a reservation event, a registration event, a dynamic web content sharing event, and a screen sharing event.

[0020] In an embodiment of the present disclosure, the user intention to share the displayed content includes but is not limited to: a text command received from a user of the electronic device, a voice input received from a user of the electronic device, a touch input received from a user of the electronic device, a gesture input received from a user of the electronic device, changing the orientation of the electronic device, selecting an area on the screen of the electronic device, and pressing a hardware key of the electronic device.

[0021] In an embodiment of the present disclosure, the one or more privacy parameters include: a region of interest (RoI), a sensitivity index, and an event relevance score.

[0022] In an embodiment of the present disclosure, the RoI is determined in the following manner: the electronic device extracts the RoI of the screen view of the electronic device through segmentation processing, wherein the RoI includes user interface (UI) components (e.g., sensitive UI components, non-sensitive UI components, etc.).

[0023] In an embodiment of the present disclosure, the sensitivity index is determined in the following manner: the electronic device determines the sensitivity index of each UI component using a pre-trained on-device deep learning classifier, wherein the pre-trained on-device deep learning classifier is trained using a diverse data set, and the diverse data set includes: user intent, user preferences, user's previous interactions, and screen context information.

[0024] In an embodiment of the present disclosure, the event relevance is determined in the following manner: the electronic device determines the event relevance score of each UI component using a pre-trained on-device deep learning classifier, wherein the pre-trained on-device deep learning classifier is trained using a diverse data set, and the diverse data set includes: the intent of the upcoming event, user preferences related to the upcoming event, the user's previous interactions with the upcoming event, and screen context information.

[0025] In an embodiment of the present disclosure, modifying the screen view of the electronic device by the electronic device based on one or more privacy parameters during the execution of an upcoming event includes: shortlisting UI components by the electronic device based on one or more privacy parameters, wherein the shortlisted UI components are necessary for executing the upcoming event; and intelligently modifying the screen view of the electronic device by the electronic device based on one or more of the display properties of the electronic device, the orientation of the electronic device, user-related information, and user feedback, wherein the modified screen view of the electronic device includes the shortlisted UI components.

[0026] According to another aspect of the present disclosure, an electronic device for managing the privacy of a screen view of an electronic device is provided. The electronic device includes: a display; at least one processor; a memory storing one or more programs configured to be executed by the at least one processor, the one or more programs including instructions for performing the following operations: displaying content on the screen view of the electronic device on the display, wherein the content includes one or more private objects; determining at least one upcoming event of a user of the electronic device; determining one or more privacy parameters of the displayed content related to the at least one upcoming event; and modifying the screen view of the electronic device based on one or more privacy parameters during the execution of the at least one upcoming event, wherein the at least one processor modifies at least one of the number and position of one or more private objects included in the content based on the one or more privacy parameters.

[0027] Other aspects, advantages, and salient features of the present disclosure will become apparent to those skilled in the art from the following detailed description which, in conjunction with the accompanying drawings, discloses various embodiments of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and other aspects, features and advantages of certain embodiments of the present disclosure will become more apparent through the following description in conjunction with the accompanying drawings, in which:

[0029] Figure 1A and Figure 1B Some methods of keeping personal information secure from being shared with other users when sharing an electronic device according to the related art are shown;

[0030] Figure 2A A block diagram illustrating an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure;

[0031] Figure 2B A block diagram showing a user interface (UI)-event detector of an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure;

[0032] Figure 2C A block diagram showing a smart score generator of an electronic device for managing the privacy of a screen view according to an embodiment of the present disclosure;

[0033] Figure 2D A block diagram showing a security view generator of an electronic device for managing the privacy of a screen view according to an embodiment of the present disclosure;

[0034] Figure 3 is a flow chart illustrating a method for managing privacy of a screen view according to an embodiment of the present disclosure;

[0035] Figure 4 is a flow chart illustrating a method for determining an upcoming event of an electronic device and an associated user intent to share displayed content according to an embodiment of the present disclosure;

[0036] Figure 5 is a flow chart illustrating a method for determining a sensitivity index of each UI component using a pre-trained on-device deep learning classifier according to an embodiment of the present disclosure;

[0037] Figure 6 is a flowchart illustrating a method for determining an event relevance score for each UI component using a pre-trained on-device deep learning classifier to obtain a minimum set of UI components that execute an upcoming event according to an embodiment of the present disclosure;

[0038] Figure 7 is a flowchart illustrating a method for determining a minimum set of UI components for executing an upcoming event according to an embodiment of the present disclosure;

[0039] Figure 8 is a flow chart illustrating a method for intelligently modifying a screen view of an electronic device to manage privacy of the screen view according to an embodiment of the present disclosure;

[0040] Fig. 9 A method for managing the privacy of a screen view when performing a payment event according to an embodiment of the present disclosure is shown;

[0041] Fig.10 A method for managing the privacy of a screen view when performing a hotel reservation event according to an embodiment of the present disclosure is shown;

[0042] Fig.11 A method for managing the privacy of a screen view when performing a taxi booking event according to an embodiment of the present disclosure is shown;

[0043] Fig.12 A method for managing the privacy of a screen view of a multi-display electronic device according to an embodiment of the present disclosure is illustrated.

[0044] The same reference numerals are used throughout the drawings to denote the same elements. DETAILED DESCRIPTION

[0045] The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of the various embodiments of the present disclosure as defined by the claims and their equivalents. It includes various specific details to assist in understanding, but these details are considered to be merely exemplary. Therefore, it will be appreciated by those of ordinary skill in the art that various changes and modifications to the various embodiments described herein may be made without departing from the scope and spirit of the present disclosure. In addition, descriptions of well-known functions and configurations may be omitted for clarity and brevity.

[0046] The terms and words used in the following description and claims are not limited to the bibliographical meanings, but are merely used by the inventor to enable a clear and consistent understanding of the present disclosure. Therefore, it will be apparent to those skilled in the art that the following description of various embodiments of the present disclosure is provided for illustrative purposes only and not for the purpose of limiting the present disclosure as defined by the appended claims and their equivalents.

[0047] It should be understood that the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a component surface" includes reference to one or more of such surfaces.

[0048] The various embodiments described herein are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments. Unless otherwise indicated, the term "or" used herein refers to a non-exclusive or. The examples used herein are intended only to help understand the manner in which the embodiments of this article can be practiced, and further enable those skilled in the art to practice the embodiments of this article. Therefore, the examples should not be interpreted as limiting the scope of the embodiments of this article.

[0049] As traditional in the art, embodiments can be described and illustrated according to the block of performing one or more functions described.These blocks, which may be referred to as units or modules, etc. in this article, are physically implemented by analog or digital circuits (such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hard-wired circuits, etc.), and may be optionally driven by firmware.Circuit can be, for example, implemented in one or more semiconductor chips, or implemented on substrate supports (such as printed circuit boards, etc.).The circuit constituting the block can be implemented by dedicated hardware, or by a processor (for example, one or more programmed microprocessors and associated circuits), or by a combination of dedicated hardware of some functions of the execution block and a processor of other functions of the execution block.Without departing from the scope of the present disclosure, each block of the embodiment can be physically separated into two or more interacting and discrete blocks.Similarly, without departing from the scope of the present disclosure, the block of the embodiment can be physically combined into more complex blocks.

[0050] The accompanying drawings are used to help easily understand various technical features, and it should be understood that the embodiments presented herein are not limited by the accompanying drawings. Therefore, except for those specifically stated in the accompanying drawings, the present disclosure should be interpreted as extending to any changes, equivalents and substitutes. Although the terms first, second, etc. can be used to describe various elements in this article, these elements should not be limited by these terms. These terms are usually only used to distinguish one element from another element.

[0051] Therefore, embodiments of the present invention disclose a method for managing the privacy of a screen view on an electronic device. The method includes displaying content on a screen view of the electronic device by an electronic device, wherein the content includes one or more privacy information. In addition, the method includes determining, by the electronic device, an upcoming event of a user of the electronic device and an associated user intent to share the displayed content during the execution of the upcoming event. In addition, the method includes determining, by the electronic device, one or more privacy parameters of the displayed content associated with the upcoming event. In addition, the method includes modifying, by the electronic device, the screen view of the electronic device based on the one or more privacy parameters during the execution of the upcoming event, wherein the modified screen view excludes one or more private objects that are not necessary for executing the upcoming event.

[0052] Therefore, embodiments of the present invention provide an electronic device for managing the privacy of a screen view on an electronic device. The electronic device includes a privacy controller coupled to a processor and a memory. The privacy controller displays content on the screen view of the electronic device, wherein the content includes one or more private objects. In addition, the privacy controller determines an upcoming event of a user of the electronic device and an associated user intent to share the displayed content during the upcoming event execution. In addition, the privacy controller determines one or more privacy parameters of the displayed content related to the upcoming event. In addition, the privacy controller modifies the screen view of the electronic device based on the one or more privacy parameters during the upcoming event execution, wherein the modified screen view excludes one or more private objects that are not necessary for executing the upcoming event.

[0053] Unlike the methods and systems of the related art, the proposed method allows an electronic device to manage the privacy of a screen view on an electronic device by intelligently modifying the screen view of the electronic device based on one or more privacy parameters (e.g., region of interest (RoI), sensitivity index, event relevance score, etc.) during the execution of an upcoming event (e.g., ticket booking). The modified screen view excludes one or more private objects that are not necessary / not non-sensitive UI components for executing the upcoming event. The non-sensitive UI components are necessary for executing the upcoming event (minimum required UI components). Therefore, the method uses the necessary non-sensitive UI components to execute the upcoming event and protects user privacy without the need to enhance hardware components or frameworks associated with the electronic device.

[0054] Another aspect of the embodiments herein is to intelligently enable one or more screen views on an electronic device and / or a connected electronic device (e.g., a smart television (TV), a smart watch, etc.) to display a modified screen view during the execution of an upcoming event. For example, in the case of a "foldable electronic device / flip electronic device" or the like, one screen (main screen or first display) is used as a "user view / screen" and another screen (second display) is used as a "security view / screen" to utilize various available features of the electronic device to execute the upcoming event. Therefore, the electronic device takes user privacy or event relevance into account when sharing the displayed content in real time.

[0055] Referring now to the drawings, and more particularly to the drawings in which preferred embodiments are shown, Figure 2A , Figure 2B , Figure 2C , Figure 2D and Figures 3 to 12 , wherein similar reference characters denote corresponding features consistently throughout the drawings.

[0056] Figure 2A A block diagram illustrating an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure.

[0057] Reference Figure 2A The electronic device (100) may be, for example, but not limited to, a smart phone, a laptop computer, a smart television (TV), etc.

[0058] In an embodiment of the present disclosure, an electronic device (100) includes: a memory (110), a processor (120), a communicator (130), a display (140), an application repository (150), and a privacy controller (160).

[0059] In an embodiment of the present disclosure, a memory (110) stores one or more privacy parameters of displayed content, an upcoming event of a user of an electronic device (100), an associated user intent, and a plurality of event parameters. The memory (110) stores one or more programs including instructions to be executed by a processor (120). The one or more programs include instructions for performing the following operations: displaying content on a screen view of an electronic device on a display, wherein the content includes one or more private objects; determining at least one upcoming event of a user of the electronic device; determining one or more privacy parameters of the displayed content associated with the at least one upcoming event; and modifying the screen view of the electronic device based on the one or more privacy parameters during execution of the at least one upcoming event, wherein at least one processor modifies at least one of the number and position of one or more private objects included in the content based on the one or more privacy parameters.

[0060] The memory (110) may include a non-volatile storage element. Examples of such non-volatile storage elements may include: a magnetic hard disk, an optical disk, a floppy disk, a flash memory, or an electrically programmable memory (EPROM) or an electrically erasable programmable (EEPROM) memory. In addition, in some examples, the memory (110) may be considered a non-transitory storage medium. The term "non-transitory" may indicate that the storage medium is not implemented in a carrier wave or a propagating signal. However, the term "non-transitory" should not be interpreted as the memory (110) being non-removable. In some examples, the memory (110) may be configured to store a larger amount of information than the memory. In some examples, the non-transitory storage medium may store data that may change over time (e.g., in a random access memory (RAM) or a cache memory). The memory (110) may be an internal storage unit, or it may be an external storage unit of the electronic device (100), a cloud storage, or any other type of external storage.

[0061] The processor (120) communicates with the memory (110), the communicator (130), the display (140), the application repository (150), and the privacy controller (160). The processor (120) is configured to execute instructions stored in the memory (110) and perform various processes. The processor (120) may include one or more processors, which may be general-purpose processors (such as central processing units (CPUs), application processors (APs), etc.), graphics processing units (such as graphics processing units (GPUs), visual processing units (VPUs)), and / or artificial intelligence (AI) dedicated processors (such as neural processing units (NPUs)).

[0062] The communicator (130) is configured to communicate internally between internal hardware components and with external devices (e.g., connected electronic devices, etc.) via one or more networks (e.g., radio technologies). The communicator (130) includes electronic circuitry specific to standards that implement wired or wireless communications.

[0063] Display (140) (eg, first screen (140a) of electronic device (100) ( Figure 2A The display (140) receives user input and is made of a liquid crystal display (LCD), a light emitting diode (LED), an organic light emitting diode (OLED), or another type of display. The user input may include, but is not limited to, touch, slide, drag, gesture, voice command, etc. The display (140) has displayed content on the screen view of the electronic device (100), wherein the content includes one or more private objects (e.g., the user's bank details).

[0064] The application repository (150) is implemented by processing circuits (such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hard-wired circuits, etc.), and can be optionally driven by firmware. The circuits can be implemented, for example, in one or more semiconductor chips, or on a substrate support (such as a printed circuit board, etc.). The application repository (150a) is configured to store function information and corresponding screen identification of each application of the electronic device (100). The application repository (150) includes multiple applications (150a) to applications (150n). Examples of the application repository (150a) are, but are not limited to, media applications, web applications, video player applications, camera applications, game applications, business applications, educational applications, lifestyle applications, entertainment applications, utility applications, travel applications, etc.

[0065] The privacy controller (160) is implemented by processing circuits (such as logic gates, integrated circuits, microprocessors, microcontrollers, memory circuits, passive electronic components, active electronic components, optical components, hard-wired circuits, etc.), and may optionally be driven by firmware. The circuits may, for example, be implemented in one or more semiconductor chips, or on a substrate support (such as a printed circuit board, etc.).

[0066] More specifically, the privacy controller 160 may change at least one of the number or position of one or more objects included in the content based on one or more privacy parameters. In other words, the privacy controller 160 may remove some of the one or more objects included in the content based on the privacy parameters, and change the position of some of the one or more objects. Alternatively, the privacy controller 160 may change the size or shape of one or more objects included in the content based on the privacy parameters.

[0067] In an embodiment of the present disclosure, the privacy controller (160) includes: a UI event detector (161), an intelligent score generator (162), a security view generator (163) and an artificial intelligence (AI) engine (164).

[0068] The UI event detector (161) determines an upcoming event of a user of the electronic device (100) and an associated user intent to share displayed content during the execution of the upcoming event. The upcoming events include, but are not limited to, payment events, reservation events, registration events, dynamic web content sharing events, and screen sharing events. The user intent to share displayed content is determined based on, for example, a text command received from the user of the electronic device (100), a voice input received from the user of the electronic device (100), a touch input received from the user of the electronic device (100), a gesture input received from the user of the electronic device (100), changing the orientation of the electronic device (100), selecting an area on the screen (i.e., display (140)) of the electronic device (100), pressing a hardware key of the electronic device (100), etc. The UI event detector (161) extracts a region of interest (RoI) of a screen view of the electronic device (100) by a segmentation method, wherein the RoI includes a user interface (UI) component.

[0069] In addition, the UI event detector (161) determines multiple event parameters of the displayed content. The multiple event parameters include, but are not limited to, screen context information, timestamp information, location information, and information associated with an application currently running on the electronic device (100). The UI event detector (161) applies the multiple event parameters to a pre-trained on-device machine learning (ML) model to determine an upcoming event in real time. The UI event detector (161) determines an upcoming event of the electronic device (100). The UI event detector (161) determines whether the security view is compatible with the upcoming event based on the displayed content on the screen view of the electronic device (100), wherein the security view excludes one or more private objects that are not necessary for executing the upcoming event. In response to determining that the security view is compatible with the upcoming event, the display (140) displays a notification message (e.g., a pop-up message, a voice message, a banner, etc.) on the screen view of the electronic device (100) to share the displayed content. The UI event detector (161) then receives the user's intention to share the displayed content when the notification message is displayed on the screen view of the electronic device (100).

[0070] The smart score generator (162) determines one or more privacy parameters of the displayed content related to the upcoming event. The one or more privacy parameters include: RoI, sensitivity index, and event relevance score. The smart score generator (162) uses a pre-trained on-device deep learning classifier to determine the sensitivity index of each UI component. The pre-trained on-device deep learning classifier is trained using a diverse data set, and the diverse data set includes: user intent, user preferences, user previous interactions, and screen context information. The smart score generator (162) uses the pre-trained on-device deep learning classifier to determine the event relevance score of each UI component. The pre-trained on-device deep learning classifier is trained using a diverse data set. The diverse data set includes: intent of the upcoming event, user preferences related to the upcoming event, user previous interactions with the upcoming event, and screen context information.

[0071] The security view generator (163) modifies the screen view of the electronic device (100) based on one or more privacy parameters during the execution of the upcoming event. The modified screen view excludes one or more private objects that are not necessary for executing the upcoming event. The screen view of the electronic device (100) is displayed on the first screen (140a) ( Figure 2A The modified screen view of the electronic device (100) is displayed on the second screen (140b) ( Figure 2A ) and / or connected electronic devices ( Figure 2A The security view generator (163) shortlists the UI components based on one or more privacy parameters. The shortlisted UI components are necessary for executing the upcoming event. The security view generator (163) then intelligently modifies the screen view of the electronic device (100) based on one or more of the display properties of the electronic device (100), the orientation of the electronic device (100), user-related information, and user feedback. The modified screen view of the electronic device (100) includes the shortlisted UI components.

[0072] Figure 2A At least one of the multiple modules / components in the system may be implemented by an AI engine (164). Functions associated with the AI ​​engine (164) may be executed by corresponding memories (110) and processors (120). One or more processors control the processing of input data according to predefined operating rules or the AI ​​engine (164) stored in non-volatile memory and volatile memory. The predefined operating rules or the AI ​​engine (164) are provided by training or learning.

[0073] Here, providing by learning means that a predefined operating rule or AI model of a desired characteristic is formulated by applying a learning process to a plurality of learning data. Learning may be performed in the device itself that executes the AI ​​according to the embodiment, and / or learning may be achieved by a separate server / system.

[0074] The AI ​​engine (164) may include multiple neural network layers. Each layer has multiple weight values ​​and performs layer operations by calculating the previous layer and operating on multiple weights. Examples of neural networks include, but are not limited to, convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), restricted Boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), generative adversarial networks (GANs), and deep Q networks.

[0075] The learning process is a method for training a predetermined target device (e.g., a robot) using a plurality of learning data to cause, allow, or control the target device to make a determination or prediction. Examples of the learning process include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0076] In addition, according to an embodiment of the present disclosure, the privacy controller 160 may be implemented separately from the processor 120, but this is only an example. The privacy controller 160 may be integrated with the processor 120 to be implemented as at least one processor.

[0077] Although Figure 2A Various hardware components of the electronic device (100) are shown, but it should be understood that other embodiments are not limited thereto. In other embodiments of the present disclosure, the electronic device (100) may include fewer or more components. In addition, the markings or names of the components are only for illustrative purposes and do not limit the scope of the present disclosure. One or more components can be combined together to perform the same or substantially similar functions to manage the privacy of the screen view.

[0078] Figure 2B A block diagram of a UI event detector of an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure is shown.

[0079] Reference Figure 2B The UI event detector (161) includes: an input detector (161a), a screen capture engine (161b), a screen segmentation engine (161c) and an intention recognizer (161d).

[0080] The input detector (161a) receives various types of input from the user of the electronic device (100), for example, a text command received from the user of the electronic device (100), a voice input received from the user of the electronic device (100), a touch input received from the user of the electronic device (100), a gesture input received from the user of the electronic device (100), changing the orientation of the electronic device (100), selecting an area on the screen of the electronic device (100), and pressing a hardware key of the electronic device (100).

[0081] The screen scraping engine (161b) scrapes the displayed content to extract the RoI and serializes the extracted RoI to the screen segmentation engine (161c) based on the application content positioning. The extracted RoI includes one or more UI components (e.g., email id links). The RoI is determined using mechanisms such as pre-trained regression models, classifiers, and non-maximum suppression mechanisms. The pre-trained regression model predicts bounding box coordinates (x, y, w, h), where x and y represent the offset of the cell position, and w and h represent the width and height, respectively. The classifier assigns class probabilities to these boxes, where the probability (confidence score) indicates the likelihood that the box contains an object. The confidence score is determined by the following equation, confidence score = Pr(contains object)*IoU(pred, truth) (1).

[0082] Where Pr indicates probability and IoU indicates intersection over union, which is an evaluation metric for measuring the accuracy of an object detector for a specific dataset. Non-maximum suppression selects the most appropriate bounding box by first selecting the bounding box with a high confidence score and then removing all other boxes with high overlap.

[0083] The screen segmentation engine (161c) generates a feature map for all bounding boxes (i.e., best fit bounding boxes) by converting the region (best fit bounding box) into a feature vector using a pre-trained deep learning model (e.g., a pre-trained on-device deep learning classifier). The screen segmentation engine (161c) divides the region into all candidate segments, such as s1, s2, s3...sn. The screen segmentation engine (161c) predicts an object confidence score for each segment. The object confidence score indicates the likelihood that the region contains the object. If the object confidence score exceeds a certain threshold, the segment has a foreground object (e.g., an email id link, a mobile number, etc.), otherwise, the segment has a background object. The object is then labeled by the screen segmentation engine (161c), indicating which category it belongs to.

[0084] The intent identifier (161d) determines the user's intent based on multiple event parameters. The multiple event parameters include: screen context information, timestamp information, location information, and information associated with a currently running application of the electronic device (100). The intent identifier (161d) uses a pre-trained on-device deep learning classifier to predict event intent based on the input obtained after segmentation.

[0085] Figure 2C A block diagram of a smart score generator of an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure is shown.

[0086] refer to Figure 2C , the smart score generator (162) includes: a sensitivity and privacy detector (162a), an event correlation predictor (162b) and a backward eliminater (162c).

[0087] The sensitivity and privacy detector (162a) uses a set of rules / heuristics in combination with a pre-trained on-device deep learning classifier, wherein the pre-trained on-device deep learning classifier is trained on a diverse dataset with multiple parameters representing user profiles and attributes derived from displayed UI components (such as user intent, user preferences, past interactions, display component context, etc.). The sensitivity and privacy detector (162a) is trained on a large amount of labeled data, wherein each training record represents a set of labeled UI widgets and their sensitivity coefficients. As a result, when the proposed method is triggered by the input detector (161a), the sensitivity and privacy detector (162a) extracts values ​​from all pre-trained classifier parameters and determines whether the displayed UI component is sensitive or non-sensitive.

[0088] The event relevance predictor (162b) determines the utilization / convenience of each UI component for an event using a hybrid architecture including a set of heuristic strategies and an intelligent prediction model to determine the "relevance level" of each UI component, which may be referred to as an "event relevance score."

[0089] The backward eliminator (162c) receives the set of labeled UI components, along with the sensitivity index and the event relevance score, to obtain shortlisted UI components. The shortlisted UI components are event-customized and privacy-preserving UI components that are optimally necessary for successfully executing the events of interest to the user. The backward eliminator (162c) reduces visual complexity while facilitating providing behavior without privacy leakage in a user-friendly and convenient manner. The backward eliminator (162c) reduces misclassification by using a feedback system.

[0090] Figure 2DA block diagram of a security view generator of an electronic device for managing privacy of a screen view according to an embodiment of the present disclosure is shown.

[0091] Reference Figure 2D , the security view generator (163) includes an event anticipation UI extractor (163a) and a layout modifier (163b).

[0092] The event anticipation UI extractor (163a) optimizes the displayed UI components by selectively retaining only those UI components required to execute the event of interest to the user without leaking any privacy information. A set of UI components (e.g., shortlisted UI components), sensitivity index, and event relevance score are input to the event anticipation UI extractor (163a). The event anticipation UI extractor (163a) then uses contextual semantic search (CSS) to determine the nature, intent, and implementation status of the upcoming event, using all possible subsets of UI components guided by privacy protection principles. The event anticipation UI extractor (163a) then determines the optimal set of anti-privacy UI components for the event (e.g., shortlisted UI components) and sends the optimal set of anti-privacy UI components to the layout modifier (163b).

[0093] The event anticipation UI extractor (163a) enables the user to experience reduced visual complexity or event-irrelevant clutter elimination while maintaining user privacy. For example, in a transaction scenario of a unified payment interface (UPI), the event anticipation UI extractor (163a) extracts all UI components and finds that only a quick response (QR) code is required to complete a UPI transaction.

[0094] The layout modifier (163b) intelligently modifies the screen view of the electronic device (100) based on one or more of the following factors: display properties of the electronic device (100), orientation of the electronic device (100) (e.g., how a user folds or flips a multi-display electronic device when sharing content), user-related information (e.g., whether the user is left-handed or right-handed, how the user holds the electronic device (100) when sharing content), and user feedback (e.g., manually modifying the screen view). The layout modifier (163b) learns information (e.g., user-related information, display properties, etc.) over a period of time by using an AI engine (164). The modified screen view of the electronic device (100) includes shortlisted UI components that are necessary to execute the upcoming event.

[0095] Figure 3 is a flow chart (300) illustrating a method for managing privacy of screen views according to an embodiment of the present disclosure.

[0096] Reference Figure 3, operations 301-304 are performed by the electronic device (100).

[0097] In operation 301, the method includes displaying content on a screen view of an electronic device (100), wherein the content includes one or more private objects. In operation 302, the method includes determining an upcoming event of a user of the electronic device (100) and a user intent associated with sharing the displayed content during execution of the upcoming event. In operation 303, the method includes determining one or more privacy parameters of the displayed content associated with the upcoming event. In operation 304, the method includes modifying the screen view of the electronic device (100) based on the one or more privacy parameters during execution of the upcoming event, wherein the modified screen view excludes one or more private objects that are not necessary for execution of the upcoming event.

[0098] Figure 4 is a flow chart ( 400 ) illustrating a method for determining an upcoming event of an electronic device and an associated user intent to share displayed content according to an embodiment of the present disclosure.

[0099] Reference Figure 4 , operations 401-404 are performed by the electronic device (100).

[0100] In operation 401, the method includes receiving input (aggregate label scores, segmented boundaries) and feeding an event intent classification to an intent recognizer (161d). In operation 402, the method includes normalizing the received input. In operation 403, the method includes classifying the normalized input using a pre-trained on-device deep learning classifier (multi-class classifier model) to predict event intent, and determining whether the security view is compatible with the predicted event intent (e.g., payment, membership, reservation, privacy, etc.). In operation 404, the method includes notifying the subsystem of a user's intent to share the displayed content of the first screen (140a) with a security view compatible display of the UI component on a second screen (140b) (e.g., folded, flipped).

[0101] Figure 5 is a flow chart (500) illustrating a method for determining a sensitivity index of each UI component using a pre-trained on-device deep learning classifier according to an embodiment of the present disclosure.

[0102] Reference Figure 5 , operations 501-504 are performed by the electronic device (100).

[0103] In operation 501, the method includes retrieving a set of labeled UI components and loading a pre-trained on-device deep learning classifier to determine the sensitivity / privacy of the UI components based on a diverse data set and the diverse data set includes: user intent, user preferences, user previous interactions, and screen context information. In operation 502, the method includes determining a set of UI components that are redundant for completing an upcoming event by applying a trial data set, and removing a set of redundant UI components. In operation 503, the method includes extracting / transforming the set of labeled UI components into a vector of decision feature values, and providing the extracted / transformed set of labeled UI components to a pre-trained on-device deep learning classifier. In operation 504, the method includes classifying each UI component as "sensitive" or "non-sensitive".

[0104] Figure 6 is a flowchart (600) illustrating a method for determining an event relevance score for each UI component using a pre-trained on-device deep learning classifier to obtain a minimum set of UI components that execute an upcoming event according to an embodiment of the present disclosure.

[0105] Reference Figure 6 , operations 601-604 are performed by the electronic device (100).

[0106] In operation 601, the method includes retrieving a set of labeled UI components and loading a pre-trained on-device deep learning classifier to determine an event relevance score for each UI component using the pre-trained on-device deep learning classifier, wherein the pre-trained on-device deep learning classifier is trained using a diverse data set. The diverse data set includes: the intent of the upcoming event, user preferences related to the upcoming event, the user's previous interactions with the upcoming event, and screen context information. In operation 602, the method includes extracting / transforming the set of labeled UI components into a vector of decision feature values, and providing the extracted / transformed set of labeled UI components to the pre-trained on-device deep learning classifier. In operation 603, the method includes determining an event relevance score (e.g., low, medium, and high) for each UI component using the pre-trained on-device deep learning classifier, the event relevance score indicating importance with respect to the intent of the event. In operation 604, the method includes performing a backward elimination process to obtain a minimum set of UI components based on a sensitivity index (sensitivity / privacy) and an event relevance score, wherein the minimum set of UI components is necessary for executing the upcoming event.

[0107] Figure 7 is a flow chart ( 700 ) illustrating a method for determining a minimum set of UI components to execute an upcoming event according to an embodiment of the present disclosure.

[0108] Reference Figure 7 , operations 701-702 are performed by the electronic device (100).

[0109] At operation 701, the method includes retrieving a minimum set of UI components based on a sensitivity index (sensitivity / privacy) and an event relevance score, wherein the minimum set of UI components is necessary to execute an upcoming event. At operation 702, the method includes forwarding the minimum set of UI components to a layout modifier (163b).

[0110] Figure 8 is a flow chart ( 800 ) illustrating a method for intelligently modifying a screen view of an electronic device to manage privacy of the screen view according to an embodiment of the present disclosure.

[0111] Reference Figure 8 , operations 801-802 are performed by the electronic device (100).

[0112] At operation 801, the method includes intelligently rebuilding the layout of the screen view using a minimum set of UI components based on display properties (e.g., user preferred hand, right to left (RTL), LTR, etc.) At operation 802, the method includes displaying the intelligently reconstructed layout on the second screen (140b).

[0113] The various actions, behaviors, boxes, operations, etc. in the flowcharts (300, 400, 500, 600, 700, and 800) may be performed in the order presented, in a different order, or simultaneously. In addition, in some embodiments of the present disclosure, some of the actions, behaviors, boxes, operations, etc. may be omitted, added, modified, or skipped without departing from the scope of the present disclosure.

[0114] Fig. 9 A method for managing the privacy of a screen view when performing a payment event according to an embodiment of the present disclosure is shown.

[0115] Reference Fig. 9 Consider a scenario (900) in which a user of an electronic device (100) goes to a gas station to refuel. After refueling, a gas pump employee requests a QR code (901) in order to send a payment request to the user. To make a payment (902, 903), the user opens a payment app on his or her electronic device (100).

[0116] The privacy controller (160) identifies a given input / opened payment application on a main screen (903a) (such as, the first screen (140a)), and the privacy controller (160) identifies the event intent "make payment" and also determines whether it qualifies for "secure view" rendering. In response to determining that the secure view is compatible with the upcoming event (i.e., the payment request), the privacy controller (160) displays a notification message on the screen view of the electronic device (100) to share the displayed content. When the notification message is displayed on the screen view of the electronic device (100), the privacy controller (160) receives a user intent / input (e.g., touch input (903b)) to share the displayed content.

[0117] The privacy controller (160) then determines one or more privacy parameters (e.g., RoI, sensitivity index, event relevance score, etc.) of the displayed content and extracts all UI components through a segmentation method, for example, as shown in Table 1.

[0118]

Table 1

[0119] UI Components Sensitivity Index Event Correlation QR Code no high UPI Id yes high Name yes middle email address yes middle phone number yes high Image 1 no Low Image 2 no Low

[0120] The privacy controller (160) determines that the QR code, UPI Id, and mobile phone number are necessary UI components for executing the upcoming event, but only the QR code is secure and sufficient to be able to execute the payment event. The privacy controller (160) intelligently modifies the screen view (904) of the electronic device (100), turning the QR code red and displaying the QR code on the secondary screen (904a) (i.e., the second screen (140b)).

[0121] Fig.10 A method for managing privacy of a screen view when performing a hotel reservation event according to an embodiment of the present disclosure is illustrated.

[0122] Reference Fig.10 Consider a scenario (1000) where a user of an electronic device (100) visits a hotel to book a room (1001). A hotel employee asks the user to show some ID during a verification / registration / booking process (1002). The user launches a gallery application (1003) on his or her electronic device (100) to complete the verification / registration / booking process.

[0123] The privacy controller (160) identifies a given input / open gallery application on the main screen (1003a) (i.e., the first screen (140a)), and the privacy controller (160) identifies the event intent "Show ID" and also determines whether it qualifies for "Secure View" rendering. The privacy controller (160) displays a notification message on the screen view of the electronic device (100) to share the displayed content in response to determining that the secure view is compatible with the upcoming event (i.e., Show ID). When the notification message is displayed on the screen view of the electronic device (100), the privacy controller (160) receives a user intent / input (e.g., touch input (1003b)) to share the displayed content.

[0124] The privacy controller (160) then determines one or more privacy parameters (e.g., RoI, sensitivity index, event relevance score, etc.) of the displayed content and extracts all UI components through a segmentation algorithm, for example, as shown in Table 2.

[0125]

Table 2

[0126] UI Components Sensitivity Index Event Correlation image no Low text no Low Name yes high address yes middle Country of Citizenship no Low Member ID no high Credit card balance yes middle Effectiveness no high

[0127] The privacy controller (160) determines that the name, member identity ID, and validity are necessary UI components for executing the upcoming event, but only the member identity ID and validity are secure and sufficient to enable the hotel reservation event to be executed. The privacy controller (160) intelligently modifies the screen view (904) of the electronic device (100), turning the member identity ID and validity red and displaying the member identity ID and validity on the secondary screen (1004a) (i.e., the second screen (140b)).

[0128] Fig.11 A method of managing the privacy of a screen view when performing a taxi booking event according to an embodiment of the present disclosure is shown.

[0129] Reference Fig.11 Consider a scenario (1100) where a user of an electronic device (100) wants to book a taxi (1101 and 1102) for a friend (a second user). The user launches a taxi application (1103) on his or her electronic device (100) to book a taxi.

[0130] The privacy controller (160) identifies a given input / opened taxi application on the main screen (1103a) (i.e., the first screen (140a)), and the privacy controller (160) identifies the event intent "Book a Taxi" and also determines whether it qualifies for "Safe View" rendering. In response to determining that the safe view is compatible with the upcoming event (i.e., book a taxi), the privacy controller (160) displays a notification message on the screen view of the electronic device (100) to share the displayed content. When the notification message is displayed on the screen view of the electronic device (100), the privacy controller (160) receives a user intent / input (e.g., touch input (1103b)) to share the displayed content.

[0131] The privacy controller (160) then determines one or more privacy parameters (e.g., RoI, sensitivity index, event relevance score, etc.) of the displayed content and extracts all UI components through a segmentation method, for example, as shown in Table 3.

[0132]

Table 3

[0133] UI Components Sensitivity Index Event Correlation image no Low Introduction yes Low Boarding location no high Where to no high Saved Places yes Low

[0134] The privacy controller (160) determines that the image, the pickup location, and the destination are necessary UI components for executing the upcoming event, but only the pickup location and the destination are safe. The privacy controller (160) intelligently modifies the screen view (904) of the electronic device (100), turns the pickup location and the destination red, and displays the pickup location and the destination on the secondary screen (1104a) (i.e., the second screen (140b)).

[0135] Fig.12 A method for managing the privacy of a screen view of a multi-display electronic device according to an embodiment of the present disclosure is illustrated.

[0136] Reference Fig.12, consider an example scenario (1201), wherein in the example scenario (1201), the user (1203b) has been asked to share his license information in order to verify the expiration of his license. The privacy controller (160) identifies a given input / opened gallery application on the main screen (1201a) (i.e., the first screen (140a)), and the privacy controller (160) identifies the event intent "share license" and also determines whether it qualifies for "safe view" rendering. The privacy controller (160) displays a notification message on the screen view of the electronic device (100) to share the displayed content in response to determining that the safe view is compatible with the upcoming event (i.e., sharing his license). When the notification message is displayed on the screen view of the electronic device (100), the privacy controller (160) receives the user intent / input (e.g., touch input (1201b)) to share the displayed content.

[0137] The privacy controller (160) then determines one or more privacy parameters (e.g., RoI, sensitivity index, event relevance score, etc.) of the displayed content and extracts all UI components through a segmentation method. The privacy controller (160) finds that the license number is sufficient for this verification (as calculated by the sensitivity index and event relevance score). The privacy controller (160) then intelligently modifies the screen view based on (1202, 1203, and 1204) orientation, preferred hand, folding style, or simply how the user holds the electronic device (100) in daily life. The modified screen view of the electronic device (100) is displayed on the second screen (140b) of the electronic device (100) (i.e., 1202a, 1203a, and 1204a).

[0138] In one embodiment of the present disclosure, the proposed method is also extended to connected display devices, such as smart watches, dashboards, augmented reality (AR) devices, and virtual reality (VR) devices. For example, a first user and a second user are traveling in a car. The second user wants to listen to his / her playlist, so the second user requests the first user to share his / her electronic device (100) so that he / she can listen to his / her favorite songs. When the first user instructs the voice assistant (e.g., Bixby) / connected electronic device to play a song in the application in the "safe view / screen" on the connected dashboard (i.e., connected electronic device) display, the connected electronic device hides all personalized content related to the first user and plays the song / video song on the connected electronic device. The second user can now play the song of his / her choice, and the first user is relieved because he / she has not shared any personal information.

[0139] The embodiments disclosed herein may be implemented using at least one hardware device and performing a network management function to control elements.

[0140] The foregoing description of the specific embodiments will so fully display the general nature of the embodiments herein that others can easily modify and / or adapt such specific embodiments for various applications without departing from the general concepts by applying current knowledge, and therefore, such adaptations and modifications should and are intended to be understood as being within the meaning and range of equivalents of the disclosed embodiments. It should be understood that the phraseology or terminology employed herein is for the purpose of description and not limitation.

[0141] While the present disclosure has been shown and described with reference to various embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents.

Claims

1. A method for managing the privacy of a screen view of an electronic device, the method comprising: displaying content on a screen view of the electronic device by the electronic device, wherein the content includes one or more private objects, determining, by the electronic device, at least one upcoming event for a user of the electronic device; determining, by the electronic device, one or more privacy parameters for displayed content associated with the at least one upcoming event; and The electronic device modifies a screen view of the electronic device based on one or more privacy parameters during execution of the at least one upcoming event, wherein the modification includes modifying at least one of a quantity and a position of one or more private objects included in the content by the electronic device based on the one or more privacy parameters.

2. The method according to claim 1, wherein: The screen view of the electronic device is displayed on a first screen of the electronic device.

3. The method according to claim 1, wherein: The modified screen view of the electronic device is displayed on at least one of a second screen of the electronic device and a screen of a connected electronic device.

4. The method according to claim 3, wherein: determining, by the electronic device, at least one upcoming event for the electronic device: determining, by the electronic device, a plurality of event parameters of the displayed content; applying, by the electronic device, the plurality of event parameters to a pre-trained on-device machine learning (ML) model to determine, in real time, the at least one upcoming event; determining, by the electronic device, the at least one upcoming event for the electronic device; determining, by the electronic device, whether a secure view is compatible with the at least one upcoming event based on content displayed on a screen view of the electronic device, wherein the secure view excludes one or more private objects that are not necessary for executing the at least one upcoming event; In response to determining that the secure view is compatible with the at least one upcoming event, displaying, by the electronic device, a notification message sharing the displayed content on a screen view of the electronic device; and When the notification message is displayed on the screen view of the electronic device, the user's intention to share the displayed content is received by the electronic device.

5. The method according to claim 4, wherein: The plurality of event parameters include at least one of screen context information, timestamp information, location information, and information associated with an application currently running on the electronic device.

6. The method according to claim 4, wherein: The at least one upcoming event includes a payment event, a reservation event, a check-in event, a dynamic web content sharing event, and a screen sharing event.

7. The method according to claim 4, wherein: The user's intention to share the displayed content is determined based on: a text command received from a user of the electronic device, a voice input received from a user of the electronic device, a touch input received from a user of the electronic device, a gesture input received from a user of the electronic device, changing the orientation of the electronic device, selecting an area on a screen of the electronic device, and pressing a hardware key of the electronic device.

8. The method according to claim 7, wherein: The one or more privacy parameters include a region of interest (RoI), a sensitivity index, and an event relevance score.

9. The method according to claim 8, wherein: The RoI is determined by: At least one region of interest (RoI) of a screen view of the electronic device is extracted by the electronic device through a segmentation method, wherein the at least one RoI includes at least one user interface (UI) component.

10. The method according to claim 9, wherein: The sensitivity index is determined by: The electronic device determines a sensitivity index for each UI component using a pre-trained on-device deep learning classifier, wherein the pre-trained on-device classifier is trained using a diverse dataset, and the diverse dataset includes: the user's intent, the user's preferences, the user's previous interactions, and screen context information.

11. The method according to claim 10, wherein: The event correlation is determined in the following manner: An event relevance score for each UI component is determined by the electronic device using a pre-trained on-device deep learning classifier, wherein the pre-trained on-device classifier is trained using a diverse dataset, and the diverse dataset includes: the intent of the at least one upcoming event, the user's preferences related to the at least one upcoming event, the user's previous interactions with the upcoming event, and screen context information.

12. The method according to claim 11, wherein: Modifying, by the electronic device, a screen view of the electronic device based on one or more privacy parameters during execution of the at least one upcoming event includes: shortlisting, by the electronic device, the at least one UI component based on one or more privacy parameters, wherein the at least one UI component shortlisted is necessary to perform the at least one upcoming event; and The electronic device intelligently modifies the screen view of the electronic device based on at least one of the display properties of the electronic device, the orientation of the electronic device, user-related information and user feedback, wherein the modified screen view of the electronic device includes at least one of the shortlisted UI components.

13. An electronic device for managing the privacy of a screen view, the electronic device comprising: monitor; at least one processor; a memory storing one or more programs configured to be executed by the at least one processor; The one or more programs include instructions for: displaying content on the screen view of the electronic device on the display, wherein the content includes one or more private objects, determining at least one upcoming event for a user of the electronic device, determining one or more privacy parameters for displayed content related to the at least one upcoming event, and Modifying a screen view of the electronic device based on one or more privacy parameters during execution of the at least one upcoming event, wherein the at least one processor modifies at least one of a quantity and a position of one or more private objects included in the content based on the one or more privacy parameters.

14. The electronic device according to claim 13, wherein: The screen view of the electronic device is displayed on a first screen of the electronic device.

15. The electronic device according to claim 13, wherein: The modified screen view of the electronic device is displayed on at least one of a second screen of the electronic device and a screen of a connected electronic device.

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