CN120813942A

CN120813942A - Method for associating a digital object with content and method for evaluating the contextual integrity of a digital object

Info

Publication number: CN120813942A
Application number: CN202380095299.0A
Authority: CN
Inventors: 奥列格·波戈尼克; 雅尼·伯曼
Original assignee: Huawei Cloud Computing Technologies Co Ltd
Current assignee: Huawei Cloud Computing Technologies Co Ltd
Priority date: 2023-03-09
Filing date: 2023-03-09
Publication date: 2025-10-17
Also published as: WO2024183910A1

Abstract

For associating a digital object with the content of a structured Web document, selecting a digital object to be protected in the structured Web document, and calculating a watermark integration capacity of the selected digital object. Further, a context-locked watermark is created for the selected digital object based on one or more verifiable elements of the content of the structured Web document such that the size of the context-locked watermark does not exceed the watermark integration capacity, and the context-locked watermark is embedded into the selected digital object. Automatic detection of the contextual integrity of digital objects in a structured Web document is provided so that users accessing the structured Web document can be protected from network attacks.

Description

Method for associating a digital object with content and method for evaluating the contextual integrity of a digital object

Technical Field

The present invention relates generally to the field of network security, and more particularly, to a method for associating a digital object with the content of a structured Web document, and a method for evaluating the contextual integrity of the digital object in the structured Web document.

Background

Currently, network security methods provide adequate protection against network attacks against hardware systems, software systems, or interfaces. However, existing network security approaches focus mainly on computer-centric solutions. Thus, this network attack mainly affects people rather than systems, as people are the weakest ring in computer-centric solutions. Thus, the type of suitable network attack for a person (the way the person thinks and the understanding of the information) has increased significantly. Some examples of such cyber attacks include false news, forgery, email or message phishing, imposition, and the like. In the case of such a network attack, digital objects, such as text, images, audio files, video files, etc., can be easily replicated in one structured Web document by any attacker, and can be reused in another structured Web document in an improper or malicious manner to implement the network attack. However, existing network security methods cannot verify not only the authenticity and integrity of the digital object itself, but also its usage context in the structured Web document. In the present invention, the term "context" refers to a plurality of semantic entities (objects, elements, attributes, etc.) included with a protected digital object in a structured Web document, and the term "context integrity" refers to a sufficient number of appropriate semantic entities present with the protected digital object in the structured Web document to provide the authenticity of the structured Web document and fairness of using the digital object in the structured Web document.

Currently, in order to reduce the above-described types of cyber attacks, attempts have been made to provide education and training to people about such cyber attacks, such as misprinted words in uniform resource locators URLs, unreasonable requests for personal information, urgency of requests, etc., for example, by teaching people to identify appropriate cyber attack signs. The problem with this attempt is that most people are not educational enough to understand the training and not work. Further, such attempts require manual education and training and are prone to errors in identifying network attacks. Another attempt involves following a security guideline, such as checking the contents of any digital object and tracking the source of the digital object. However, such attempts require consciousness and intelligence of the person. Further attempts have included using URL evaluation services that maintain a blacklist of URLs and provide scoring of URLs according to user requirements. However, such URL evaluation services rely on user reports, which may miss problematic URLs. Furthermore, such URL evaluation services cannot cope with dynamically changing URLs. Further attempts have included using brand verification services to compare some digital objects, such as images of certain products, with samples of authentic products and report corresponding results to the user. However, such brand verification services employ third party operators and are only effective for counterfeit cases, not helpful in detecting other types of network attacks. Another attempt involves the use of systems associated with enhanced security policies that detect and attack suspected digital objects. However, such systems are only effective in the case of the business domain, and are ineffective against some of the types of cyber attacks mentioned above (such as false news and forgery). In general, existing attempts rely mostly on human cooperation, consciousness, intelligence and concentration, and are therefore prone to error. Therefore, there is a technical problem how to automate the network security method to eliminate the above-described type of network attack that affects people.

Accordingly, in view of the foregoing discussion, there is a need to overcome the aforementioned drawbacks associated with conventional network security approaches.

Disclosure of Invention

The present invention provides a method for associating a digital object with the content of a structured Web document. Furthermore, the present invention provides a method for evaluating the contextual integrity of digital objects in a structured Web document. As described above in the present disclosure, the term "context" refers to a plurality of semantic entities (objects, elements, attributes, etc.) included with a protected digital object in a structured Web document, and the term "context integrity" refers to a sufficient number of appropriate semantic entities present with the protected digital object in the structured Web document to provide authenticity of the structured Web document and fairness of using the digital object in the structured Web document. The present invention provides a solution to the existing problem of how to automate a network security method to eliminate network attacks of the type described above that affect humans. It is an object of the present invention to provide a solution that overcomes at least some of the problems encountered in the prior art and to provide an improved method for associating a digital object with the content of a structured Web document, and an improved method for assessing the contextual integrity of the digital object in the structured Web document to protect a user from improper or malicious use of the digital object in the structured Web page.

One or more of the objects of the invention are achieved by the solutions provided in the attached independent claims. Advantageous implementations of the invention are further defined in the dependent claims.

In one aspect, the present invention provides a method for associating a digital object with the content of a structured Web document. The method includes selecting a digital object to be protected in a structured Web document, calculating a watermark integration capacity of the selected digital object, creating a context-locked watermark for the selected digital object based on one or more verifiable elements of the content of the structured Web document such that the size of the context-locked watermark does not exceed the watermark integration capacity, and embedding the context-locked watermark into the selected digital object.

Preferably, the context-locked watermark is an invisible and powerful watermark that remains intact with the digital object in the event of any modification or manipulation of the digital object, e.g. in the event of resizing the image in which the watermark is embedded, cropping the image in which the watermark is embedded, etc. The advantage of this approach is that the manipulated digital objects, e.g. manipulated images, text files, video or audio files, are automatically detected by means of a context-locked watermark, thereby protecting the end user from appropriate cyber attacks, such as false news, fraud, imposter, phishing, etc. The improved method eliminates human error in identifying the manipulated digital object and facilitates the accuracy of detecting network attacks. Furthermore, the improved method is applicable to all types of digital objects, facilitating detection of manipulation for any type of digital object. The context-locked watermark created by the improved method facilitates verifying the authenticity and integrity of the context of the original digital object. The watermark integration capacity determined by the improved method indicates the limit to which a context-locked watermark can be added to a digital object, which is advantageous in preventing the quality of the digital object from being affected by the context-locked watermark. The context-locked watermark created by the improved method is hardly destroyed by any attacker with conventional skills, which is beneficial to maintaining the robustness of the context of the digital object. The method is used to associate the digital object with the content of the structured Web document by embedding a context-locked watermark embedded in the selected digital object. The method can be used to disclose new functionality by observing the appropriate evaluation flow and prompts to the end user, by detecting the appropriate watermark in the digital object, by checking the UI of the content editor, and by looking up advertisements for relevant functionality in the user manual of the content editor.

In one implementation, creating the context-locked watermark includes selecting one or more verifiable elements in the content of the structured Web document as anchors, assigning weights to each of the anchors to reflect the importance of the anchors, and encoding the selected anchors with the assigned weights into the context-locked watermark.

The one or more validation elements generated by the method act as a connection link between the digital object and the content of the structured Web document, facilitating determination of the actual source of information represented by the digital object.

In one implementation, the method includes determining weights to be assigned to each of the selected anchors based on one or more of the type of anchor, a predefined weighting algorithm, and user input such that the sum of the weights of all anchors is equal to a predefined full match value.

The weights assigned to the selected anchors facilitate determining the necessary anchors necessary to establish a connection between the digital object and the content of the structured Web document.

In another implementation, the method includes adding a start tag and a mismatch tolerance threshold (mismatch tolerance threshold, MTT) to the context-locked watermark, wherein the MTT is used to define an acceptable matching distance value between an anchor point encoded into the context-locked watermark of the digital object and content of a structured Web document that includes the digital object.

The start tag and mismatch tolerance threshold determine acceptable variations between the digital object and the content of the structured Web document, facilitating a determination of the allowable degree of mismatch between the digital object and the content of the structured Web document.

In one implementation, the method includes selecting watermarking techniques and/or watermarking parameters for creating a context-locked watermark based on one or more of watermark integration capacity, predefined security and robustness requirements, and user input.

The watermarking technique or watermarking parameters used in the improved method are advantageous for providing security and robustness for the context-locked watermark and preventing any impact on the quality of the digital object when adding the context-locked watermark.

In another implementation, the selected watermarking technique and/or watermarking parameters are used to create an invisible context-locked watermark that has the ability to accommodate modifications to digital objects.

The context-locked watermark is invisible and powerful to any attacker manipulating the digital object, is beneficial for maintaining the identity of the digital object, and can easily detect the manipulated digital object.

In another aspect, the present invention provides a method for evaluating the contextual integrity of digital objects in a structured Web document. The method includes detecting a context-locked watermark in a digital object embedded in a structured Web document, decoding one or more verifiable elements from the context-locked watermark, detecting one or more elements in the content of the structured Web document that are identical to the decoded verifiable elements, calculating a context match score for the digital object based on the number of detected elements that are identical to the decoded verifiable elements, and notifying a user that the digital object lacks context integrity if the context match score is less than a mismatch tolerance threshold.

The method advantageously provides for automatic assessment of any digital object during rendering of any structured web page and thereby provides an indication to a user as to whether any digital object on the structured web page is manipulated. The improved method is advantageous in reducing human error in assessing the authenticity of a digital object. The improved method is advantageous for identifying digital objects that provide false information, and the improved method provides alerts to users regarding such information. Furthermore, the improved method is applicable to all types of digital objects, facilitating manipulation in the case of any type of digital object. Further, the visual cues indicated in the improved method are advantageous for enabling all types of users to recognize manipulating digital objects, regardless of the technical knowledge of the user.

In one implementation, the method includes decoding a mismatch tolerance threshold from a context-locked watermark.

The mismatch tolerance threshold indicates an acceptable difference between the digital object and the content of the structured Web document, facilitating a determination of whether any digital object is manipulated and beyond an allowable range.

In one implementation, the method includes determining a manipulation correction factor based on a degree of manipulation of the digital object. Further, calculating the context match score includes multiplying the sum of the weights by a steering correction factor.

The manipulation correction factor indicates a degree of manipulation associated with any digital object and is beneficial for improving the accuracy of determining the manipulated digital object.

In another implementation, informing the user of the lack of contextual integrity of the digital object includes providing visual cues to the user in one or more of a color frame of a rendered image of the digital object, a specific label of the rendered image that covers the digital object, a bullet box bubble with warning text, and the like, when the structured Web document is rendered on the user device. Further, visual cues are automatically provided during rendering of the structured Web document or in response to user requests for assessing the contextual integrity of the digital object.

Visual cues are advantageous to provide a simple indication that the digital object lacks integrity so that any person without technical knowledge can implement an improved method on any browser.

A computing device for processing a digital object, the computing device for implementing a method for associating a digital object with content of a structured Web document.

The computing device achieves all the advantages and technical effects of the method of associating a digital object with the content of a structured Web document.

A user device for Web browsing, the user device having a digital object reliability assessment module for implementing a method for assessing the contextual integrity of digital objects in a structured Web document.

The user device achieves all the advantages and technical effects of a method of evaluating the contextual integrity of digital objects in a structured Web document.

It will be appreciated that all of the above implementations may be combined. It should be noted that all devices, elements, circuits, units and means described in the present application may be implemented in software or hardware elements or any kind of combination thereof. The steps performed by the various entities described in this disclosure, as well as the functions to be performed by the various entities described are intended to mean that the respective entities are adapted to, or are adapted to, perform the respective steps and functions. Even though in the following description of specific embodiments, the specific functions or steps to be performed by external entities are not reflected in the description of specific details of the entity performing the specific steps or functions, it should be clear to a skilled person that these methods and functions may be implemented in corresponding software or hardware elements or any kind of combination thereof. It will be appreciated that features of the application are susceptible to being combined in various combinations without departing from the scope of the application as defined by the accompanying claims.

Additional aspects, advantages, features and objects of the invention will become apparent from the accompanying drawings and detailed description of illustrative implementations which are explained in connection with the following appended claims.

Drawings

The foregoing summary, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention, there is shown in the drawings exemplary constructions of the invention. The invention is not limited to the specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will appreciate that the drawings are not drawn to scale. Wherever possible, like elements are designated by like numerals.

Embodiments of the invention will now be described, by way of example only, with reference to the following figures, in which:

FIG. 1 is a flow chart of a method for associating a digital object with the content of a structured Web document in accordance with an embodiment of the present invention;

FIG. 2 is a block diagram depicting a computing device for implementing a method for associating a digital object with content of a structured Web document, in accordance with an embodiment of the invention;

FIG. 3 is a flow chart of a method of content association or anchoring according to an embodiment of the present invention;

FIG. 4 is a flow chart of a method for evaluating the contextual integrity of digital objects in a structured Web document according to an embodiment of the present invention;

FIG. 5 is a block diagram depicting a user device for implementing a method for evaluating the contextual integrity of digital objects in a structured Web document, in accordance with an embodiment of the invention;

FIG. 6 is a flow chart of a context integrity assessment method in accordance with an embodiment of the present invention;

FIG. 7 is a flow chart of a method of inserting an invisible watermark in a multimedia digital object according to an embodiment of the invention;

Fig. 8 is a flow chart of a method of inserting an invisible watermark into an original image or a main image according to an embodiment of the present invention.

In the drawings, the underlined numbers are used to denote items where the underlined numbers are located or items adjacent to the underlined numbers. The non-underlined numbers relate to items identified by lines associating the non-underlined numbers with the items. When a number is not underlined and has an associated arrow, the number without the underline is used to identify the general item to which the arrow points.

Detailed Description

The following detailed description illustrates embodiments of the invention and the manner in which the embodiments may be implemented. While some modes for carrying out the invention have been disclosed, those skilled in the art will recognize that other embodiments for carrying out or practicing the invention may also exist.

FIG. 1 is a flow chart of a method of associating a digital object with the content of a structured Web document in accordance with an embodiment of the present invention. Referring to FIG. 1, a flow chart of a method 100 of associating a digital object with the content of a structured Web document is shown. The method 100 includes steps 102-108.

Method 100 involves associating a digital object with the content of a structured Web document. The method 100 is used in situations where any digital object is used to perform unscrupulous or illegal activities, such as propagating false news using a digital object that is not news related, forging products by manipulating the digital object, and so forth. Method 100 is used to verify the authenticity of these digital objects and identify any manipulated information that is disclosed through the use of these digital objects.

In step 102, method 100 includes selecting a digital object to be protected in a structured Web document. In one implementation, the structured Web document includes a Web page of a website or an online application, and is designed by implementing a well-defined structure using a markup language, such as hypertext markup language (hypertext markup language, HTML), extensible markup language, XML, rich text format, RTF, and the like. In one implementation, the digital object is a stand-alone element that appears as a basic part of the structured Web document. Examples of digital objects may include, but are not limited to, image files, video, audio, text files, and the like. In one implementation, a content owner or creator selects a digital object to be added to a structured Web document and protects it from cyber attacks.

In step 104, the method 100 includes calculating watermark integration capacity of the selected digital object. In one example, a watermark refers to information embedded in a digital object that associates the digital object with an original information source. In addition, the watermark integration capacity of a digital object refers to the maximum amount of information that can be embedded as a watermark into the digital object without significantly affecting the quality of the digital object. In one implementation, the content owner or device of the structured Web document calculates watermark integration capacity by processing the digital object. The watermark integration capacity of a digital object depends on a number of factors, including the size of the selected digital object, the complexity of the watermark, and the file format of the selected digital object. In one example, the watermark integration capacity of the digital object is obtained based on the size or format of the selected digital object. In another example, the watermark integration capacity of the digital object is obtained based on the size and format of the selected digital object.

In step 106, the method 100 includes creating a context-locked watermark for the selected digital object based on one or more verifiable elements of the content of the structured Web document such that the size of the context-locked watermark does not exceed the watermark integration capacity. In one implementation, the context-locked watermark is a watermark that is an indication of originality of the digital object. In one example, the context-locked watermark is a proof of the context of the selected digital object. In another implementation, the context of a digital object refers to surrounding information about the digital object, such as information about the creation, location, use, and purpose of the digital object. In one example, for a selected digital object, such as an image, context refers to file format, size, resolution, image subject, date and time the image was taken, and so forth. In addition, the context-locking watermark locks the context of the digital object with the corresponding digital object and maintains the identity of the selected digital object in the structured Web document.

According to one embodiment, creating a context-locked watermark includes selecting one or more verifiable elements in the content of a structured Web document as anchors, assigning weights to each of the anchors to reflect the importance of the anchors, and encoding the selected anchors with the assigned weights into the context-locked watermark. Examples of anchors may include, but are not limited to, original page URLs, co-located references, page and/or image titles, basic words and/or phrases in related text. In one example, a certain number of anchors, e.g., page URLs, picture titles, etc., are automatically selected, and the content owner adds additional anchors, e.g., URLs of text, other digital objects, etc., to the context-locked watermark. One or more verifiable elements or anchors are used to establish a relationship of the digital object to the content of the structured Web document. The digital object is identified as originating from the structured Web document by one or more verifiable elements or anchors. For example, the digital object is an image and the verifiable element is a URL of a page displaying the image. In this case, if the digital object is used for any other Web document, the verifiable element indicates the original location and context of the digital object, facilitating identification of the authenticity of the information disclosed using such digital object. An anchor point for a context-locked watermark for any digital object is determined based on the watermark integration capacity of the corresponding digital object. In one implementation, the weight is a numerical value that is assigned to each anchor point based on the importance of the corresponding anchor point. In one implementation, the most important anchor points (i.e., the basic anchor points) are assigned higher weights, while less important anchor points (i.e., optional additional items) are assigned less weights. According to one embodiment, each verifiable element of the one or more verifiable elements is selected from the content of the structured Web document based on a predefined selection algorithm and/or user input. In one implementation, the predefined selection algorithm is a mathematical process that selects one or more verifiable elements. In another implementation, one or more verifiable elements are determined based on input from a user or content owner. One or more verifiable elements establish a connection link between the content of the structured Web document and the digital object through the context-locked watermark. For example, when any digital object is to test the authenticity of any other Web document, one or more verifiable elements or anchors in the context-locked watermark of the corresponding digital object act as fingerprints of the content of the structured Web document.

According to one embodiment, the method 100 further includes determining a type of each of the selected anchors and encoding the type of the selected anchor into the context-locked watermark. In one implementation, the type of anchor is the data type of the corresponding anchor. In one example, the digital object is an article on a web site. In such an example, the anchor point is the title of the article. Here, the article titles appear in text form. Thus, the type of anchor is "text". Exemplary table 1 shows anchor points, types, and weights, as follows:

TABLE 1

Anchor point	Type(s)	Weighting of
			Page URL	URL	0.5
Website owner	XRef	0.15
			Article title	Text of	0.2
Key phrase 1	Text of	0.15

According to table 1, the anchor "page URL" has the highest weight, i.e., 0.5. Thus, the anchor "page URL" has the highest importance in the context-locked watermark. In one example, in the case of processing an image, the URL of the web page to which the corresponding image belongs is considered to be the most important factor in determining the authenticity of the image because the weight is highest. In one implementation, the content owner assigns a weight to each anchor point. In such implementations, the content owner or editor uses the weights to specify more important and less important context elements. After each anchor point is assigned a weight, the selected anchor point is embedded into the context-locked watermark along with the assigned weight.

According to one embodiment, the method 100 further includes determining the weights to be assigned to each selected anchor point based on one or more of the anchor point type, a predefined weighting algorithm, and user input such that the sum of the weights of all anchor points is equal to a predefined full match value. In one example, the predefined weight algorithm is a mathematical process that calculates weights to be assigned to anchor points. In another example, the user input includes a weight of the anchor point determined by the content owner. The content owner determines the weight based on the degree of importance of the determined anchor point in the context-locked watermark. The weights for each anchor point are added until the value of the sum of the weights reaches a predefined complete match value. In one implementation, a full match value refers to a weight limit that may be assigned to an anchor point in a context-locked watermark. In one implementation, each anchor point matches a predefined template and contributes a predefined complete match value to the overall match accumulator.

According to one embodiment, the method 100 further includes adding a start marker and a mismatch tolerance threshold (mismatch tolerance threshold, MTT) to the context-locked watermark, wherein the MTT is used to define an acceptable matching distance value between an anchor point encoded into the context-locked watermark of the digital object and content of a structured Web document that includes the digital object. In one implementation, the start marker is an identifiable bit pattern, such as a particular technology, patch size, etc., that supports bit frame alignment and context-locked watermark parameter encoding. In one embodiment, the start marker evaluates the degree of manipulation of the digital object. The mismatch tolerance threshold defines a mismatch limit between an anchor point encoded into the context-locked watermark of the digital object and the content of the structured Web document that includes the digital object. The acceptable match distance value depends on the low, medium and high context mismatch. The start tag and mismatch tolerance threshold (mismatch tolerance threshold, MTT) are used to improve the control and accuracy of creating the context-locked watermark. The start marker is used to define the exact starting point of the context-locked watermark, ensuring that the detection process starts only from the correct position of the context-locked watermark. Similarly, MTT is used to define acceptable matching distance values between anchors encoded into a context-locked watermark and the content of a structured Web document. MTT can also prevent false positives because it requires a level of context-locked watermarking to exist between the content before detection is considered valid.

According to one embodiment, the method 100 includes selecting watermarking techniques and/or watermarking parameters for creating a context-locked watermark based on one or more of watermark integration capacity, predefined security and robustness requirements, and user input. In other words, the context-locked watermarking to be embedded into the digital object is performed by watermarking techniques and/or watermarking parameters. In one implementation, the watermarking technique is a statistical watermarking technique. The content owner selects a watermarking technique for any digital object based on the watermark integration capability of the corresponding digital object. Watermarking techniques add context-locking watermarks to digital objects without affecting the quality and robustness of the digital objects. According to one embodiment, the selected watermarking technique and/or watermarking parameters are used to create an invisible context-locked watermark having an adaptation capability to modifications to the digital object. The context-locked watermark created by the watermarking technique remains intact with the digital object in the event of any modification or manipulation of the digital object, thereby distinguishing between the modified digital object and the original digital object. In one implementation, the watermark parameters are watermark-based image statistics parameters, such as spectral coding, etc. The size and quality of the digital object, the watermarking technique and watermarking parameters have a significant impact on the amount of information that can be embedded as a watermark.

In step 108, the method 100 includes embedding a context-locked watermark into the selected digital object. In one example, a digital object (e.g., an image) is selected to prevent manipulation prior to addition to a structured Web document. Further, a context-locked watermark is created by selecting one or more verifiable elements from the content of the structured Web document. One or more verifiable elements are selected as anchor points and a weight is assigned to each anchor point. Further, an anchor point is embedded into the context-locked watermark. Furthermore, a context-locked watermark is embedded into the digital object along with the selected anchor point. The digital object is further added to the structured Web document along with the context-locked watermark. The context-locked watermark serves as a fingerprint or identifier of the digital object context. The presence of a context-locked watermark is necessary in order to determine the authenticity and integrity of the digital object. Furthermore, if no context-locked watermark is present in the digital object, the digital object is considered to have been manipulated or reused. Thereby protecting the user or person from manipulated information disclosed by such digital objects.

The method 100 has the advantage that the manipulated digital objects, such as manipulated images, text files, video or audio files, are automatically detected by means of a context-locked watermark, thereby protecting the end user from suitable cyber attacks, such as false news, fraud, imposter, phishing, etc. The method 100 eliminates human error in identifying manipulated digital objects, facilitating the accuracy of detecting network attacks. Furthermore, method 100 is applicable to all types of digital objects, facilitating detection of manipulation for any type of digital object. The context-locked watermark embedded in the selected digital object facilitates protecting and verifying the authenticity and integrity of the context of the original digital object in the structured Web document. The watermark integration capacity determined by the method 100 indicates the limit to which a context-locked watermark can be embedded in a digital object, which is advantageous in preventing the quality of the digital object from being affected by the context-locked watermark. The context-locked watermark created by the method 100 is hardly destroyed by any attacker with conventional skills, which is advantageous to preserve the robustness of the context of the digital object. Method 100 is used to associate a digital object with the content of a structured Web document by embedding a context-locked watermark embedded in the selected digital object. The method 100 may be used to disclose new functionality by observing the appropriate evaluation flow and prompts to the end user, by detecting the appropriate watermark in the digital object, by checking the UI of the content editor, and by looking up advertisements for relevant functionality in the user manual of the content editor.

FIG. 2 is a block diagram depicting a computing device for implementing a method for associating a digital object with content of a structured Web document, in accordance with an embodiment of the invention. Referring to FIG. 2, a computing device 202 is shown for implementing the method 100 (in FIG. 1) for associating a digital object with content of a structured Web document.

Computing device 202 is used to process one or more digital objects. Further, the computing device is operable to implement method 100 by associating a digital object with the content of the structured Web document. In one implementation, the computing device 202 includes a first controller 204, a first communication interface 206, and a first memory 208. First controller 204 is operative to process one or more digital objects received via first communication interface 206 by associating the one or more digital objects with the content of the structured Web document. Examples of implementations of the first controller 204 may include, but are not limited to, a central data processing device, a microprocessor, a microcontroller, a complex instruction set computing (complex instruction set computing, CISC) processor, an application-specific integrated circuit (ASIC) processor, a reduced instruction set (reduced instruction set, RISC) processor, a very long instruction word (very long instruction word, VLIW) processor, a state machine, and other processors or control circuits. Examples of implementations of the first communication interface 206 may include, but are not limited to, a network interface, a computer port, a network socket, a network interface controller (network interface controller, NIC), and any other network interface device. In addition, the first memory 208 is used to store digital objects processed by the first controller 204. Examples of implementations of the first Memory 208 may include, but are not limited to, electrically Erasable Programmable Read Only Memory (EEPROM), dynamic Random Access Memory (DRAM), random Access Memory (Random Access Memory, RAM), read Only Memory (ROM), hard disk drive (HARD DISK DRIVE, HDD), flash Memory, secure Digital (SD) card, solid state drive (Solid-STATE DRIVE, SSD), and/or CPU cache Memory.

In operation, computing device 202 is used to select a digital object to be protected in a structured Web document. Examples of digital objects may include, but are not limited to, images, video, audio, text, and the like. In addition, the computing device 202 is configured to calculate watermark integration capacity for the selected object. In one implementation, the watermark integration capacity of a digital object refers to the maximum amount of information that can be embedded into the digital object as a watermark without significantly affecting the quality of the digital object. Further, the computing device 202 is configured to create a context-locked watermark for the selected digital object based on one or more verifiable elements of the content of the structured Web document such that the size of the context-locked watermark does not exceed the watermark integration capacity. According to one embodiment, the computing device 202 is configured to select one or more verifiable elements in the content of the structured Web document as anchor points while creating the context-locked watermark. The computing device 202 is also operable to assign weights to each of the anchors based on the importance of each anchor and encode the selected anchor along with the weights into the context-locked watermark. According to one embodiment, the computing device 202 is configured to select each of one or more verifiable elements from the content of the structured Web document based on a predefined selection algorithm and/or user input.

According to one embodiment, the computing device 202 is configured to determine a type of each of the selected anchors and encode the type of the selected anchor into the context-locked watermark. According to another embodiment, the computing device 202 is operable to determine the weight to be assigned to each of the selected anchors based on one or more of the type of anchor, a predefined weighting algorithm, and user input received through the first communication interface 206. Weights are assigned to the selected anchors such that the sum of the weights of all anchors is equal to a predefined value. After adding the anchor point with the weight to the context-locked watermark, the computing device 202 is also used to add a start marker and a mismatch tolerance threshold (mismatch tolerance threshold, MTT) to the context-locked watermark. The start tag and MTT are used to define acceptable match distance values between an anchor point encoded into a context-locked watermark of a digital object and the content of a structured Web document that includes the digital object. According to one embodiment, the computing device 202 is configured to select watermarking techniques and/or watermarking parameters for creating a context-locked watermark based on one or more of watermark integration capacity, predefined security, robustness requirements of the context-locked watermark, and user input received through the first communication interface 206. According to one embodiment, the computing device 202 is configured to select a watermarking technique and/or watermarking parameter, wherein the selected watermarking technique and/or watermarking parameter is used to create an invisible context-locked watermark having an adaptation capability for modification of digital objects. In addition, the computing device 202 is configured to embed a context-locked watermark into the selected digital object. Computing device 202 achieves all the advantages and technical effects of method 100 of associating a digital object with the content of a structured Web document.

Fig. 3 is a flow chart of a method of content association or anchoring according to an embodiment of the present invention. Fig. 3 is described in connection with the elements of fig. 1 and 2. Referring to fig. 3, a flow chart of a method 300 of content association or anchoring is shown. The method 300 includes steps 302 through 316.

In one implementation, the method 300 of content association or anchoring begins at step 302. In step 304, method 300 includes selecting a digital object to be protected in a structured Web document. In step 306, the method 300 includes calculating watermark (WATERMARKING, WM) capacity of the selected digital object. In one implementation, in step 308, the method 300 includes prompting the content owner for watermark integration capability, and based on the watermark integration capability, the content owner performs the steps in the method 300. In step 310, method 300 includes selecting an anchor in the content of the structured Web document. In step 312, the method includes assigning a weight to each of the selected anchors. Further, in step 314, the method 300 includes adding the selected anchor point to the context lock watermark along with the assigned weight. Steps 310, 312 and 314 are repeated until the watermark integration capacity is not exceeded. When the anchor point added to the context-locked watermark exceeds the watermark integration capacity, the method 300 performs step 316, which includes adding the context-locked watermark to the digital object, such as an image. The method 300 of content association or anchoring ends at step 318.

FIG. 4 is a flow chart of a method of evaluating the contextual integrity of digital objects in a structured Web document, according to an embodiment of the present invention. Fig. 4 is described in connection with the elements of fig. 1, 2 and 3. Referring to FIG. 4, a flow chart of a method 400 of evaluating the contextual integrity of digital objects in a structured Web document is shown. Method 400 includes steps 402 through 410.

Method 400 includes determining the contextual integrity of any digital object in a structured Web document. Context integrity refers to the authenticity or certainty of the context of an object. During any network attack, the digital objects in the structured Web document are manipulated and disseminated with false information or sent by an attacker to send spam, the context integrity is compromised. The contextual integrity of any digital object is assessed by the method 400, preventing a person from being affected by such spurious information by manipulating the digital object. In one embodiment, method 400 is automatically initiated by a browser that loads a structured Web document as the structured Web document is rendered. In another embodiment, the method 400 is performed in response to a request from a user to use a browser, such as through a shortcut command or a menu command.

In step 402, method 400 includes detecting a context-locked watermark embedded in a digital object in a structured Web document. Examples of digital objects may include, but are not limited to, images, video files, audio files, text files, and the like. In one embodiment, the context-locked watermark is a watermark that maintains the context of digital objects in a structured Web document. In one embodiment, a context-locked watermark is created by method 100 (of FIG. 1) to protect digital objects in a structured Web document.

In step 404, the method 400 includes decoding one or more verifiable elements from the context-locked watermark. In one implementation, one or more verifiable elements from the context-locked watermark are connection links between the content of the structured Web document and the digital objects. Examples of one or more verifiable elements may include, but are not limited to, page URLs, detailed information of the structured Web document owners, article titles on the structured Web document, key phrases, and the like. According to one embodiment, method 400 includes decoding the weights and types of each decoded verifiable element. In one implementation, the weight of one or more verifiable elements is a value assigned to each verifiable element based on the importance level of the corresponding verifiable element. In one implementation, the type of verifiable element is metadata of the verifiable element. For example, the digital object is an "article" on a website and the verifiable element is a "title of the article", then the type of verifiable element is text (because the title is made up of text). According to one embodiment, the method 400 includes decoding a mismatch tolerance threshold from the context-locked watermark. In one implementation, the mismatch tolerance threshold defines a mismatch limit between one or more verifiable elements encoded in a context-locked watermark of a digital object and content of a structured Web document that includes the corresponding digital object. In one implementation, the context-locked watermark includes three parts, a start tag, an anchor packet, and a mismatch threshold tolerance (mismatch threshold tolerance, MTT). An anchor package is a collection of anchors that are embedded into a context-locked watermark by a predefined watermarking technique.

In step 406, the method 400 further includes detecting one or more elements in the content of the structured Web document that are identical to the decoded verifiable elements. The decoded verifiable element indicates the source of the digital object. In step 406, method 400 detects whether any elements of the same origin as the digital object are found in the content of the structured Web document. According to one embodiment, the method 100 includes determining a manipulation correction factor based on a degree of manipulation of the digital object. The manipulation correction factor is a value indicative of the degree of manipulation of the digital object. Manipulation correction factors reflect a decrease in reliability in manipulating a digital object. In other words, the value of the manipulation correction factor decreases as the manipulation of the digital object increases. In one implementation, the manipulation correction factor is used to match the trust adjustment of the digital object.

In step 408, method 400 includes calculating a context match score for the digital object based on the detected number of elements that is the same as the decoded verifiable element. The context matching score is a numerical value representing the authenticity of the digital object in the structured Web document. According to one embodiment, the method 400 further includes calculating a context match score by summing weights of the decoded verifiable elements of the same element detected in the content of the structured Web document. In one example, the decoded verifiable element is found in the content of the structured Web document, such as a page URL with a weight value of 0.5, a key phrase associated with the selected digital object with a weight value of 0.15, and so on. The method 400 also includes adding the weights of these decoded verifiable elements, such as Σwi=0.15+0.5=2.0. Furthermore, calculating the context match score by the method 100 further includes multiplying the sum of the weights by a steering correction factor. In one implementation, the context match score is calculated as follows:

Where ms=context match score, mcf=steering modifier, ai=value of anchor i, ti=reference template of anchor i, wi=weight of anchor. In one example, the reference template for the anchor or verifiable element is a template that does not require any action to indicate the anchor. In one implementation, a decrease in the value of the context matching score indicates a decrease in the robustness of the context-locked watermark.

In step 410, method 400 includes notifying a user of a lack of context integrity of the digital object if the context match score is less than a mismatch tolerance threshold. A low value of the context matching score represents a change in the context of the digital object from the original digital object in the structured Web document. Further, if the value of the context match score is equal to or greater than the mismatch tolerance threshold, the digital object is original (i.e., less, or not manipulated or reused). According to one embodiment, the method 400 further includes providing a visual cue to a user when rendering the structured Web document on the user device in the form of one or more of a rendered color frame surrounding the digital object, a rendered specific label overlaying the digital object, a bullet bubble with alert text, and the like. Further, visual cues are automatically provided during rendering of the structured Web document or in response to user requests for assessing the contextual integrity of the digital object. In other words, if the value of the context match score is less than the mismatch tolerance threshold, method 400 notifies a user operating a browser that loads a structured Web document of the lack of integrity information about the digital object. The information is provided to the user in the form of visual cues. Visual cues include displaying a color box around a digital object that indicates that the corresponding digital object is out of the context of a structured Web document. In one example, the particular label overlaying the rendering of the digital object may include text overlaid on the digital object or an emoticon integrated with the digital object. In addition, a box bubble representing a warning message is displayed on the structured Web document. In one implementation, the visual cues are automatically displayed on the web page or upon request by a user to operate the browser. In one implementation, the type of visual cues varies according to the user's profile. For example, for adult users, the visual cues are displayed as text, while for minors or children, the visual cues are displayed as color emoticons to provide a warning to the user.

Method 400 facilitates providing an automatic assessment of any digital object during rendering of any web page and thereby providing an indication to a user as to whether any digital object on the web page is manipulated. Method 400 reduces human error in assessing the authenticity of a digital object. Method 400 identifies digital objects that provide false information and provides alerts to the user regarding such information. Furthermore, method 400 is applicable to all types of digital objects. Further, the visual cues indicated in method 400 facilitate enabling all types of users to identify manipulating digital objects, regardless of the user's technical knowledge. Method 400 facilitates allowing structured Web documents to be appropriately forwarded and modified while maintaining an exact degree of digital object context.

FIG. 5 is a block diagram of a user device describing a method of now evaluating the contextual integrity of digital objects in a structured Web document, according to an embodiment of the present invention. Fig. 5 is described in connection with the elements of fig. 1,2,3 and 4. Referring to FIG. 5, a block diagram 500 depicting a user device 502 for Web browsing is shown, including a digital object reliability evaluation module 504 for implementing the method 400 (FIG. 4) of evaluating the contextual integrity of digital objects in a structured Web document.

In one implementation, the user device 502 includes a second controller 506, a second communication interface 508, and a second memory 510. In one implementation, digital object trust evaluation module 504 is configured with a second controller 506. In one implementation, the mismatch tolerance threshold is specified by the content owner and the acceptable match distance value in method 400 is checked by digital object trustworthiness assessment module 504. In one implementation, digital object trust evaluation module 504 is installed in an end user device that evaluates structured Web documents (i.e., browser plug-ins) to support automatic or manual evaluation of the context of a digital object. Digital object reliability evaluation module 504 is used to implement method 400 of evaluating the contextual integrity of digital objects in a structured Web document.

A second controller 506 is used to process one or more digital objects from the content of the structured Web document. In one implementation, processing of the digital object by the second controller 506 occurs automatically during rendering of the structured Web document or by user input received from the second communication interface 508. Examples of implementations of the second controller 506 may include, but are not limited to, a central data processing device, a microprocessor, a microcontroller, a complex instruction set computing (complex instruction set computing, CISC) processor, an application-specific integrated circuit (ASIC) processor, a reduced instruction set (reduced instruction set, RISC) processor, a very long instruction word (very long instruction word, VLIW) processor, a state machine, and other processors or control circuits. Examples of implementations of the second communication interface 508 may include, but are not limited to, a network interface, a computer port, a network socket, a network interface controller (network interface controller, NIC), and any other network interface device. In addition, second memory 510 is used to store data regarding the execution of the evaluation of the digital object by digital object trust evaluation module 504 via second controller 506. Examples of implementations of the second Memory 510 may include, but are not limited to, electrically erasable programmable Read-Only Memory (EEPROM), dynamic Random-Access Memory (DRAM), random-Access Memory (Random Access Memory, RAM), read-Only Memory (ROM), hard disk drive (HARD DISK DRIVE, HDD), flash Memory, secure Digital (SD) card, solid-state drive (Solid-STATE DRIVE, SSD), and/or CPU cache Memory.

In one implementation, user device 502 detects a context-locked watermark embedded in a digital object in a structured Web document. Further, the user device 502 decodes one or more verifiable elements from the context-locked watermark. According to one embodiment, the user device 502 decodes the weight and type of each decoded verifiable element from the context-locked watermark. According to one embodiment, the user equipment 502 decodes the mismatch tolerance threshold from the context-locked watermark.

In addition, the user device 502 detects one or more elements in the content of the structured Web document that are the same as the decoded verifiable elements. Further, the user device 502 determines a manipulation correction factor based on the degree of manipulation of the digital object. Based on the weights and manipulation correction factors of the decoded verifiable elements, user device 502 calculates a context matching score for the digital object based on the number of detected elements that are the same as the decoded verifiable elements. According to one embodiment, the user device 502 calculates the context match score by summing weights of decoded verifiable elements of the same element detected in the content of the structured Web document. According to one embodiment, the user device 502 multiplies the sum of the weights of the decoded verifiable elements with the steering correction factor to calculate a context match score. After calculating the context match score, if the context match score is less than the mismatch tolerance threshold, user device 502 notifies a user operating user device 502 that the digital object lacks context integrity. According to one embodiment, user device 502 notifies the user of the lack of contextual integrity of the digital object by providing visual cues to the user when rendering a structured Web document on user device 502 in the form of one or more of a rendered color frame surrounding the digital object, a rendered specific label overlaying the digital object, a box bubble with warning text, and the like. Further, user device 502 automatically provides visual cues during rendering of the structured Web document or in response to user requests for assessing the contextual integrity of the digital object. User device 502 achieves all the advantages and technical effects of method 400 of evaluating the contextual integrity of digital objects in a structured Web document.

FIG. 6 is a flow chart of a context integrity assessment method in accordance with an embodiment of the present invention. Fig. 6 is described in connection with the elements of fig. 4 and 5. Referring to FIG. 6, a flow chart of a method 600 of context integrity assessment is shown. The method 600 includes steps 602 through 618.

In one implementation, in step 602, the method 600 begins rendering a structured Web document. In step 604, method 600 includes detecting a context-locked watermark in a digital object in the content of a structured Web document. In one implementation, the method 600 includes detecting, by a watermark decoding engine, a start marker in a context-locked watermark. In the event that a start marker is found, method 600 performs step 606, which includes calculating a maneuver correction factor. The manipulation correction factors indicate the integrity, quality, and robustness degree of the context-locked watermark. The low robustness of the watermark reduces the value of the steering correction factor. In step 608, method 600 includes creating reference templates for all anchors in the context-locked watermark. In step 610, method 600 includes finding an anchor in a structured Web document. In the event that an anchor is found, method 600 performs step 612, which includes matching the anchor with the reference template and calculating a context match score. Further, in step 614, the method 600 includes comparing the contextual matching score to a mismatch tolerance threshold. In one implementation, the comparison between the context match score and the mismatch tolerance threshold is performed by using matching techniques such as fuzzy string comparison, and combinations of different factors (i.e., a strict match for the base factor and a loose match for the additional factor). Further, if the value of the context match score is less than the mismatch tolerance threshold, the digital object lacks context integrity, and method 600 proceeds to step 616, which includes adding a visual cue to indicate that the digital object lacks context integrity. Further, in step 618, the method 600 includes conventional rendering of the structured Web document. However, if the context match score is greater than the mismatch tolerance threshold, step 618 continues with step 614, which is performing conventional rendering of the structured Web document without adding visual cues.

Fig. 7 is a flow chart describing a method of inserting an invisible watermark in a multimedia digital object according to an embodiment of the invention. Fig. 7 is described in conjunction with the elements of fig. 1, 2, 3,4, 5, and 6. Referring to fig. 7, a flow chart of a method 700 of inserting an invisible watermark in a multimedia digital object is shown. Method 700 includes steps 702 through 720.

In step 702, method 700 includes receiving host multimedia 704 to perform perceptually important block segmentation. During block segmentation, the host multimedia 704 is segmented into a plurality of embedded blocks, and a discrete cosine transform (discrete cosine transform, DCT) is applied to each block. In one implementation, watermark encoding is based on watermark driven block modification, i.e., bit values are encoded as statistical differences between two or more adjacent blocks of host multimedia 704. Further, in step 706, method 700 includes converting host multimedia 704 to grayscale multimedia. In step 708, method 700 includes submitting the grayscale host multimedia to an image statistics generator, and method 700 further includes receiving a plurality of keys 716. In one implementation, the image statistics generator uses statistical measures of the embedded regions of the host multimedia 704 to make imperceptible modifications as well as detectable modifications. In step 710, method 700 includes forming a composite image based on an image statistics generator. Further, in step 712, method 700 includes creating a watermark for host multimedia 704 by receiving watermark 714 and plurality of keys 716. In step 718, method 700 includes generating a composite watermark. Further, in step 720, watermark 714 is added to host multimedia 704 to generate watermarked multimedia 722. An advantage of statistical watermarking is that the statistical watermark is difficult to remove from the watermarked multimedia 722. With statistical watermarking, spectral differences between embedded regions of the watermarked multimedia 722 are preserved as brightness, contrast, and spectrum are changed in the watermarked multimedia 722. Statistical watermarking is capable of embedding multiple copies of watermark 714 and uses a relatively small embedded area that can withstand cropping and rotation operations. During statistical watermarking, encoding the original spectral information into watermark 714 facilitates evaluating the authenticity of host multimedia 704, regardless of whether the host multimedia is manipulated.

Fig. 8 is a flow chart of a method of inserting an invisible watermark into an original image or a main image according to an embodiment of the present invention. Fig. 8 is described in conjunction with the elements of fig. 1, 2, 3,4, 5, 6, and 7. Referring to fig. 8, a method 800 of inserting an invisible watermark into a host image (or original image) (I) 802 is shown. Method 800 includes steps 804 through 822.

In step 804, method 800 includes computing a block discrete cosine transform (discrete cosine transform, DCT) from the main image 802. In step 806, the method 800 includes calculating a perceptual metric (χ) of all sub-images of the main image 802. Further, in step 808, method 800 includes determining an appropriate sub-image from all sub-images of main image 802. In step 810, the method 800 includes generating a DCT domain composite image from an appropriate sub-image of the main image 802. In one implementation, step 810 includes receiving a seed key 812 to generate a DCT domain composite image. In step 814, method 800 includes creating a composite watermark image. In one implementation, in step 814, the method 800 includes receiving a block DCT calculated from a watermark identification (W) 816, a first scaling factor (alpha _kβ_k) 818, and a second seed key 820. In step 822, method 800 includes inserting watermark identification 816 to form watermarked image 824. In one implementation, in step 822, the method 800 includes receiving a pseudo-seed key 826 and generating a pseudo-random (1, -1) bit pattern 828. In another implementation, in step 822, the method 800 includes receiving a second scaling factor (α _i,j,k) to generate a watermarked image 824.

Modifications may be made to the embodiments of the invention described above without departing from the scope of the invention, as defined in the accompanying claims. Expressions such as "comprising," "including," "incorporating," "being/being" and the like used to describe and claim the present invention are intended to be interpreted in a non-exclusive manner, i.e. to allow items, components or elements not explicitly described to exist as well. Reference to the singular is also to be construed to relate to the plural. The word "exemplary" is used herein to mean "serving as an example, instance, or illustration. Any embodiment described as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments, or as excluding combinations of features of other embodiments. The word "optionally" as used herein means "provided in some embodiments and not provided in other embodiments. It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the disclosure that are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable combination or as any other described embodiment of the disclosure.

Claims

1. A method (100) for associating a digital object with the content of a structured Web document, the method (100) comprising:

selecting a digital object to be protected in the structured Web document;

calculating watermark integration capacity of the selected digital object;

Creating a context-locked watermark for the selected digital object based on one or more verifiable elements of the content of the structured Web document such that the size of the context-locked watermark does not exceed the watermark integration capacity;

The context-locked watermark is embedded into the selected digital object.

2. The method (100) of claim 1, wherein the creating a context-locked watermark comprises:

Selecting one or more verifiable elements as anchor points in the content of the structured Web document;

Assigning a weight to each of the anchors to reflect the importance of the anchor;

the selected anchor points with assigned weights are encoded into the context-locked watermark.

3. The method (100) of claim 2, further comprising:

A type of each of the selected anchors is determined and the type of the selected anchor is encoded into the context-locked watermark.

4. A method (100) according to claim 2 or 3, further comprising:

The weight to be assigned to each of the selected anchors is determined based on one or more of the type of anchor, a predefined weighting algorithm, and user input such that the sum of the weights of all anchors is equal to a predefined full match value.

5. The method (100) according to any one of claims 2 to 4, further comprising:

A start marker and a mismatch tolerance threshold (mismatch tolerance threshold, MTT) are added to the context-locked watermark, wherein the MTT is used to define an acceptable matching distance value between the anchor point encoded into the context-locked watermark of the digital object and the content of a structured Web document comprising the digital object.

6. The method (100) of any one of claims 1 to 5, wherein each verifiable element of the one or more verifiable elements is selected from the content of the structured Web document based on a predefined selection algorithm and/or user input.

7. The method (100) according to any one of claims 1 to 6, further comprising:

the watermarking technique and/or watermarking parameters used to create the context-locked watermark are selected in accordance with one or more of the watermarking integration capacity, predefined security and robustness requirements, and user input.

8. The method (100) of claim 7, wherein the selected watermarking technique and/or watermarking parameter is used to create an invisible context-locked watermark having an adaptation capability to modifications to digital objects.

9. A method (400) for evaluating the contextual integrity of a digital object in a structured Web document, the method (400) comprising:

detecting a context-locked watermark embedded in a digital object in a structured Web document;

decoding one or more verifiable elements from the context-locked watermark;

detecting one or more elements in the content of the structured Web document that are identical to the decoded verifiable element;

calculating a context match score for the digital object based on the number of detected elements that are the same as the decoded verifiable element;

If the context match score is less than a mismatch tolerance threshold, notifying a user that the digital object lacks the context integrity.

10. The method (400) of claim 9, further comprising decoding the mismatch tolerance threshold from the context-locked watermark.

11. The method (400) according to claim 9 or 10, further comprising:

decoding the weight and type of each of the decoded verifiable elements from the context-locked watermark,

Wherein the computing a context match score includes summing the weights of the decoded verifiable elements for which the same element has been detected in the content of the structured Web document.

12. The method (400) of claim 11, further comprising:

A manipulation correction factor is determined based on a degree of manipulation of the digital object,

Wherein the calculating the context match score further comprises multiplying the sum of the weights with the steering correction factor.

13. The method (400) of any of claims 9 to 12, wherein notifying the user of the lack of contextual integrity of the digital object comprises providing visual cues to the user in one or more of a color frame of a rendering of the digital object, a particular label of the rendering of the digital object overlaying the rendering, a box bubble with warning text, and the like, when the structured Web document is rendered on a user device,

Wherein the visual cue is automatically provided during rendering of the structured Web document or in response to a user request to evaluate the contextual integrity of the digital object.

14. A computing device (302) for processing a digital object, characterized in that the computing device (302) is configured to implement the method (100) for associating a digital object with the content of a structured Web document according to any of claims 1 to 8.

15. A user device (502) for Web browsing, characterized in that the user device (502) has a digital object reliability assessment module (504), wherein the digital object reliability assessment module (504) is adapted to implement the method (400) for assessing the contextual integrity of digital objects in a structured Web document according to any of claims 9 to 13.