Data processing device and data processing method

Abstract

A data processing device includes an input unit configured to receive a request for a document, wherein the request specifies at least one PII element associated with a first subject. Further, the data processing device also includes an identification unit configured to identify one or more PII elements in the requested document; a lookup unit configured to search a database for each identified PII element to link identified PII elements associated with the same subject. In addition, the data processing device includes an redaction unit configured to redact the document to obfuscate one or more identified PII elements that are not linked with the specified PII element; and an output unit configured to output the redacted document. The data processing device ensures data privacy by obfuscating data that is not associated with the first subject, further making the data processing device compliant with data privacy regulations and compliance.

Description

Technical Field

[0001] This disclosure generally relates to the fields of compliance and data management systems, and more specifically, to a data processing device and a computer-implemented data processing method. Background Technology

[0002] Typically, different organizations need to maintain data related to multiple entities, customers, and prospects. Furthermore, this data may be distributed across different storage systems and tiers, making the extraction of information about specific entities complex, time-consuming, and sometimes requiring manual intervention. Traditionally, metadata is stored by the organization to preserve data related to multiple entities. Metadata allows for the retrieval of information about entities to respond to regulatory queries. For example, a request from an individual entity can provide access to all personal information about that individual entity stored by the organization, or access to the organization's forced erasure of all personal information about that individual entity. However, in this scenario, data continuously flows into different storage systems, necessitating constant indexing of the information. This means that establishing connections between different information in different storage systems related to the same entity is a challenging task.

[0003] In some scenarios, during the entity registration process, multiple documents need to be sent from an entity to an organization, and these documents need to be linked to the same entity. Moreover, these documents do not reside in the same file, or even the same storage system, and are updated over time along with the entity's information. For example, the entity's contact information might be stored in a customer database, and payment details in a financial database. However, in such scenarios, the data is not always structured, and even in structured data, associating data items is not a simple task. For example, a car insurance claim has detailed information about both drivers, and the driver's license details are provided as copies of both drivers' licenses. Therefore, the insurance claim needs to be processed by collecting driver's license information from the driver's license image and integrating each driver's personally identifiable information (PII), without associating it between drivers.

[0004] Currently, several methods have been proposed for identifying personally identifiable information (PII) in multiple documents. For example, various search tools can be used to search for and identify PII in documents. However, existing methods are based on automated, data-centric technical solutions or graphs used in data models (e.g., identity graphs), but these methods, bound to a single document, often cannot handle PII scattered across multiple documents. Therefore, a technical problem exists: how to improve the efficiency and accuracy of identifying personally identifiable information related to a specific person in one or more documents while obfuscating data unrelated to that person.

[0005] Therefore, based on the above discussion, it is necessary to overcome the aforementioned shortcomings of traditional data processing methods related to the identification of PII elements of specific personnel in typical data processing devices. Summary of the Invention

[0006] This disclosure provides a data processing apparatus and a computer-implemented data processing method. It offers a technical solution to address existing problems, namely, how to improve the efficiency and accuracy of identifying personally identifiable information related to a specific person in one or more documents while obfuscating data unrelated to that person. This disclosure aims to provide a technical solution that at least partially overcomes the problems encountered in the prior art and provides an improved data processing apparatus and an improved computer-implemented data processing method, for example, by providing a data subject access request (DSAR) and personally identifiable information (PII) to detect data obfuscation.

[0007] The objective of this disclosure is achieved by the technical solutions provided in the appended independent claims. Advantageous embodiments of this disclosure are further defined in the dependent claims.

[0008] In one aspect, this disclosure provides a data processing apparatus including an input unit for receiving a request for a document. The request specifies at least one personally identifiable information (PII) element associated with a first subject. The data processing apparatus further includes an identification unit for identifying one or more PII elements in the requested document. The data processing apparatus also includes: a lookup unit for searching a database for each identified PII element to link PII elements of identifiers associated with the same subject; and an editing unit for editing the document to obfuscate PII elements of one or more identifiers not linked to the specified PII element. The data processing apparatus further includes an output unit for outputting the edited document.

[0009] By identifying one or more PII elements associated with the first subject, the data processing device efficiently and accurately identifies relevant information related to the first subject. Furthermore, the data processing device identifies one or more PII elements associated with the first subject not only from a single document but also from multiple documents. Moreover, the data processing device obfuscates PII elements not linked to the first subject, thus ensuring data privacy and further enabling the data processing device to comply with data privacy regulations and regulations.

[0010] In one implementation, the designated PII element is associated with a first subject. The editing unit is further configured to: for each identifier's PII element not linked to the designated PII element, determine whether the first subject is authorized to view the identifier's PII element; and obfuscate any identifier's PII element not linked to the designated PII element, wherein the subject associated with the designated PII element is not authorized to view the identifier's PII element.

[0011] By identifying the PII elements of each identifier that are not linked to the specified PII element, and obfuscating the PII elements of the identifier that the first subject has no right to view, the data processing device is able to hide sensitive data that does not belong to the first subject.

[0012] In another implementation, the request for a document includes a request for a data subject access report (DSAR) of the subject associated with the specified PII element. The data processing device further includes a search unit for searching one or more documents based on the subject and providing each document to the identification unit.

[0013] In the implementation described above, the search unit enables the data processing device to search one or more documents to include all PII elements related to the first subject.

[0014] In another implementation, the lookup unit is used to search a relational graph stored in the database. Each node of the graph represents an identified PII element, and each edge of the graph represents a link between pairs of identified PII elements.

[0015] In this implementation, the lookup unit enables the data processing device to discover links between one or more PII elements. The relational graph database enables the data processing device to determine which PII element belongs to the first entity.

[0016] In another implementation, each node of the relationship graph also includes an accuracy score for each identifier's PII element based on the accuracy of the identifier and a uniqueness score for each identifier's PII element based on the uniqueness of the identifier's PII element type, and each edge also includes a relationship accuracy score for each link based on the accuracy of the link.

[0017] Advantageously, the relationship graph enables the data processing device to identify the PII elements based on the accuracy score of each node, so as to efficiently and accurately link the one or more PII elements associated with the first subject with higher accuracy and reliability.

[0018] In another implementation, the lookup unit is used to traverse the graph starting from the specified PII element and generate a list including the PII elements of each traversal, wherein the traversal is limited by a weighting factor based on the assigned score.

[0019] This is helpful in determining which PII element is being traversed in the document.

[0020] On the other hand, this disclosure provides a computer-implemented data processing method, the method comprising: an input unit receiving a request for a document, wherein the request specifies at least one personally identifiable information (PII) element associated with a first subject. The computer-implemented method further comprises: an identification unit identifying one or more PII elements in the requested document; a search unit searching a database for each identified PII element to link PII elements of identified entities associated with the same subject. The method further comprises: an editing unit editing the document to obfuscate one or more PII elements not linked to the specified PII element; and an output unit outputting the edited document.

[0021] The method achieves all the advantages and technical effects of the data processing device of this disclosure.

[0022] In yet another aspect, this disclosure provides a computer-readable medium including instructions that, when executed by a processor, cause the processor to perform the method.

[0023] The processor (e.g., the processor of a device or system) achieves all the advantages and effects of the method after executing the method.

[0024] It should be understood that all of the above implementation methods can be combined together.

[0025] It should be noted that all devices, elements, circuits, units, and modules described in this application can be implemented in software elements or hardware elements, or any combination thereof. All steps performed by the various entities described in this application, and the functions to be performed by the various entities, are intended to refer to the respective entities for performing the respective steps and functions. Even in the description of the following specific embodiments, if a particular function or step to be performed by an external entity is not reflected in the description of the specific detailed elements of the entity performing that particular step or function, it will be apparent to those skilled in the art that these methods and functions can be implemented in the corresponding software or hardware elements, or in any combination of such elements. It is understood that the features of this disclosure are readily combined in various ways without departing from the scope of this disclosure as defined by the appended claims.

[0026] Other aspects, advantages, features, and objectives of this disclosure will become apparent from the accompanying drawings and detailed description of the illustrative embodiments, which are interpreted in conjunction with the appended claims. Attached Figure Description

[0027] The foregoing summary of the invention and the detailed description of illustrative embodiments below can be better understood when read in conjunction with the accompanying drawings. Exemplary constructions of this disclosure are shown in the drawings to illustrate the present disclosure. However, this disclosure is not limited to the specific methods and means disclosed herein. Furthermore, those skilled in the art will understand that these drawings are not drawn to scale. Where possible, the same elements are represented by the same numbers.

[0028] The embodiments of this disclosure are described below by way of example only, in conjunction with the accompanying drawings.

[0029] Figure 1 A block diagram illustrating various exemplary components of the data processing apparatus provided in embodiments of this disclosure;

[0030] Figure 2 A flowchart of a computer-implemented data processing method provided in an embodiment of this disclosure;

[0031] In the accompanying diagrams, underlined numbers indicate the item to which the underlined number is located or the item adjacent to the underlined number. Ununderlined numbers are associated with the item identified by the line linking the ununderlined number to that item. When a number is ununderlined but has an associated arrow, the ununderlined number identifies the general item pointed to by the arrow. Detailed Implementation

[0032] The following detailed description illustrates embodiments of the present disclosure and ways in which these embodiments may be implemented. While some implementations of the present disclosure have been disclosed, those skilled in the art will recognize that other embodiments for carrying out or practicing the present disclosure may also be implemented.

[0033] Figure 1 A block diagram illustrating various exemplary components of the data processing apparatus provided in embodiments of this disclosure is provided. (Refer to...) Figure 1 The diagram shows a block diagram 100 of a data processing device 102, which includes an input unit 104, an identification unit 106, a lookup unit 108, an editing unit 110, an output unit 112, a search unit 114, a memory 116, and a processor 118.

[0034] Data processing device 102 may include appropriate logic, circuitry, interfaces, or code for identifying personally identifiable information (PII) elements associated with a first subject. The PII element is present in one or more documents received from the first subject, and the data is obfuscated to view information belonging to the first subject. Data processing device 102 is also used to obfuscate PII elements that are not linked to one or more identified PII elements. In one implementation, the first subject may be a potential customer of an organization. In another implementation, the first subject may be a user of a product, a visitor to a website, a customer of a company, or an employee of an organization, without limiting the scope of this disclosure.

[0035] Input unit 104 may include appropriate logic, circuitry, interfaces, or code for receiving requests for documents. Examples of input unit 104 may include, but are not limited to, data terminals, receivers, receiving units, transceivers, fax machines, virtual servers, etc.

[0036] The identification unit 106 may include appropriate logic, circuitry, interfaces, or code for identifying one or more personally identifiable information (PII) elements in a requested document.

[0037] The lookup unit 108 may include appropriate logic, circuitry, interfaces, or code for searching the database for each identifier’s PII element to link PII elements of identifiers associated with the same subject.

[0038] Editing unit 110 may include appropriate logic, circuitry, interfaces, or code for editing a document to obfuscate one or more identified PII elements that are not linked to a specified PII element.

[0039] Output unit 112 may include appropriate logic, circuitry, interfaces, or code for outputting the edited document.

[0040] Search unit 114 may include appropriate logic, circuitry, interfaces, or code for searching one or more documents based on a subject. Search unit 114 is used to provide each document to identification unit 106.

[0041] Memory 116 may include appropriate logic, circuitry, interfaces, or code for storing data and instructions executable by processor 118. Examples of implementations of memory 116 may include, but are not limited to, electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), read-only memory (ROM), hard disk drive (HDD), flash memory, solid-state drive (SSD), or CPU cache memory. Memory 116 may store an operating system or other program products (including one or more operating algorithms) to operate data processing device 102.

[0042] Processor 118 may include appropriate logic, circuitry, interfaces, or code for executing instructions stored in memory 116. In one example, processor 118 may be a general-purpose processor. Other examples of processor 118 may include, but are not limited to, control units, central processing units (CPUs), digital signal processors (DSPs), microprocessors, microcontrollers, complex instructionset computing (CISC) processors, application-specific integrated circuit (ASIC) processors, reduced instruction set computing (RISC) processors, very long instruction word (VLIW) processors, state machines, data processing units, graphics processing units (GPUs), and other processors or control circuitry. Furthermore, processor 118 may refer to one or more separate processors, processing devices, or processing units as part of a machine, such as data processing device 102.

[0043] In operation, the data processing device 102 includes an input unit 104 for receiving a request for a document, wherein the request specifies at least one personally identifiable information (PII) element associated with a first subject. The input unit 104 is used to receive a request for a document related to the first subject, wherein the received request includes at least one personally identifiable information about the first subject. In one example, during registration for a service being used by the first subject, one or more PII elements are provided by the first subject to the organization during registration.

[0044] According to one embodiment, the request for a document includes a request for a data subject access report (DSAR) of a subject associated with a specified PII element. The data processing device 102 also includes a search unit 114 for searching one or more documents based on a first subject. The search unit 114 is used to provide each document to the identification unit 106. The request for a document is sufficient to identify the first subject, wherein the document includes a data subject access report (DSAR) request for a first subject associated with a specified PII element or more than one PII element. This request corresponds to identifying all relevant information about the first subject, regardless of which regulation the request is used to satisfy, such as a data subject access request (DSAR). In one implementation, the search may include searching from a relational graph of PIIs that include each document added to the database and associated with the first subject. Furthermore, the relational graph is constructed offline when each document is added to the database. After receiving a request for a document from the input unit 104, the search unit 114 searches for one or more documents about the first subject. Furthermore, the search unit 114 provides one or more documents found to the identification unit 106 to identify one or more PII elements associated with the first subject. Alternatively, the data processing device 102 includes an input unit 104 that receives requests for documents, and the search unit 114 searches for one or more documents associated with the first subject and provides the documents to the identification unit 106. Thus, the data processing device 102 is able to identify all relevant PII elements associated with the first subject in multiple documents.

[0045] The data processing device 102 also includes an identification unit 106 for identifying one or more PII elements in the requested document. In the example of the registration process described above, the PII elements may include the first subject's name, social security number (SSN), first subject's address, first subject's telephone number, first subject's credit card number, etc. Advantageously, the identification of one or more PII elements in the requested document enables the data processing device 102 to identify all personal information related to the first subject.

[0046] The data processing device 102 also includes a lookup unit 108 for searching the database for each identifier's PII element to link PII elements of identifiers associated with the same subject. In an example of the registration process, the lookup unit 108 is used to search the database for each identifier's PII element to link PII elements of identifiers associated with the first subject, such as the first subject's name, SSN, phone number, and credit card number. The lookup unit 108 can be used to group subject information such as name, SSN, phone number, and credit card number found in the database (i.e., PII elements associated with the first subject) together to obtain all PII elements associated with the first subject.

[0047] According to one embodiment, the lookup unit 108 is used to search a relationship graph stored in a database. Each node of the graph represents an identified PII element, and each edge of the graph represents a link between pairs of identified PII elements. The lookup unit 108 is used to search the relationship graph (or weighted graph) by searching for each identified PII element through the nodes of the graph and by searching for links between each identified PII element pair through the edges of the graph. In an example of a registration process, the lookup unit 108 can be used to search for various PII elements, such as the name of the first entity, the SSN of the first entity, the phone number of the first entity, and the credit card number of the first entity, as nodes of the graph. Furthermore, the lookup unit 108 can also be used to find links between each pair of PII elements as edges of the graph. Advantageously, the lookup unit 108 enables the data processing device 102 to discover links between one or more PII elements. The relationship graph database enables the data processing device to understand which PII element belongs to the first entity.

[0048] According to one embodiment, each node in the relationship graph also includes an accuracy score for each identified PII element based on the accuracy of the identifier and a uniqueness score for each identified PII element based on the uniqueness of the type of the identified PII element. Each edge also includes a relationship accuracy score for each link based on the accuracy of the link. The accuracy score describes the accuracy of the identifier performed by the identifier unit 106. The accuracy score is in the range of 0 to 1. Furthermore, the uniqueness score describes the uniqueness of the PII element. The uniqueness score value is between 0 and 1. A unique PII element can be a PII element that is legally unique and has a uniqueness equal to 1, such as a social security number (SSN) or a passport number (PPN). However, other PII elements, such as home addresses, phone numbers, credit card numbers, etc., are assigned a value less than 1, and the higher the value, the more unique the PII element. Additionally, the relationship accuracy score (which may also be named the PII relationship accuracy score) describes the accuracy of the links identified by the lookup unit 108. The relationship accuracy score value is between 0 and 1. Therefore, the data processing device 102 is able to discover relationships between PII elements. The relational graph database enables data processing device 102 to understand which PII entities belong to a specific individual, such as passport numbers, credit card numbers, names, etc. Advantageously, the relational graph allows data processing device 102 to identify the PII elements based on the accuracy score of each node, thereby enabling more efficient and accurate linking of the one or more PII elements associated with the first subject with higher accuracy and reliability.

[0049] According to one embodiment, the lookup unit 108 is configured to traverse the graph starting from a specified PII element and generate a list including the PII elements of each traversal. The traversal is limited by a weighting factor based on assigned scores. The input unit 104 is configured to receive the request, which includes one PII element or more than one PII element sufficient to identify the first subject. After the input unit 104 receives the request, the lookup unit 108 is configured to search a relational graph stored in a database by graph traversal to collect relevant information about the first subject. The graph traversal begins with the PII element or group of PII elements specified in the request. To collect relevant information about the first subject, the lookup unit 108 is also configured to generate a list including the PII elements of each traversal. The graph traversal is limited by a weighting factor calculated based on the accuracy and uniqueness scores assigned to each node and the relational accuracy score assigned to each edge. Alternatively, by using a weighting factor, the graph traversal is limited to those PII elements closely related to the one or more PII elements specified in the received request. The weighting factor for each node is calculated by multiplying the node's accuracy score by its path weight, where the path weight is the product of the previous node's path weight, the previous node's uniqueness score, and the accuracy score of the relationship between the two nodes. The weighting factor is a decreasing product because all scores—accuracy score, uniqueness score, and relationship accuracy score—are between 0 and 1. Therefore, this is advantageous for determining which PII element is being traversed in the document.

[0050] The data processing apparatus 102 further includes an editing unit 110 for editing the document to obfuscate one or more identified PII elements that are not linked to a specified PII element. The data processing apparatus 102 locates one or more PII elements associated with the first subject. However, some identified PII elements are not linked to the specified PII element; therefore, the identified PII elements must be obfuscated. An application programming interface (API) allows the first subject to hide all personally identifiable information, but not personally identifiable information that the first subject is allowed to see.

[0051] According to one embodiment, the designated PII element is associated with a first subject. Editing unit 110 is configured to determine, for each identifier's PII element not linked to the designated PII element, whether the first subject is authorized to view the identifier's PII element. Editing unit 110 is configured to obfuscate any identifier's PII element linked to the designated PII element, wherein the subject associated with the designated PII element is not authorized to view the identifier's PII element. One or more PII elements include name, social security number (SSN), address, and other names. For example, the following table represents one or more PII elements, such as address, SSN, passport ID, last name, and first name.

[0052] address SSN Passport ID Surname Name Tel Aviv 1234123 23453245234 Natanzon Assaf Herzlie 123453 34545134 Cohen Benny Tel Aviv 234625 348572345 Natanzon Gil Tel Aviv 23421 3645635 Natanzon Mirit Hyrule 45355 4563563 Legend Zelda

[0053] In the exemplary scenario, as shown in the table above, Assaf, Benny, Gil, Mirit, and Zelda are treated as different data subjects (i.e., subjects other than the first subject). The exemplary scenario in the table above could be an example of an organization storing PII elements for all Assaf, Benny, Gil, Mirit, and Zelda as different data subjects (or users). Furthermore, if Assaf requests a data-specific access report, the PII elements for all other data subjects are obfuscated. Additionally, in the example scenario, Gil is under 18 years old, so Assaf's father can view his personally identifiable information. Therefore, the data obfuscation allows Assaf to view the following information:

[0054] address SSN Passport ID Surname Name Tel Aviv 1234123 23453245234 Natanzon Assaf **** **** **** **** **** Tel Aviv 234625 348572345 Natanzon Gil **** **** **** **** **** **** **** **** **** ****

[0055] By identifying the PII elements of each identifier that are not linked to the specified PII element, and obfuscating the PII elements of the identifier that the first subject has no right to view, the data processing device 102 is able to hide sensitive data that does not belong to the first subject.

[0056] The data processing device 102 also includes an output unit 112 for outputting the edited document. After the editing unit 110 edits the document, the output unit 112 provides the edited document to a first subject to view it. The final edited document includes one or more specified PII elements associated with the first subject. Furthermore, the edited document includes data obfuscation of sensitive data not linked to the first subject.

[0057] Therefore, due to the identification of one or more PII elements associated with the first subject, the data processing device 102 efficiently and accurately identifies relevant information associated with the first subject. Furthermore, the data processing device 102 identifies one or more PII elements associated with the first subject not only from a single document but also from multiple requested documents. Moreover, the data processing device 102 obfuscates PII elements not linked to the first subject, thus ensuring data privacy and further enabling the data processing device 102 to comply with data privacy regulations and regulations.

[0058] Figure 2 A flowchart illustrating a computer-implemented data processing method provided in an embodiment of this disclosure. (Already combined with...) Figure 1 The components are described Figure 2 . refer to Figure 2 The diagram illustrates a computationally implemented data processing method 200. The computationally implemented method 200 includes steps 202 to 210. The computer-implemented data processing method 200 comprises (…). Figure 1 The data processing device 102 performs the operation.

[0059] A computer-implemented data processing method 200 is provided. This method provides all relevant sensitive information relating to a first subject and obfuscates sensitive information unrelated to the first subject.

[0060] In step 202, the computer-implemented data processing method 200 includes: an input unit (e.g., Figure 1 The input unit 104) receives a request for a document, wherein the received request includes at least one personally identifiable information about the first subject. In one example, during the registration process for a service being used by the first subject, one or more PII elements are provided by the first subject to the organization during the registration period.

[0061] In step 204, the computer-implemented data processing method 200 further includes: an identification unit (e.g., identification unit 106) identifying one or more personally identifiable information (PII) elements in the requested document. Upon receiving the request, identification unit 106 identifies one or more PII elements. The identified one or more PII elements may include name, identity, address, telephone number, etc. Furthermore, identification unit 106 identifies all PIIs, including those unrelated to the first subject. Therefore, data processing device 102 confuses PIIs unrelated to the first subject. Advantageously, the identification of one or more PII elements in the requested document enables data processing device 102 to identify all PIIs related to the first subject as well as PIIs unrelated to the first subject.

[0062] In step 206, the computer-implemented data processing method 200 further includes searching the database for the PII element of each identifier using a lookup unit (e.g., lookup unit 108) to link the PII elements of identifiers associated with the same subject. The lookup unit 108 can be used to group subject information such as name, SSN, phone number, and credit card information found in the database (i.e., PII elements associated with the first subject) together to obtain all PII elements associated with the first subject.

[0063] In step 208, the computer-implemented data processing method 200 further includes editing by an editing unit (e.g., editing unit 110). The computer-implemented data processing method 200 identifies one or more PII elements associated with the first subject. However, some identified PII elements are not linked to designated PII elements; therefore, the identified PII elements must be obfuscated. An application programming interface (API) allows the first subject to hide all personally identifiable information, but not the personally identifiable information that the first subject is allowed to see.

[0064] In step 210, the computer-implemented data processing method 200 further includes output by an output unit (e.g., output unit 112). After the editing unit 110 edits the document, the output unit 112 provides the edited document to the first subject for viewing. The final edited document includes one or more specified PII elements associated with the first subject. Furthermore, the edited document includes data obfuscation of sensitive data not linked to the first subject.

[0065] According to one embodiment, a request for a document includes a request for a data subject access report (DSAR) of a subject associated with a specified PII element. The computer-implemented data processing method 200 further includes a search unit searching for one or more documents based on the subject and providing each document to an identification unit 106. A request for a document including a data subject access report (DSAR) request for a subject associated with a specified PII element or more than one PII element is sufficient to identify the first subject. This request corresponds to identifying all relevant information about the first subject, regardless of which regulation the request is used to satisfy, such as a data subject access request (DSAR). In one implementation, the search may include searching from a relational graph of PIIs included in a database for each document added to the database, the graph being constructed offline when each document is added to the database. After receiving a request for a document from the input unit 104, the search unit 114 searches for one or more documents about the first subject. Furthermore, the search unit 114 provides the searched one or more documents to the identification unit 106 to search for and identify one or more PII elements associated with the first subject. Alternatively, the data processing device 102 includes an input unit 104 that receives requests for documents, and a search unit 114 that searches for one or more documents related to the first subject and provides the documents to the identification unit 106. This enables the data processing device 102 to identify all relevant PII elements related to the first subject in multiple documents.

[0066] According to one embodiment, searching for each PII element includes searching a relational graph stored in a database. Each node of the graph represents an identified PII element, and each edge of the graph represents a link between pairs of identified PII elements. A computer-implemented data processing method 200 is used to search the relational graph (or weighted graph) by searching for each identified PII element through the nodes of the graph and by searching for links between each identified PII element pair through the edges of the graph. Advantageously, the computer-implemented data processing method 200 enables the data processing device 102 to discover links between one or more PII elements. The relational graph database enables the data processing device to understand which PII element belongs to the first entity.

[0067] According to one embodiment, each node of the relationship graph also includes an accuracy score for each identified PII element based on the accuracy of the identifier and a uniqueness score for each identified PII element based on the uniqueness of the type of the identified PII element. Each edge also includes a relationship accuracy score for each link based on the accuracy of the link. The accuracy score describes the accuracy of the identifier performed by the computer-implemented data processing method 200. The accuracy score is in the range of 0 to 1. Furthermore, the uniqueness score describes the uniqueness of the PII element. The uniqueness score value is between 0 and 1. A unique PII element can be a PII element that is legally unique and has a uniqueness equal to 1, such as a social security number (SSN) or a passport number (PPN). However, other PII elements, such as home addresses, phone numbers, credit card numbers, etc., are assigned a value less than 1, and the higher the value, the more unique the PII element. Additionally, the relationship accuracy score (which may also be named the PII relationship accuracy score) describes the accuracy of the links identified by the lookup unit 108. The relationship accuracy score value is between 0 and 1. Therefore, the data processing device 102 is able to discover relationships between PII elements. The relational graph database enables data processing device 102 to understand which PII entities belong to a specific individual, such as passport numbers, credit card numbers, names, etc. Advantageously, the relational graph allows data processing device 102 to identify the PII elements based on the accuracy score of each node, thereby efficiently and accurately linking the one or more PII elements associated with the first subject with higher accuracy and reliability.

[0068] According to one embodiment, editing a document includes traversing a graph starting from a specified PII element and generating a list including each traversed PII element. The traversal is limited by a weighting factor based on assigned scores. An input unit 104 is configured to receive the request, which includes one PII element or more than one PII element sufficient to identify the first subject. After receiving the request, a lookup unit 108 is configured to search a relational graph stored in a database by graph traversal to collect relevant information about the first subject. The graph traversal begins with the PII element or group of PII elements specified in the request. To collect relevant information about the first subject, the lookup unit 108 is also configured to generate a list including each traversed PII element. The graph traversal is limited by a weighting factor calculated based on an accuracy and uniqueness score assigned to each node and a relational accuracy score assigned to each edge. Alternatively, by using a weighting factor, the graph traversal is limited to those PII elements closely related to the one or more PII elements specified in the received request. The weighting factor for each node is calculated by multiplying the node's accuracy score by its path weight, where the path weight is the product of the previous node's path weight, the previous node's uniqueness score, and the accuracy score of the relationship between the two nodes. The weighting factor is a decreasing product because all scores—accuracy score, uniqueness score, and relationship accuracy score—are between 0 and 1. Therefore, this is advantageous for determining which PII element is being traversed in the document.

[0069] According to one embodiment, editing the document further includes: for each PII element not linked to the specified PII element, determining whether a subject associated with the specified PII element is authorized to view the PII element. Editing the document includes: obfuscating any identified PII elements not linked to the specified PII element, wherein a subject associated with the specified PII element does not have permission to view the identified PII element. One or more PII elements include a name, social security number (SSN), address, and other names.

[0070] Therefore, due to the identification of one or more PII elements associated with the first subject, the computer-implemented data processing method 200 efficiently and accurately identifies relevant information associated with the first subject. Furthermore, the computer-implemented data processing method 200 identifies one or more PII elements associated with the first subject not only from a single document but also from multiple requested documents. Moreover, the computer-implemented data processing method 200 obfuscates PII elements not linked to the first subject, thus ensuring data privacy and further enabling the computer-implemented data processing method 200 to comply with data privacy regulations and regulations.

[0071] Steps 202 to 210 are merely illustrative, and other alternatives may be provided without departing from the scope of the claims herein, wherein one or more steps are added, one or more steps are deleted, or one or more steps are provided in a different order.

[0072] In one aspect, a computer-readable medium is provided comprising instructions that, when executed by a processor (e.g., processor 118 of data processing device 102), cause the processor to perform the computer-implemented data processing method 200. In one example, the instructions may be implemented on a computer-readable medium including, but not limited to, electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), read-only memory (ROM), hard disk drive (HDD), flash memory, secure digital (SD) cards, solid-state drives (SSDs), computer-readable storage media, and / or CPU cache. In one example, the instructions are generated by a computer program that implements the computer-implemented data processing method 200 and is intended to implement the computer-implemented data processing method 200 on one or more processors, such as processor 118 of data processing device 102.

[0073] Modifications to the embodiments of this disclosure described above may be made without departing from the scope of this disclosure as defined by the appended claims. Expressions such as “comprising,” “including,” “combining,” “having,” and “are” used to describe and claim this disclosure are intended to be interpreted in a non-unique manner, allowing for the appearance of items, portions, or elements not explicitly described. Singular references should also be interpreted to refer to the plural. The word “exemplary” as used herein means “as an example, instance, or illustration.” Any embodiment described as “exemplary” is not necessarily to be construed as preferred or superior to other embodiments, and / or does not exclude combinations of features from other embodiments. The word “optionally” as used herein means “provided in some embodiments and not in others.” It should be understood that certain features of this disclosure described in the context of a single embodiment for clarity may also be provided in combination in a single embodiment. Conversely, for brevity, various features of this disclosure described in the context of a single embodiment may also be provided individually or in any suitable combination or as embodiments of any other described aspect of this disclosure.

Claims

1. A data processing device (102), characterized in that, include: The input unit (104) is configured to receive a request for a document, wherein the request specifies at least one personally identifiable information (PII) element associated with a first subject; Identification unit (106) is used to identify one or more PII elements in the document to be requested; The lookup unit (108) is used to search the database for the PII element of each identifier to link the PII elements of identifiers associated with the same subject; Editing unit (110) is used to edit the document to obfuscate PII elements of one or more identifiers that are not linked to a specified PII element; Output unit (112) is used to output the edited document; The request for the document includes a request for a Data Subject Access Report (DSAR) of the subject associated with the specified PII element, and the data processing device (102) further includes: The search unit (114) is used to search for one or more documents based on the subject and provide each document to the identification unit (106). The search unit (108) is used to search a relational graph stored in the database, wherein each node of the relational graph represents an identified PII element, and each edge of the relational graph represents a link between pairs of identified PII elements; Each node in the relationship graph also includes an accuracy score for each identifier's PII element based on the accuracy of the identifier and a uniqueness score for each identifier's PII element based on the uniqueness of the identifier's PII element type. Each edge also includes a relationship accuracy score for each link based on the accuracy of the link. The accuracy score, the uniqueness score, and the relationship accuracy score are between 0 and 1. The search unit (108) is used to traverse the relationship graph starting from the specified PII element and generate a list including each traversed PII element, wherein the traversal is limited by a weighting factor based on an assigned score, the weighting factor being the accuracy score of the node, the path weight of the previous node, the uniqueness score of the previous node, and the decreasing product of the accuracy scores of the relationship between nodes.

2. The data processing device (102) according to claim 1, characterized in that, The designated PII element is associated with the first subject, and the editing unit is further configured to: For each identifier's PII element that is not linked to the specified PII element, determine whether to authorize the first subject to view the identifier's PII element; Obfuscate any PII element of an identifier that is not linked to the specified PII element, wherein the subject associated with the specified PII element has no right to view the PII element of the identifier.

3. A computer-implemented data processing method (200), characterized in that, include: The input unit (104) receives a request for a document, wherein the request specifies at least one personally identifiable information (PII) element associated with a first subject; The identification unit (106) identifies one or more PII elements in the requested document; The lookup unit (108) searches the database for the PII element of each identifier to link the PII elements of identifiers associated with the same subject; The editing unit (110) edits the document to obfuscate one or more PII elements that are not linked to the specified PII element; Output unit (112) outputs the edited document; The request for the document includes a request for a Data Subject Access Report (DSAR) of the subject associated with the specified PII element, and the method further includes: The search unit (114) searches for one or more documents based on the subject and provides each document to the identification unit (106). Searching for each PII element involves searching a relational graph stored in the database, wherein each node of the relational graph represents an identified PII element, and each edge of the relational graph represents a link between pairs of identified PII elements. Each node in the relationship graph also includes an accuracy score for each identifier's PII element based on the accuracy of the identifier and a uniqueness score for each identifier's PII element based on the uniqueness of the identifier's PII element type. Each edge also includes a relationship accuracy score for each link based on the accuracy of the link. The accuracy score, the uniqueness score, and the relationship accuracy score are between 0 and 1. Editing the document involves traversing the relationship graph starting from the specified PII element and generating a list including each PII element traversed, wherein the traversal is constrained by a weighting factor based on an assigned score, the weighting factor being a decreasing product of the node's accuracy score, the path weight of the previous node, the uniqueness score of the previous node, and the accuracy scores of the relationships between nodes.

4. The computer-implemented data processing method (200) according to claim 3, characterized in that, Editing the document also includes: For each PII element that is not linked to the specified PII element, determine whether to authorize the subject associated with the specified PII element to view the PII element; Obfuscate any PII element of an identifier that is not linked to the specified PII element, wherein the subject associated with the specified PII element has no right to view the PII element of the identifier.

5. A computer-readable medium including instructions, characterized in that, When the instruction is executed by the processor, it causes the processor to perform the method according to claim 3 or 4.

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