KR20230061195A - Personal information fragmentation method and device - Google Patents

Abstract

The present invention relates to a personal information fragmentation method. The personal information fragmentation method includes the steps of: receiving data containing personal information; separating the received data into areas which correspond to personal information and areas which do not correspond to personal information; dividing personal information data including areas which correspond to the separated personal information into a plurality of blocks using data fragmentation; and encrypting non-personal information data including areas which do not correspond to personal information and the personal information data divided into a plurality of blocks and distributing and storing the data to a plurality of nodes.

Description

Personal information fragmentation method and device {PERSONAL INFORMATION FRAGMENTATION METHOD AND DEVICE}

The present invention relates to a method and apparatus for fragmentation of personal information, and more specifically, to a method and apparatus for fragmentation of personal information based on a block chain.

Currently, various online services require personal information such as a user's name, address, phone number, and account number for user registration. In general, personal information input by a user is protected using various security systems, but a problem of leakage of personal information online sometimes occurs. Therefore, it is required to develop a security technology to prevent leakage of personal information or to make it difficult to identify personal information.

The present invention provides a personal information fragmentation method, a computer program stored in a computer readable medium, a computer readable medium in which the computer program is stored, and an apparatus (system) to solve the above problems.

The present invention can be implemented in a variety of ways, including a method, an apparatus (system), a computer program stored in a computer readable medium, or a computer readable medium in which a computer program is stored.

According to an embodiment of the present invention, a personal information fragmentation method performed by at least one processor includes the steps of receiving data including personal information, dividing the received data into areas corresponding to personal information and areas not corresponding to personal information. The step of dividing the personal information data including the area corresponding to the separated personal information into a plurality of blocks using data fragmentation, and the non-personal information data including the area that does not correspond to personal information and and encrypting the personal information data divided into a plurality of blocks and distributively storing them in a plurality of nodes.

According to an embodiment of the present invention, generating map data including a coupling relationship between a plurality of blocks and non-personal information data distributed and stored in a plurality of nodes, and map data generated using a smart contract on a blockchain network It further includes the step of storing in .

According to an embodiment of the present invention, the step of encrypting non-personal information data including an area not corresponding to personal information and personal information data divided into a plurality of blocks and storing them in a plurality of nodes in a distributed manner, Combining the included first and second blocks to generate fake data, and combining the generated fake data with personal information data divided into a plurality of blocks.

According to an embodiment of the present invention, the step of encrypting non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks and storing them in a plurality of nodes in a distributed manner corresponds to personal information. and selectively encrypting non-personal information data including non-personal information data and personal information data divided into a plurality of blocks by using bit value inversion of Huffman code.

According to an embodiment of the present invention, the step of encrypting non-personal information data including a region that does not correspond to personal information and personal information data divided into a plurality of blocks and storing them in a plurality of nodes in a distributed manner, among the plurality of blocks Calculating the number of a plurality of nodes for storing a predetermined number or more blocks in an activated node and encrypting non-personal information data including areas that do not correspond to personal information and personal information data divided into a plurality of blocks and distributing and storing the calculated number in a plurality of nodes.

A computer program stored in a computer readable recording medium is provided to execute the above-described method according to an embodiment of the present invention on a computer.

A computing device according to an embodiment of the present invention includes a communication module, a memory, and at least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory. At least one program receives data including personal information, divides the received data into an area corresponding to personal information and an area that does not correspond to personal information, and includes the area corresponding to the separated personal information. To divide information data into a plurality of blocks using data fragmentation, encrypt non-personal information data including areas that do not correspond to personal information and personal information data divided into a plurality of blocks, and distribute and store them in a plurality of nodes contains commands.

According to an embodiment of the present invention, at least one program generates map data including a coupling relationship between a plurality of blocks and non-personal information data distributed and stored in a plurality of nodes, and map data generated using a smart contract. It further includes instructions for storing on the blockchain network.

According to an embodiment of the present invention, at least one program generates fake data by combining a first block and a second block included in a plurality of blocks, and personal information divided into a plurality of blocks. It further contains instructions for combining with data.

According to an embodiment of the present invention, at least one program selects non-personal information data including an area not corresponding to personal information and personal information data divided into a plurality of blocks by using bit value inversion of Huffman code. It further includes instructions for encrypting with .

According to an embodiment of the present invention, at least one program calculates the number of a plurality of nodes for storing a predetermined number or more blocks among a plurality of blocks in an activated node, and includes an area that does not correspond to personal information. It further includes instructions for encrypting non-personal information data and personal information data divided into a plurality of blocks to distribute and store them in a plurality of nodes of the calculated number.

In various embodiments of the present invention, the computing device can minimize exposure of personal information when data is leaked by combining and storing fake data not included in existing personal information data with personal information data.

In various embodiments of the present invention, when encryption is performed using bit value inversion of the Huffman code, a decoding process is simplified during encryption, and decoding time can be effectively reduced.

In various embodiments of the present invention, when storing data including personal information, the computing device performs fragmentation, encryption, distributed storage, etc. to effectively prevent personal information leakage.

By generating and inserting fake data in various embodiments of the present invention, security of personal information can be efficiently maintained even when an arbitrary attacker checks a plurality of blocks.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned are clear to those skilled in the art (referred to as "ordinary technicians") from the description of the claims. will be understandable.

BRIEF DESCRIPTION OF THE DRAWINGS Embodiments of the present invention will be described with reference to the accompanying drawings described below, wherein like reference numbers indicate like elements, but are not limited thereto.
1 is a functional block diagram showing the internal configuration of a computing device according to an embodiment of the present invention.
2 is an exemplary flowchart illustrating a process of performing data fragmentation and combining between a fragmentation performer, a distribution management unit, and a data combiner according to an embodiment of the present invention.
3 is a diagram illustrating an example of generating fake data according to an embodiment of the present invention.
4 is a diagram illustrating an example in which a distribution node distributes and stores a plurality of blocks according to an embodiment of the present invention.
5 is a flowchart illustrating an example of a personal information fragmentation method according to an embodiment of the present invention.
6 is a flowchart illustrating an example of a method for generating fake data according to an embodiment of the present invention.
7 is a block diagram showing an internal configuration of a computing device according to an embodiment of the present invention.

Hereinafter, specific details for the implementation of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description, if there is a risk of unnecessarily obscuring the gist of the present invention, detailed descriptions of well-known functions or configurations will be omitted.

In the accompanying drawings, identical or corresponding elements are given the same reference numerals. In addition, in the description of the following embodiments, overlapping descriptions of the same or corresponding components may be omitted. However, omission of a description of a component does not intend that such a component is not included in an embodiment.

Advantages and features of the disclosed embodiments, and methods of achieving them, will become apparent with reference to the following embodiments in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and can be implemented in various different forms, only these embodiments make the present invention complete and the scope of the invention to those skilled in the art. It is provided only for complete information.

Terms used in this specification will be briefly described, and the disclosed embodiments will be described in detail. The terms used in this specification have been selected from general terms that are currently widely used as much as possible while considering the functions in the present invention, but these may vary depending on the intention or precedent of a person skilled in the related field, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, not simply the name of the term.

Expressions in the singular number in this specification include plural expressions unless the context clearly dictates that they are singular. Also, plural expressions include singular expressions unless the context clearly specifies that they are plural. When it is said that a certain part includes a certain component in the entire specification, this means that it may further include other components without excluding other components unless otherwise stated.

In the present invention, the terms "comprise", "comprising" and the like may indicate that features, steps, operations, elements and/or components are present, but may be used when such terms include one or more other functions, It is not excluded that steps, actions, elements, components, and/or combinations thereof may be added.

In the present invention, when a specific element is referred to as being “coupled”, “combined”, “connected”, or “reactive” to any other element, the specific element is directly bonded to, combined with, and/or other elements. or may be linked or reacted, but is not limited thereto. For example, one or more intermediate components may exist between certain components and other components. Also, in the present invention, “and/or” may include each of one or more items listed or a combination of at least a part of one or more items.

In the present invention, terms such as "first" and "second" are used to distinguish a specific component from other components, and the aforementioned components are not limited by these terms. For example, the “first” element may have the same or similar shape as the “second” element.

In the present invention, "blockchain" is a system in a distributed environment in which digitized information, assets, or transactions can be exchanged in general, using a shared ledger or ledger to establish peer-to-peer (P2P) -to-peer) It may refer to a system or platform that records the history of electronic transactions occurring in the network. Here, the blockchain uses a decentralized or decentralized consensus mechanism, and the validating node on the network executes the same (or agreed upon) consensus algorithm for the same transaction details. can be approved (or disapproved). For example, the blockchain may be, but is not limited to, a private blockchain, a public blockchain, a main chain or side chain, an on-chain chain, off-chain, hybrid blockchain, or any combination thereof. In addition, in the present invention, "node" can refer to a device capable of recording, maintaining, and storing a shared ledger in a block chain, and capable of recording and processing transaction details such as block creation. there is.

In the present invention, "smart contract" may refer to a series of software codes realized on a blockchain platform, and when using such a smart contract, the contents of the contract are automatically fulfilled when predetermined conditions are met. It can be.

In the present invention, "personal information" may include any data and/or information associated with an individual, for example, the individual's name, resident registration number, occupation, address, image, video, contact information, financial And payment information may include, but is not limited thereto.

In the present invention, "data fragmentation" may refer to dividing data constituting one logical object into small units to physically distribute and store them. For example, data fragmentation may include horizontal fragmentation, vertical fragmentation, mixed fragmentation, and the like, but is not limited thereto.

1 is a functional block diagram showing the internal configuration of a computing device 100 according to an embodiment of the present invention. As shown, the computing device 100 may include a fragmentation performer 110, a distribution manager 120, a data combiner 130, and the like, but is not limited thereto. The computing device 100 may communicate with an arbitrary external device and/or database and exchange data including personal information.

According to an embodiment, the segmentation performer 110 may receive data including personal information and separate the received data into a region corresponding to personal information and a region not corresponding to personal information. For example, an area corresponding to personal information may be determined by a user associated with the personal information or extracted by an arbitrary algorithm and/or machine learning model according to features of received data.

In addition, the fragmentation performer 110 may divide personal information data including a region corresponding to the separated personal information into a plurality of blocks by using data fragmentation. For example, the fragmentation performing unit 110 may perform data fragmentation using a predetermined algorithm and/or a machine learning model. Here, a block may refer to each data fragment generated by data fragmentation based on received data.

According to an embodiment, the fragmentation performer 110 generates fake data using a plurality of blocks divided from the personal information data, and divides the generated fake data into a plurality of blocks and personal information data can be combined Here, the fake data may refer to any data generated using at least some of a plurality of blocks, and in this way, the computing device 100 combines fake data not included in existing personal information data with personal information data. By combining and storing, exposure of personal information in case of data leakage can be minimized.

According to an embodiment, the fragmentation performer 110 may generate first fake data by combining a first block and a second block included in a plurality of blocks. Also, the fragmentation performer 110 may generate second fake data by combining a third block and a fourth block included in a plurality of blocks. That is, specific fake data may be generated by combining two or more blocks included in a plurality of blocks, and in this case, an arbitrary number of fake data may be configured. Here, the fake data may be generated using a predetermined algorithm and/or machine learning model.

Additionally or alternatively, data obfuscation may be performed on personal information data including fake data. Here, data obfuscation is to make specific data difficult to read by an arbitrary device, and may be performed based on an arbitrary algorithm and/or a machine learning model. For example, data obfuscation may include data masking that combines personal information data with other public information to make the personal information data difficult to identify.

According to an embodiment, the distribution management unit 120 may encrypt and store personal information data (personal information data divided into a plurality of blocks) and/or non-personal information data in distributed nodes. For example, the distribution management unit 120 selectively selects non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks by using bit value inversion of Huffman code. can be encrypted. Here, the Huffman code may be an encoding method used when compressing facsimile transmission and figure information.

According to an embodiment, the distribution management unit 120 may compress each of the plurality of blocks with Huffman coding. Then, the distribution management unit 120 may determine whether to send each block included in the plurality of blocks as original code or encrypted. In this case, the distribution management unit 120 may invert values of premise bits of an encrypted block, and store or transmit the original block together with encryption information of an unencrypted block. In this way, when encryption is performed using bit value inversion of the Huffman code, a decoding process is simplified during encryption, and decoding time can be effectively reduced.

According to an embodiment, the distribution management unit 120 may calculate the number of a plurality of nodes for storing blocks of a predetermined number or more among a plurality of blocks in an activated node to ensure availability of data. In addition, the distribution management unit 120 may encrypt non-personal information data including a region not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes of the calculated number. For example, the number of nodes in which personal information data is stored may be calculated by Equation 1 below.

Here, D may be the number of requests for personal information data per unit time, and K may be the number of blocks required for recovery. In addition, N is the number of data partitions, C may represent the storage capacity of the node, and P may represent the processing performance of the node. Also, T may represent unit time.

When the number of nodes for storing a plurality of blocks is calculated, the distribution management unit 120 distributes and stores the plurality of blocks by using a predetermined non-contiguous data distribution and storage algorithm so as not to store contiguous data in the same node. can In this way, when a plurality of nodes are distributed and stored, the distribution management unit 120 may generate map data including a coupling relationship between a plurality of distributedly stored blocks and non-personal information data. In addition, the distribution management unit 120 may store, manage, and/or process map data generated using a smart contract on a blockchain network.

According to an embodiment, the data combiner 130 may collect and combine data stored in a plurality of nodes in a distributed manner. For example, when there is a request for distributed and stored data, the data combiner 130 may extract map data associated with the requested data on the blockchain network. Then, the data combination unit 130 may collect and decode distributedly stored data (eg, a plurality of blocks) based on the extracted map data, and perform relation-based combination. In this case, decryption may be performed using a predetermined algorithm and/or machine learning model.

In FIG. 1 , each functional configuration included in the computing device 100 has been separately described, but this is only to aid understanding of the present invention, and one computing device may perform two or more functions. With this configuration, when storing data including personal information, the computing device 100 performs fragmentation, encryption, distributed storage, and the like, to effectively prevent leakage of personal information.

2 is an exemplary flowchart illustrating a process of performing data fragmentation and combining between the fragmentation performer 110, the distribution management unit 120, and the data combiner 130 according to an embodiment of the present invention. As shown, the fragmentation performer 110, the distribution management unit 120, and the data combiner 130 may exchange data and/or information required for data fragmentation and combining.

According to an embodiment, the fragmentation performer 110 may receive data including personal information. In this case, the distribution management unit 120 may provide the optimal partitioning and attribute-based encryption key 122 to the fragmentation performing unit 110 . When the optimal segmentation and attribute-based encryption key 122 is received, the fragmentation performer 110 divides the received data into an area corresponding to personal information and an area that does not correspond to personal information, and corresponds to the separated personal information. Personal information data including the area to be divided into a plurality of blocks using data fragmentation. In other words, the fragmentation performer 110 may perform data fragmentation and encryption (112). In FIG. 2 , it has been described above that the fragmentation unit 110 performs data encryption, but is not limited thereto, and data encryption may also be performed by the distribution management unit 120 .

According to an embodiment, the fragmentation unit 110 may transmit the encrypted data 114 to the distribution management unit 120 . In this case, the distribution management unit 120 may distribute and store the received data (124). For example, the distribution management unit 120 may encrypt non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes in a distributed manner. In this case, the distribution management unit 120 generates map data including a coupling relationship between a plurality of blocks and non-personal information data that are distributed and stored in a plurality of nodes, and maps the generated map data using smart contracts to the blockchain network. can be saved

Additionally or alternatively, the distribution management unit 120 may calculate the number of nodes for storing at least a predetermined number of blocks among the plurality of blocks in the activated node. Then, the distribution management unit 120 may encrypt non-personal information data including a region not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes of the calculated number. Additionally or alternatively, the distribution management unit 120 generates fake data by combining a specific block and other specific blocks included in a plurality of blocks, and combines the generated fake data with personal information data divided into a plurality of blocks. It can be distributed and stored on multiple nodes.

According to one embodiment, distributedly stored data may be combined and provided. When data provision is required, the distribution management unit 120 may transmit the attribute-based encryption key and division information 126 to the data combination unit 130 . Here, the division information may include map data including coupling relationships between data distributed and stored in a plurality of nodes, but is not limited thereto. When receiving the attribute-based encryption key and division information 126, the data combiner 130 obtains a block associated with data from each node, and decrypts and combines the data based on the attribute-based encryption key and division information 126. can be performed (132).

3 is a diagram illustrating an example of generating fake data 330 according to an embodiment of the present invention. As described above, the computing device (100 in FIG. 1) may encrypt non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes in a distributed manner. In this case, the computing device generates fake data 330 by combining the first block 310 and the second block 320 included in the plurality of blocks, and divides the generated fake data 330 into a plurality of blocks. It can be combined with personal information data and stored in a distributed manner. In this case, any algorithm and/or machine learning model for generating fake data 330 may be used.

In FIG. 3, it is shown that fake data 330 is generated using two blocks 310 and 320, but is not limited thereto. For example, the computing device may generate fake data by combining or combining three or more blocks. Also, the location and/or region where the fake data 330 is inserted or combined may be determined based on the location and/or region of blocks used to generate the fake data 330, but is not limited thereto. By generating and inserting the fake data 330 in this way, even when an arbitrary attacker checks a plurality of blocks, it is possible to efficiently maintain the security of personal information.

4 is a diagram illustrating an example in which a distribution node 420 distributes and stores a plurality of blocks according to an embodiment of the present invention. In the illustrated example, the distribution node 420 may include the above-described distribution management unit ( 120 in FIG. 1 ). As described above, the distribution node 420 encrypts non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks, and distributes the data to a plurality of data nodes 430, 440, and 450. distributed storage. In this case, the distribution node 420 generates map data 422 including a coupling relationship between a plurality of blocks and non-personal information data distributed and stored in a plurality of data nodes 430, 440, and 450, and uses a smart contract. The generated map data 422 may be stored on the blockchain network 410.

According to an embodiment, the distribution node 420 sets the number of a plurality of data nodes 430, 440, and 450 for storing blocks of a predetermined number or more among a plurality of blocks in an activated node to ensure availability of data. can be calculated In addition, the distribution node 420 encrypts non-personal information data including an area not corresponding to personal information and personal information data divided into a plurality of blocks, and the calculated number of data nodes 430, 440, and 450 can be distributed and stored in

In FIG. 4, it is shown that three data nodes 430, 440, and 450 exist, but it is not limited thereto, and any number of data nodes may exist.

5 is a flowchart illustrating an example of a personal information fragmentation method 500 according to an embodiment of the present invention. Personal information fragmentation method 500 may be performed by at least one processor (eg, at least one processor of a computing device). The personal information fragmentation method 500 may be initiated by a processor receiving data including personal information (S510).

The processor may separate the received data into an area corresponding to personal information and an area not corresponding to personal information (S520). In addition, the processor may divide the personal information data including the area corresponding to the separated personal information into a plurality of blocks using data fragmentation (S530). Here, the block may be a data fragment including a part of the personal information data, and the processor may divide the personal information data into a plurality of blocks using an optimal partitioning algorithm or the like.

The processor may encrypt non-personal information data including areas not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes in a distributed manner (S540). In this case, the processor calculates the number of a plurality of nodes for storing a predetermined number or more of the plurality of blocks in the activated node, and divides the non-personal information data including the non-personal information area into a plurality of blocks. The divided personal information data may be encrypted and stored in a plurality of nodes of the calculated number in a distributed manner.

6 is a flowchart illustrating an example of a fake data generating method 600 according to an embodiment of the present invention. The fake data generating method 600 may be performed by at least one processor (eg, at least one processor of a computing device). According to an embodiment, the processor may encrypt non-personal information data including a region not corresponding to personal information and personal information data divided into a plurality of blocks and store them in a plurality of nodes in a distributed manner. In this case, the processor may generate fake data by combining the first block and the second block included in the plurality of blocks (S610). In addition, the processor may combine the generated fake data with personal information data divided into a plurality of blocks (S620).

Additionally or alternatively, the processor may generate map data including a coupling relationship between a plurality of blocks and non-personal information data distributed and stored in a plurality of nodes. In addition, the processor may store map data generated using a smart contract on a blockchain network. Additionally or alternatively, the processor may selectively encrypt non-personal information data including a region not corresponding to personal information and personal information data divided into a plurality of blocks using bit value inversion of Huffman code.

7 is a block diagram showing an internal configuration of a computing device 700 according to an embodiment of the present invention. The computing device 700 may include a memory 710 , a processor 720 , a communication module 730 and an input/output interface 740 . As shown in FIG. 7 , the computing device 700 may be configured to communicate information and/or data over a network using a communication module 730 .

Memory 710 may include any non-transitory computer readable storage medium. According to one embodiment, the memory 710 is a non-perishable mass storage device (permanent mass storage device) such as random access memory (RAM), read only memory (ROM), disk drive, solid state drive (SSD), flash memory, and the like. mass storage device). As another example, a non-perishable mass storage device such as a ROM, SSD, flash memory, or disk drive may be included in the computing device 700 as a separate permanent storage device separate from memory. Also, an operating system and at least one program code may be stored in the memory 710 .

These software components may be loaded from a computer-readable recording medium separate from the memory 710 . A recording medium readable by such a separate computer may include a recording medium directly connectable to the computing device 700, for example, a floppy drive, a disk, a tape, a DVD/CD-ROM drive, a memory card, and the like. It may include a computer-readable recording medium. As another example, software components may be loaded into the memory 710 through the communication module 730 rather than a computer-readable recording medium. For example, at least one program may be loaded into the memory 710 based on a computer program installed by files provided by developers or a file distribution system that distributes application installation files through the communication module 730. can

The processor 720 may be configured to process commands of a computer program by performing basic arithmetic, logic, and input/output operations. Commands may be provided to a user terminal (not shown) or other external system by the memory 710 or the communication module 730 .

The communication module 730 may provide a configuration or function for a user terminal (not shown) and the computing device 700 to communicate with each other through a network, and the computing device 700 may provide an external system (for example, a separate cloud system). etc.) may provide a configuration or function to communicate with. For example, control signals, commands, data, etc. provided under the control of the processor 720 of the computing device 700 are transmitted through the communication module 730 and the network to the user terminal and/or to the user terminal through the communication module of the external system. and/or transmitted to an external system.

Also, the input/output interface 740 of the computing device 700 may be connected to the computing device 700 or may be a means for interface with a device (not shown) for input or output that may be included in the computing device 700. . In FIG. 7 , the input/output interface 740 is illustrated as an element separately configured from the processor 720 , but is not limited thereto, and the input/output interface 740 may be included in the processor 720 . Computing device 700 may include many more components than those of FIG. 7 . However, there is no need to clearly show most of the prior art components.

The processor 720 of the computing device 700 may be configured to manage, process, and/or store information and/or data received from a plurality of user terminals and/or a plurality of external systems.

The above-described methods and/or various embodiments may be realized with digital electronic circuits, computer hardware, firmware, software, and/or combinations thereof. Various embodiments of the present invention may be performed by a data processing device, eg, one or more programmable processors and/or one or more computing devices, or as a computer readable recording medium and/or a computer program stored on a computer readable recording medium. can be implemented The above-described computer programs may be written in any form of programming language, including compiled or interpreted languages, and may be distributed in any form, such as a stand-alone program, module, or subroutine. A computer program may be distributed over one computing device, multiple computing devices connected through the same network, and/or distributed over multiple computing devices connected through multiple different networks.

The methods and/or various embodiments described above may be performed by one or more processors configured to execute one or more computer programs that process, store, and/or manage any function, function, or the like, by operating on input data or generating output data. can be performed by For example, the method and/or various embodiments of the present invention may be performed by a special purpose logic circuit such as a Field Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC), and the method and/or various embodiments of the present invention may be performed. Apparatus and/or systems for performing the embodiments may be implemented as special purpose logic circuits such as FPGAs or ASICs.

The one or more processors executing the computer program may include a general purpose or special purpose microprocessor and/or one or more processors of any kind of digital computing device. The processor may receive instructions and/or data from each of the read-only memory and the random access memory, or receive instructions and/or data from the read-only memory and the random access memory. In the present invention, components of a computing device performing methods and/or embodiments may include one or more processors for executing instructions, and one or more memory devices for storing instructions and/or data.

According to one embodiment, a computing device may exchange data with one or more mass storage devices for storing data. For example, a computing device may receive/receive data from and transfer data to a magnetic or optical disc. A computer-readable storage medium suitable for storing instructions and/or data associated with a computer program includes semiconductor memory devices such as Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable PROM (EEPROM), and flash memory devices. Any type of non-volatile memory may be included, but is not limited thereto. For example, computer readable storage media may include magnetic disks such as internal hard disks or removable disks, magneto-optical disks, CD-ROM and DVD-ROM disks.

To provide interaction with a user, a computing device includes a display device (eg, a cathode ray tube (CRT), a liquid crystal display (LCD), etc.) It may include a pointing device (eg, a keyboard, mouse, trackball, etc.) capable of providing input and/or commands to, but is not limited thereto. That is, the computing device may further include any other type of device for providing interaction with a user. For example, a computing device may provide any form of sensory feedback to a user for interaction with the user, including visual feedback, auditory feedback, and/or tactile feedback. In this regard, the user may provide input to the computing device through various gestures such as visual, voice, and motion.

In the present invention, various embodiments may be implemented in a computing system including a back-end component (eg, a data server), a middleware component (eg, an application server), and/or a front-end component. In this case, the components may be interconnected by any form or medium of digital data communication, such as a communication network. For example, the communication network may include a local area network (LAN), a wide area network (WAN), and the like.

A computing device based on the example embodiments described herein may be implemented using hardware and/or software configured to interact with a user, including a user device, user interface (UI) device, user terminal, or client device. can For example, the computing device may include a portable computing device such as a laptop computer. Additionally or alternatively, the computing device may include personal digital assistants (PDAs), tablet PCs, game consoles, wearable devices, internet of things (IoT) devices, virtual reality (VR) devices, AR (augmented reality) device, etc. may be included, but is not limited thereto. A computing device may further include other types of devices configured to interact with a user. Further, the computing device may include a portable communication device (eg, a mobile phone, smart phone, wireless cellular phone, etc.) suitable for wireless communication over a network, such as a mobile communication network. A computing device communicates wirelessly with a network server using wireless communication technologies and/or protocols such as radio frequency (RF), microwave frequency (MWF) and/or infrared ray frequency (IRF). It can be configured to communicate with.

The various embodiments herein, including specific structural and functional details, are exemplary. Accordingly, embodiments of the present invention are not limited to those described above and may be implemented in various other forms. In addition, terms used in the present invention are for describing some embodiments and are not construed as limiting the embodiments. For example, the singular and the above may be construed to include the plural as well, unless the context clearly dictates otherwise.

In the present invention, unless defined otherwise, all terms used in this specification, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which such concept belongs. . In addition, terms commonly used, such as terms defined in a dictionary, should be interpreted as having a meaning consistent with the meaning in the context of the related technology.

Although the present invention has been described in relation to some embodiments in this specification, various modifications and changes can be made without departing from the scope of the present invention that can be understood by those skilled in the art. Moreover, such modifications and variations are intended to fall within the scope of the claims appended hereto.

100: computing device
110: Fragmentation performing unit
120: distributed management unit
130: data coupling unit

Claims (11)

A personal information fragmentation method performed by at least one processor, comprising:
Receiving data including personal information;
separating the received data into an area corresponding to personal information and an area not corresponding to personal information;
dividing personal information data including a region corresponding to the separated personal information into a plurality of blocks using data fragmentation; and
Encrypting non-personal information data including a region not corresponding to the personal information and personal information data divided into a plurality of blocks and storing them distributedly in a plurality of nodes;
Personal information fragmentation method including.
According to claim 1,
generating map data including a coupling relationship between a plurality of blocks stored in a distributed manner in the plurality of nodes and the non-personal information data; and
Storing the generated map data on a blockchain network using a smart contract;
Personal information fragmentation method further comprising a.
According to claim 1,
Encrypting the non-personal information data including the area not corresponding to the personal information and the personal information data divided into the plurality of blocks and storing them in a plurality of nodes in a distributed manner,
generating fake data by combining a first block and a second block included in the plurality of blocks; and
combining the generated fake data with the personal information data divided into the plurality of blocks;
Personal information fragmentation method including.
According to claim 1,
Encrypting the non-personal information data including the area not corresponding to the personal information and the personal information data divided into the plurality of blocks and storing them in a plurality of nodes in a distributed manner,
selectively encrypting non-personal information data including a region not corresponding to the personal information and personal information data divided into the plurality of blocks by using bit value inversion of a Huffman code;
Personal information fragmentation method including.
According to claim 1,
Encrypting the non-personal information data including the area not corresponding to the personal information and the personal information data divided into the plurality of blocks and storing them in a plurality of nodes in a distributed manner,
calculating the number of the plurality of nodes for storing a predetermined number or more blocks among the plurality of blocks in an activated node; and
Encrypting the non-personal information data including the area not corresponding to the personal information and the personal information data divided into the plurality of blocks and distributively storing them in a plurality of nodes of the calculated number;
Personal information fragmentation method including.
A computer program stored in a computer-readable recording medium to execute the method according to any one of claims 1 to 5 on a computer.
As a computing device,
communication module;
Memory; and
at least one processor connected to the memory and configured to execute at least one computer readable program included in the memory;
including,
The at least one program,
receive data containing personal information;
Dividing the received data into areas corresponding to personal information and areas not corresponding to personal information;
Dividing the personal information data including the area corresponding to the separated personal information into a plurality of blocks using data fragmentation;
A computing device comprising instructions for encrypting non-personal information data including a region not corresponding to the personal information and personal information data divided into a plurality of blocks and storing them in a plurality of nodes in a distributed manner.
According to claim 7,
The at least one program,
generating map data including a coupling relationship between a plurality of blocks stored in a distributed manner in the plurality of nodes and the non-personal information data;
A computing device further comprising instructions for storing the generated map data on a blockchain network using a smart contract.
According to claim 7,
The at least one program,
Combining a first block and a second block included in the plurality of blocks to generate fake data;
The computing device further comprising instructions for combining the generated fake data with the personal information data divided into the plurality of blocks.
According to claim 7,
The at least one program,
The computing device further comprising instructions for selectively encrypting non-personal information data including a region not corresponding to the personal information and personal information data divided into the plurality of blocks by using bit value inversion of a Huffman code.
According to claim 7,
The at least one program,
Calculating the number of the plurality of nodes for storing a predetermined number or more of the plurality of blocks in the activated node;
The computing device further comprising instructions for encrypting non-personal information data including an area not corresponding to the personal information and personal information data divided into a plurality of blocks and storing them in a distributed manner in a plurality of nodes of the calculated number.

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