Computer, method executed using computer, and program

Abstract

To curb unlawful use of artwork while ensuring accessibility to the artwork.SOLUTION: A computer according to the present invention is configured to: input one or more values relating to stroke data associated with artwork of an artist into a machine learning model generated on the basis that an artificial intelligence program is caused to learn one or more values indicative of characteristics of the artwork of the artist; and output artist feature quantity indicative of characteristics of creation of the artwork of the artist from the machine learning model. The one or more values relate to at least one of a writing speed, a writing pressure value, pen angle data, and a temporal distribution of touch and hover states.SELECTED DRAWING: Figure 18

Description

[Technical field]

[0001] The present invention relates to an artwork management method, a computer, and a program. [Background technology]

[0002] In recent years, various services have been created using smart contracts that use blockchain to guarantee the validity of contracts. For example, Patent Literature 1 discloses the use of smart contracts for money lending by banks. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2019-524018 Summary of the Invention [Problem to be solved by the invention]

[0004] Meanwhile, there is a technology called Digital Rights Management (DRM) that aims to protect the rights of digital image creators by restricting the reproduction of digital images. This technology can be used to restrict illegal use, such as unauthorized use, of artworks such as digital paintings created on tablet devices, but at the same time, it reduces accessibility to the artworks. This could result in the rights of the artists who are the creators of the artworks being infringed, so improvements are needed.

[0005] Therefore, one object of the present invention is to provide an artwork management method, computer, and program that can restrict illegal use of artwork while ensuring accessibility to the artwork. [Means for solving the problem]

[0006] The artwork management method according to the present invention is an artwork management method executed by one or more computers, and includes a detection step in which a first computer included in the one or more computers detects artwork included in a website, a determination step in which the first computer determines whether a purchase transaction indicating the purchase of the artwork detected in the detection step is recorded in a blockchain network, and a transmission step in which the first computer sends a report indicating that unauthorized use of the artwork has been discovered if it is determined by the determination step that the purchase transaction is not recorded.

[0007] The computer according to the present invention includes a detection unit that detects artwork included in a website, a determination unit that determines whether a purchase transaction indicating the purchase of the artwork detected by the detection unit is recorded in a blockchain network, and a transmission unit that transmits a report indicating that unauthorized use of the artwork has been discovered if the determination unit determines that the purchase transaction is not recorded.

[0008] The program according to the present invention is a program for causing a computer to execute a detection step of detecting artwork included on a website, a determination step of determining whether a purchase transaction indicating the purchase of the artwork detected in the detection step is recorded in a blockchain network, and a transmission step of sending a report indicating that unauthorized use of the artwork has been discovered if it is determined by the determination step that the transaction is not recorded. Effect of the Invention

[0009] According to the present invention, it is possible to suppress illegal use of artwork while ensuring accessibility to the artwork. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing a configuration of an artwork transaction and management system 1 according to an embodiment of the present invention. [Diagram 2] 2 is a diagram showing an example of the hardware configuration of a platform portal server 3, an artist terminal 4, and a purchaser terminal 5. FIG. [Diagram 3] FIG. 4 is a diagram illustrating pen angle data. [Figure 4] FIG. 2 is a diagram showing a configuration of biometric signature data. [Diagram 5] FIG. 2 is a diagram showing input and output of data to and from the platform portal server 3. [Figure 6] FIG. 2 is a functional block diagram of the platform portal server 3 for exhibiting artwork. [Figure 7] FIG. 2 is a functional block diagram of a platform portal server 3 for selling artworks. [Figure 8] 13A is a functional block diagram of a plug-in installed in a third-party terminal 6, and FIG. 13B is a functional block diagram of a platform portal server 3 involved in the payment of rewards to a third-party terminal 6. FIG. [Figure 9] FIG. 2 is a functional block diagram of the platform portal server 3 for determining the authenticity of artwork. [Figure 10] FIG. 1A is a diagram for explaining an artist feature that indicates the characteristics of an artwork created by an artist, and FIG. 1B is a diagram for explaining an artwork feature that is made up of a plurality of values ​​that indicate the characteristics of the artwork. [Figure 11] FIG. 11 is a diagram showing a specific example of an artwork feature amount. [Figure 12] 13 is a process flow diagram showing the process executed by the platform portal server 3. FIG. [Figure 13] FIG. 13 is a diagram showing details of the artwork submission process executed in step S7 of FIG. 12. [Figure 14] FIG. 13 is a diagram showing details of the artwork sales process executed in step S8 of FIG. 12. [Figure 15]FIG. 13 is a diagram showing details of the artwork sales process executed in step S8 of FIG. 12. [Figure 16] FIG. 15 is a diagram showing details of the watermark embedding process executed in step S41 of FIG. 14. [Figure 17] FIG. 17 is a process flow diagram showing a process for retrieving a watermark from watermarked artwork generated by the watermark embedding process shown in FIG. [Figure 18] 13 is a process flow diagram showing unauthorized use monitoring processing executed by a plug-in installed in the browser software of the third party terminal 6. FIG. [Figure 19] FIG. 13 is a diagram showing details of the reward payment process executed in step S9 of FIG. [Figure 20] FIG. 13 is a diagram showing details of the authenticity determination process executed in step S10 of FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

[0012] 1 is a diagram showing the configuration of an artwork trading and management system 1 according to this embodiment. As shown in the figure, the artwork trading and management system 1 has a configuration in which a platform portal server 3, an artist terminal 4, a purchaser terminal 5, a third party terminal 6, a blockchain network 7, a distributed file system 8, and a catalog database 9 are interconnected via a network 2. In addition, a secure key store 3a, a feature database 3b, and an incentive pool 3c are connected to the platform portal server 3.

[0013] 2 is a diagram showing an example of the hardware configuration of the platform portal server 3, the artist terminal 4, the purchaser terminal 5, and the third party terminal 6. Each of the platform portal server 3, the artist terminal 4, the purchaser terminal 5, and the third party terminal 6 can be configured by a computer 100 having the configuration shown in the figure.

[0014] As shown in FIG. 2, the computer 100 includes a CPU (Central Processing Unit) 101, a storage device 102, an input device 103, an output device 104, and a communication device 105.

[0015] The CPU 101 is a device that controls each part of the computer 100 and reads and executes various programs stored in the storage device 102. Each process described with reference to Fig. 12 to Fig. 17, Fig. 19, and Fig. 20 shown later is realized by the CPU 101 of the platform portal server 3 executing a program stored in the storage device 102. Moreover, a process described with reference to Fig. 18 shown later is realized by the CPU 101 of the third party terminal 6 executing a program (a plug-in described later) stored in the storage device 102.

[0016] The storage device 102 includes a main storage device such as a dynamic random access memory (DRAM) and an auxiliary storage device such as a hard disk, and serves to store various programs for executing the operating system and various applications of the computer 100, as well as data used by these programs. An artificial intelligence program for performing unsupervised learning by deep learning is pre-stored in the storage device 102 of the platform portal server 3, and the platform portal server 3 also functions as a machine learning device by executing this program.

[0017] The input device 103 is a device that receives input operations from a user and supplies them to the CPU 101, and is configured to include, for example, a keyboard, a mouse, and a touch detection device. Of these, the touch detection device is a device that includes a touch sensor and a touch controller, and is used to detect pen input or touch input. Pen input is realized, for example, by an active electrostatic method or an electromagnetic induction method. Touch input is realized, for example, by a capacitance method.

[0018] The output device 104 is a device that outputs the processing results of the CPU 101 to the user, and is configured to include, for example, a display and a speaker. The communication device 105 is a device for communicating with external devices, and transmits and receives data according to instructions from the CPU 101. Data transmission and reception between the platform portal server 3, the artist terminal 4, the purchaser terminal 5, and the third party terminal 6 is realized by the communication devices 105 communicating with each other.

[0019] Returning to Fig. 1, the artist terminal 4 is a computer used by the artist to input and submit artwork, as well as to input biometric signature data, which will be described later. The artwork and biometric signature data are both digital data, and are generated by the artist using pen P to input data to the input device 103 of the artist terminal 4. The specific process for submitting artwork will be described later.

[0020] To explain the method of inputting artwork, the touch detection device of artist terminal 4 is configured to be able to detect pen P present in the vicinity of the touch surface. While detecting pen P, the touch detection device periodically acquires coordinate data indicating the position of pen P on the touch surface, a writing pressure value indicating the pressure applied to the tip of pen P, and pen angle data indicating the inclination of pen P with respect to the touch surface, and supplies these to CPU 101.

[0021] The coordinate data is data indicating the position of the pen P detected by the touch detection device. To explain in detail taking an example where pen input is realized by an active electrostatic method, the touch sensor is first configured to include a plurality of X electrodes each extending in the Y direction and arranged at equal intervals in the X direction, and a plurality of Y electrodes each extending in the X direction and arranged at equal intervals in the Y direction. The touch controller obtains coordinate data indicating the position of the pen P by receiving burst signals transmitted by the pen P at each of the plurality of X electrodes and the plurality of Y electrodes.

[0022] The pen pressure value is data detected, for example, by a pressure sensor built into the pen P. The pen angle data is data detected, for example, by a tilt sensor built into the pen P. The pen P that supports the active electrostatic method can transmit a data signal to the paired touch controller, and transmits the pen pressure value and pen angle data by this data signal.

[0023] FIG. 3 is a diagram for explaining pen angle data. As shown in the figure, the pen angle data includes an azimuth angle θ, a tilt angle φ, and a rotation angle ψ. Of these, the tilt angle φ may be detected by the touch controller based on a signal transmitted by the pen P. In this case, the pen P has a configuration in which two electrodes are arranged in parallel in the pen axis direction, and each transmits a burst signal. The touch detection device detects the tilt angle φ from the position at which each of the two burst signals thus transmitted is received.

[0024] Returning to Fig. 1, the CPU 101 of the artist terminal 4 determines whether or not the tip of the pen P is in contact with the touch surface based on the pen pressure value supplied from the touch detection device. Then, stroke data is generated from a series of coordinate data and the like acquired while the pen P is in a touching state, and the stroke data is stored in the storage device 102 and displayed on a display constituting the output device 104. The artwork is composed of a digital ink file including the series of stroke data thus stored in the storage device 102. Each stroke data is data including a series of combinations of coordinate data, pen pressure values, and pen angle data, and timestamp information indicating the time when each combination was acquired by the touch detection device.

[0025] Fig. 4 is a diagram showing the structure of biometric signature data. The biometric signature data is data generated according to, for example, WILL (Wacom Ink Layer Language) or FSS (Forensic Signature Stream), and as shown in Fig. 4, includes dynamic signature data, a hash value of a signed document, context information, additional information, dynamic signature data, a hash value of a signed document, a hash value of the context information, this hash value and this hash value of the additional information, and a checksum for detecting errors that may occur when transmitting or receiving this hash value. Of these, the dynamic signature data is composed of a digital ink file including a series of stroke data, similar to artwork.

[0026] The hash value of the signed document is the hash value of the electronic data of the document (exhibition application, contract, etc.) that the artist signed to generate the biometric signature data. Note that the hash value is a value obtained by inputting the target electronic data into a predetermined one-way hash function. This also applies to the other hash values ​​described below.

[0027] The context information includes the name data of the artist who signed, the date and time of signing, the purpose of the signature, information on the touch detection device used for signing (manufacturer name, model name, etc.), information on the application used for signing (application name, version information, etc.), information on the operating system of the artist terminal 4 (operating system name, version information, etc.), address information of the artist terminal 4 (IP address, MAC address, etc.), etc. The additional information is information that can be arbitrarily specified by the administrator of the artwork transaction management system 1 in addition to the dynamic signature data, the hash value of the signed document, and the context information.

[0028] Returning to Fig. 1, the purchaser terminal 5 is a computer used by a purchaser to purchase artwork (artwork put up for sale by an artist). Specific processing for this purchase will be described later.

[0029] The third-party terminal 6 is a third-party computer seen from the administrator of the artwork transaction and management system 1, and serves to monitor illegal use, such as unauthorized use, of the artwork and to report any unauthorized use discovered. The monitoring is performed, for example, by a plug-in installed in the browser software. The third-party terminal 6 also serves to request the platform portal server 3 to determine the authenticity of the artwork. The specific process for this monitoring and authenticity determination will be described later.

[0030] The blockchain network 7 is a network of multiple computers connected peer-to-peer and configured to record smart contract transactions on the blockchain. As a specific example, the blockchain network 7 is the Ethereum network. Recording of transactions on the blockchain is performed by several computers (hereinafter referred to as "miners") connected to the blockchain network 7.

[0031] Specifically, each block constituting the blockchain includes a block header and data (transaction data) indicating the specific contents of a transaction. The block header includes a Merkle root, which is data obtained by compressing the size of the transaction data, a hash value of the previous block, and a nonce value, which is an arbitrary character string. In the blockchain network 7, a rule is established that in order to connect a new block to the blockchain, the hash value of the block must satisfy a certain condition (for example, the condition that the value starts with "000"). Therefore, a miner who wants to record a block in the blockchain performs an operation (mining) of brute-forcely finding a nonce value so that the hash value of the block header of the block satisfies the above-mentioned predetermined condition. As a result of this operation, the miner who succeeds in finding the nonce value first connects the block to the blockchain, thereby completing the recording of the transaction in the blockchain.

[0032] The distributed file system 8 is a network of multiple computers connected peer-to-peer, and is configured to store any electronic data. As a specific example, the distributed file system 8 is IPFS (InterPlanetary File System). Electronic data stored in the distributed file system 8 is identified by its hash value. That is, in the distributed file system 8, the hash value of the stored electronic data functions as address information of the electronic data. In this embodiment, the distributed file system 8 is used to store encrypted artwork.

[0033] The catalog database 9 is a database implemented on one or more computers. In this embodiment, it is used to store catalogs of artworks (information required for sales). The catalog database 9 may be implemented in the platform portal server 3.

[0034] The secure key store 3a is a database for storing encryption keys used for encrypting data, and is set in advance to only accept access from the platform portal server 3. In this embodiment, the secure key store 3a is used to store public keys 1 and 2, private keys 1 and 2, and data encryption keys 1 and 2, which will be described later.

[0035] The feature database 3b is a database that stores artist features that indicate the characteristics of artwork created by an artist, and artwork features that are made up of a plurality of values ​​that indicate the characteristics of the artwork. Details of these features will be described later. The feature database 3b is also set in advance so that it only accepts access from the platform portal server 3.

[0036] The incentive pool 3c is a database for storing money to be given as an incentive to a third-party terminal 6 that transmits a report of the discovery of illegal use, for example, unauthorized use, of an artwork. As an example, this money may be a virtual currency (such as Ether) realized by the blockchain network 7. The incentive pool 3c is also set in advance to only accept access from the platform portal server 3.

[0037] The platform portal server 3 is a computer that functions as an artwork trading device, and plays a role in accepting artworks submitted by artists and realizing the purchase of submitted artworks. The platform portal server 3 also plays a role in monitoring unauthorized use of artworks via the third-party terminal 6, acquiring and managing the above-mentioned artist characteristics and artwork characteristics, and determining the authenticity of artworks using the managed artist characteristics and artwork characteristics.

[0038] 5 is a diagram showing data input and output to and from the platform portal server 3. The following will focus on and explain the stages of accepting artwork submissions, enabling artwork purchases, monitoring unauthorized use of artworks, and determining the authenticity of artworks.

[0039] First, in the stage of accepting the listing of an artwork, the platform portal server 3 accepts the listing of the artwork from the artist terminal 4. This listing includes a digital ink file, which is the main body of the artwork, and the sales conditions (paid / free, price if paid, etc.). The price may be indicated by a virtual currency (such as Ether) realized by the blockchain network 7. The platform portal server 3 also accepts input of the biometric signature data described above from the artist terminal 4. Having received the listing and the biometric signature data, the platform portal server 3 records a transaction indicating the listing (listing transaction) on the blockchain network 7. The specific contents of the listing transaction will be described later.

[0040] The platform portal server 3 that has accepted the submission of an artwork assigns identification information of a predetermined format (hereinafter, referred to as "image ID") to the artwork and embeds the image ID in the artwork. The artwork with the embedded image ID is then encrypted by a data encryption key 1, which corresponds to a common key in a common key cryptosystem, and stored in the distributed file system 8. The image ID may be information of a predetermined format that can distinguish artworks circulating in the market from one another, and may specifically be a random character string or a hash value of the artwork. The platform portal server 3 also generates a pair of a public key 1 and a private key 1, which correspond to a public key and a private key in a public key cryptosystem, and encrypts the data encryption key 1 with the public key 1. The pair of the public key 1 and the private key 1 and the encrypted data encryption key 1 are then stored in the secure key store 3a. The artwork is encrypted by the data encryption key 1, not by the public key 1, because the public key in the public key cryptosystem cannot encrypt large data such as artwork.

[0041] The platform portal server 3 further registers in the catalog database 9 a thumbnail of the put up artwork, the sales conditions, and the ID (identification information) of the listing transaction recorded in the blockchain network 7, and returns the ID of the listing transaction and the private key 1 to the artist terminal 4. The returned listing transaction ID is used by the artist to refer to the blockchain network 7 and confirm the contents of his / her listing. In addition, the private key 1 is used by the artist to retrieve his / her artwork from the distributed file system 8.

[0042] Furthermore, the platform portal server 3 acquires one or more values ​​indicating characteristics of the artwork created by the artist from one or more stroke data constituting the submitted artwork, and inputs each acquired value into the machine learning model to acquire the artist feature. The acquired artist feature is then stored in the feature database 3b in association with information identifying the artist. Details of the artist feature and the machine learning model will be described later.

[0043] Similarly, the platform portal server 3 acquires a plurality of values ​​indicating the characteristics of the artwork from one or more stroke data constituting the submitted artwork, and stores the values ​​as artwork feature quantities in the feature quantity database 3b. The details of the artwork feature quantities will also be described later.

[0044] Next, at the stage of realizing the purchase of the put up artwork, the platform portal server 3 accepts a purchase application from the purchaser terminal 5. This purchase application includes purchaser information (such as an account on the blockchain network 7 and a name) indicating the purchaser, information indicating the artwork selected by the purchaser, and a payment (for example, information indicating an arbitrary amount of virtual currency). Having accepted the purchase application, the platform portal server 3 records a transaction indicating the purchase (purchase transaction) in the blockchain network 7. The specific contents of the purchase transaction will be described later.

[0045] The platform portal server 3, which has accepted the purchase application, extracts the private key 1 and the data encryption key 1 from the secure key store 3a, and also extracts the artwork from the distributed file system 8. Then, the data encryption key 1 is decrypted with the private key 1, and the artwork (the artwork in which the image ID is embedded) is decrypted with the decrypted data encryption key 1.

[0046] The platform portal server 3 further embeds a watermark in the decrypted artwork to generate watermarked artwork, encrypts it with the data encryption key 2, and stores it in the distributed file system 8. As will be described in detail later, this watermark is generated based on the ID (identification information) of the purchase transaction.

[0047] The platform portal server 3 also generates a pair of public key 2 and private key 2, which correspond to the public key and private key in the public key cryptography, and encrypts the data encryption key 2 with the public key 2. Then, the pair of public key 2 and private key 2 and the encrypted data encryption key 2 are stored in the secure key store 3a. Note that the reason why the watermarked artwork is encrypted with the data encryption key 2 rather than the public key 2 is that the size of the watermarked artwork is large, just like when it is put up for sale.

[0048] The platform portal server 3 then performs a process of returning the purchase transaction ID, the private key 2, and the hash value of the encrypted watermarked artwork to the purchaser terminal 5, and also performs a process of sending the purchase transaction ID and the proceeds of the sale to the artist terminal 4. The purchase transaction ID returned to each terminal is used by the purchaser and artist to refer to the blockchain network 7 and confirm the purchase details. In addition, the private key 2 and the hash value of the encrypted watermarked artwork are used to retrieve the artwork purchased by the purchaser from the distributed file system 8 and decrypt it.

[0049] Furthermore, when the platform portal server 3 transfers the proceeds to the artist terminal 4, it performs a process of deducting a portion of the proceeds (for example, 10%), and storing the amount in the incentive pool 3c in association with the image ID. The money (for example, virtual currency) thus stored in the incentive pool 3c is used to pay the user of the third-party terminal 6 compensation for discovering the unauthorized use. Note that if damages are obtained through a copyright infringement lawsuit or the like after the unauthorized use is discovered, all or a portion of the damages may also be stored in the incentive pool 3c in the form of virtual currency.

[0050] Next, in the stage of monitoring unauthorized use of the artwork, the platform portal server 3 first distributes a browser software plug-in (add-on) to the third-party terminal 6. This plug-in runs on the browser software and has the function of monitoring websites loaded by users. In addition, the information required to access the blockchain network 7 (a contract account, described later) is written in advance to the plug-in.

[0051] Specifically, monitoring by the plug-in is performed by detecting artwork managed by the artwork transaction and management system 1, and if a purchase transaction corresponding to the detected artwork exists in the blockchain network 7, generating a report indicating that unauthorized use of the artwork has been discovered, and recording a report transaction indicating the generated report in the blockchain network 7. More details about this process will be described later.

[0052] When a new report transaction is recorded in the blockchain network 7, the platform portal server 3 acquires money stored in the incentive pool 3c in association with the image ID of the artwork corresponding to the report transaction, and transmits the money as a reward to the third-party terminal 6 that recorded the report transaction. The money thus transmitted functions as an incentive for the user of the third-party terminal 6 to keep the plug-in running.

[0053] Fig. 6 to Fig. 9 are functional block diagrams of a plug-in installed in the platform portal server 3 or the third party terminal 6. Fig. 6 shows a functional block of the platform portal server 3 related to the exhibition of artwork, Fig. 7 shows a functional block of the platform portal server 3 related to the sale of artwork, Fig. 8(a) shows a functional block of a plug-in installed in the third party terminal 6, Fig. 8(b) shows a functional block of the platform portal server 3 related to the payment of remuneration to the third party terminal 6, and Fig. 9 shows a functional block of the platform portal server 3 related to the authenticity determination of artwork. Below, the functional blocks of the platform portal server 3 will be described in detail with reference to these figures.

[0054] Referring first to Figure 6, the platform portal server 3 is configured to have, as functional blocks related to the listing of artwork, a receiving unit 11, a duplicate determination unit 12, a feature acquisition unit 13, an artwork encryption processing unit 14, an artwork storage processing unit 15, a key pair generation unit 16, a transaction issuing unit 17, a key encryption processing unit 18, a catalog generation unit 19, and a transmitting unit 20.

[0055] The receiving unit 11 receives an artwork listing from the artist terminal 4. As described above, this listing includes the artwork itself and information indicating the sales conditions.

[0056] The duplication determination unit 12 determines whether the submitted artwork is a duplicate of another artwork (i.e., whether the submitted artwork is not unique). This determination may be performed, for example, by comparing the submitted artwork with artworks previously stored in the distributed file system 8 by the platform portal server 3, or by comparing with images obtained by searching on the Internet, or by both. If the comparison results in no other artwork that overlaps with the submitted artwork, the duplication determination unit 12 determines that there is no duplication, and causes the receiving unit 11 to further receive the above-mentioned biometric signature data from the artist terminal 4. On the other hand, if another artwork that overlaps with the submitted artwork is found, the duplication determination unit 12 determines that there is a duplication, and returns to the artist terminal 4 that the submitted artwork cannot be submitted.

[0057] Moreover, the duplication determination unit 12 performs a process of assigning unique identification information (hereinafter referred to as "image ID") to artwork determined to be non-duplicate and embedding the information in the artwork. This process may be performed, for example, by adding the image ID to the artwork as metadata, by arranging the image ID obliquely on the surface of the artwork in a visibly recognizable state, or by generating a watermark indicating the image ID by a process similar to that of the watermark generation unit 36 ​​described later and embedding the generated watermark in the artwork by a process similar to that of the watermark embedding processing unit 37 described later.

[0058] The feature acquisition unit 13 performs a process of acquiring the above-mentioned artist feature and artwork feature based on the artwork determined not to be duplicated by the duplication determination unit 12, and storing them in the feature database 3b. This process will be described in detail below with reference to Figs. 10 and 11.

[0059] FIG. 10(a) is a diagram explaining artist features that indicate the characteristics (habits) of an artist's artwork production, and FIG. 10(b) is a diagram explaining artwork features that consist of multiple values ​​that indicate the characteristics of the artwork.

[0060] 10(a), each time an artwork is generated that is determined not to be duplicated by the duplication determination unit 12, the platform portal server 3 obtains one or more values ​​indicating characteristics of the artwork created by the artist from one or more stroke data constituting the artwork, and inputs the obtained values ​​together with artist information indicating the artist of the artwork to the above-mentioned artificial intelligence program. The artificial intelligence program learns the data thus inputted by deep learning and constructs a machine learning model. The machine learning model thus constructed is capable of outputting artist features in response to the above-mentioned one or more values ​​being newly inputted.

[0061] The one or more values ​​input to the artificial intelligence program are typically composed of the average value and variance of the pen speed, the average value and variance of the pen pressure value, the average value and variance of the pen angle data, and the temporal distribution of the touch state and the hover state, as shown in Fig. 10(a). However, it goes without saying that only some of these values ​​or other values ​​may be used.

[0062] The platform portal server 3 acquires the one or more values ​​from one or more stroke data constituting the artwork determined by the overlap determination unit 12 to be non-overlapping, and inputs the acquired values ​​to a machine learning model constructed by an artificial intelligence program. As a result, artist features are output from the machine learning model. The platform portal server 3 stores the acquired artist features in the feature database 3b in association with the corresponding artist information. If artist features for the same artist are already stored in the feature database 3b, the stored artist features are updated with the newly acquired artist features.

[0063] 10(b), the platform portal server 3 acquires artwork feature amounts consisting of a plurality of values ​​indicating the features of the artwork from one or more stroke data constituting the artwork that has been determined not to be overlapped by the overlap determination unit 12. The plurality of values ​​includes a series of pen touch coordinates each indicating the position of the pen when a pen touch is performed, and a series of pen up coordinates each indicating the position of the pen when a pen up is performed. The platform portal server 3 stores the artwork feature amounts thus acquired in the feature amount database 3b in association with the corresponding artwork.

[0064] The data shown in Table 1 below is an example of multiple values ​​that make up the artwork feature. In this data, the "d" at the beginning of each line indicates a pen touch, and the "u" indicates a pen up. In addition, the two coordinates after the "d" or "u" indicate the X and Y coordinates, respectively.

[0065] [Table 1]

[0066] FIG. 11 is a diagram showing an example of mapping of artwork features. In the figure, the number of times pen touches or pen ups occurred is represented for each coordinate by grayscale density. In this way, the mapping of artwork features results in a noise image showing the characteristics of the artwork. This noise image itself may be used as the artwork feature.

[0067] Returning to Fig. 6, the artwork encryption processing unit 14 encrypts the artwork when the duplication determination unit 12 determines that there is no duplication. To be more specific, the artwork encryption processing unit 14 first generates a data encryption key 1 that corresponds to a common key in a common key cryptosystem. Then, the generated data encryption key 1 is used to encrypt the artwork.

[0068] The artwork storage processing unit 15 stores the artwork encrypted by the artwork encryption processing unit 14 in the distributed file system 8 in association with the image ID assigned by the duplicate determination unit 12, and also obtains the hash value.

[0069] The key pair generation unit 16 generates a pair of a public key 1 and a private key 1, which correspond to a public key and a private key in a public key cryptosystem.

[0070] The transaction issuing unit 17 generates an auction transaction including the image ID assigned by the duplication determining unit 12, the hash value of the encrypted artwork acquired by the artwork storage processing unit 15, the biometric signature data received by the receiving unit 11, and the public key 1 generated by the key pair generating unit 16, and issues the transaction to a contract account (described later) of the blockchain network 7. After this, any of the miners connected to the blockchain network 7 completes recording of the auction transaction in the blockchain.

[0071] The key encryption processing unit 18 encrypts the data encryption key 1 using the public key 1 generated by the key pair generation unit 16, and stores the data encryption key 1 together with the pair of public key 1 and private key 1 in the secure key store 3a, corresponding to the ID of the listing transaction issued by the transaction issuing unit 17.

[0072] The catalog generation unit 19 generates thumbnails of the put-up artworks and registers them in the catalog database 9 together with the sales conditions and the ID of the putting-up transaction. By registering the put-up artworks in the catalog database 9 in this manner, a purchaser can refer to the catalog database 9 and select the artwork he or she wishes to purchase.

[0073] The transmitter 20 returns the listing transaction ID issued by the transaction issuer 17 and the private key 1 generated by the key pair generator 16 to the artist terminal 4. This enables the artist to confirm the listing transaction on the blockchain network 7, and also enables the artist to confirm the original artwork by retrieving and decrypting the encrypted artwork stored in the distributed file system 8.

[0074] The artist's confirmation of the original artwork will be described in more detail. The artist uses the artist terminal 4 to transmit the listing transaction ID and the private key 1 to the platform portal server 3. The platform portal server 3 obtains a hash value of the encrypted artwork by referring to the blockchain network 7 based on the listing transaction ID received from the artist terminal 4. Then, the platform portal server 3 accesses the distributed file system 8 using the obtained hash value and reads the encrypted artwork. The platform portal server 3 also reads the encrypted data encryption key 1 from the secure key store 3a based on the listing transaction ID received from the artist terminal 4, and decrypts it with the private key 1 received from the artist terminal 4. Finally, the platform portal server 3 obtains the artwork by decrypting the encrypted artwork using the decrypted data encryption key 1, and returns it to the artist terminal 4. In this way, the artist can confirm the artwork.

[0075] Next, referring to Figure 7, the platform portal server 3 is configured to have functional blocks related to the sale of artwork, such as a receiving unit 30, a purchase eligibility determination unit 31, a key decryption processing unit 32, an artwork decryption processing unit 33, a key pair generation unit 34, a transaction issuance unit 35, a watermark generation unit 36, a watermark embedding processing unit 37, an artwork encryption processing unit 38, an artwork storage processing unit 39, a key encryption processing unit 40, and a transmission unit 41.

[0076] The receiving unit 30 receives a purchase offer indicating an intention to purchase an artwork from the purchaser terminal 5. As described above, this purchase offer includes the purchaser information, information indicating the artwork selected by the purchaser, and the price.

[0077] The purchase possibility determination unit 31 determines whether the purchase offer is successful. More specifically, the purchase possibility determination unit 31 first reads out the sales conditions of the corresponding artwork and the ID of the auction transaction from the catalog database 9. Then, the purchase possibility determination unit 31 compares the read out sales conditions with the contents of the purchase offer and determines whether the purchase offer is successful based on the result. For example, if the sales conditions stipulate that the price of the artwork is 1 Ether, then if the purchase offer includes 1 Ether, the purchase possibility determination unit 31 determines that the purchase offer is successful. On the other hand, if the purchase offer does not include 1 Ether, the purchase possibility determination unit 31 determines that the purchase offer is not successful. In the latter case, the purchase possibility determination unit 31 returns a notice of purchase denial to the purchaser terminal 5.

[0078] The key decryption processing unit 32 reads the private key 1 and the encrypted data encryption key 1 from the secure key store 3a based on the ID of the auction transaction. Then, the key decryption processing unit 32 uses the read private key 1 to decrypt the read encrypted data encryption key 1.

[0079] The artwork decryption processing unit 33 acquires the image ID of the artwork or the hash value of the encrypted artwork by referring to the blockchain network 7 based on the ID of the listing transaction. Then, based on the acquired image ID or hash value, the encrypted artwork is read from the distributed file system 8 and decrypted using the data encryption key 1 decrypted by the key decryption processing unit 32.

[0080] The key pair generating unit 34 generates a pair of a public key 2 and a private key 2, which correspond to a public key and a private key in a public key cryptosystem.

[0081] The transaction issuing unit 35 generates a purchase transaction including the purchaser information included in the purchase offer, the listing transaction ID read by the purchase availability determination unit 31 from the catalog database 9, the image ID of the artwork, the amount indicating the purchase price of the artwork, and the public key 2 generated by the key pair generation unit 34, and issues the transaction to a contract account (described later) on the blockchain network 7. After this, any of the miners connected to the blockchain network 7 completes recording of the purchase transaction on the blockchain.

[0082] The watermark generation unit 36 ​​generates a watermark based on the purchase transaction ID issued by the transaction issuer 35. The watermark thus generated is, for example, a QR code (registered trademark) indicating the purchase transaction ID. The watermark embedding processing unit 37 performs processing to generate watermarked artwork by embedding a watermark in the artwork decoded by the artwork decoding processing unit 33. Details of this processing will be described later in detail with reference to FIG. 16.

[0083] The artwork encryption processing unit 38 generates a data encryption key 2 that corresponds to a common key in the common key cryptosystem, and encrypts the watermarked artwork using the generated data encryption key 2. The artwork storage processing unit 39 stores the watermarked artwork encrypted by the artwork encryption processing unit 38 in the distributed file system 8, and also acquires its hash value.

[0084] The key encryption processing unit 40 encrypts the data encryption key 2 using the public key 2 generated by the key pair generation unit 34, associates it with the purchase transaction ID issued by the transaction issuing unit 35, and stores it in the secure key store 3a.

[0085] The transmission unit 41 returns the ID of the purchase transaction, the hash value acquired by the artwork storage processing unit 39, and the private key 2 generated by the key pair generation unit 34 to the purchaser terminal 5, and also transmits the ID of the purchase transaction and a portion (e.g., 90%) of the proceeds to the artist terminal 4. The remaining portion (e.g., 10%) of the proceeds is accumulated in the incentive pool 3c. This allows the purchaser and artist to confirm the purchase transaction on the blockchain network 7. In addition, the purchaser can obtain the purchased artwork in a watermarked state by acquiring and decrypting the encrypted watermarked artwork stored in the distributed file system 8. In addition, it becomes possible to give a reward to the third-party terminal 6 for discovering the unauthorized use of the artwork.

[0086] The acquisition of the artwork by the purchaser will be described in more detail. The purchaser uses the purchaser terminal 5 to transmit the hash value of the encrypted watermarked artwork, the ID of the purchase transaction, and the private key 2 to the platform portal server 3. The platform portal server 3 accesses the distributed file system 8 using the hash value received from the purchaser terminal 5, and reads out the encrypted watermarked artwork. The platform portal server 3 also reads out the encrypted data encryption key 2 from the secure key store 3a based on the ID of the purchase transaction received from the purchaser terminal 5, and decrypts it with the private key 2 received from the purchaser terminal 5. Finally, the platform portal server 3 obtains the watermarked artwork by decrypting the encrypted watermarked artwork using the decrypted data encryption key 2, and returns it to the purchaser terminal 5. In this way, the purchaser can obtain the watermarked artwork.

[0087] Next, referring to Figure 8(a), the third-party terminal 6 is configured to have an image extraction unit 50, an artwork detection unit 51, a purchase history determination unit 52, a report presence / absence determination unit 53, and a reporting unit 54, which are functional blocks realized by a plug-in installed in the browser software.

[0088] The image extractor 50 extracts images from a website loaded by the browser software. Specifically, it scans the source code to obtain the path of the image file, and downloads the image file from the path. The image file is, for example, a jpg file, a png file, or a gif file.

[0089] The artwork detection unit 51 detects artwork managed by the artwork transaction and management system 1 by attempting to extract an image ID from the image extracted by the image extraction unit 50. That is, if an image is managed by the artwork transaction and management system 1, an image ID should be embedded in the image by the above-mentioned process, so if an image ID cannot be extracted here, it means that the image is not managed by the artwork transaction and management system 1. Conversely, if an image ID can be extracted, it means that the image is managed by the artwork transaction and management system 1. Therefore, the artwork detection unit 51 detects an image from which an image ID can be extracted as artwork, and supplies it to the purchase history determination unit 52 together with the extracted image ID.

[0090] The purchase history determination unit 52 determines whether or not a purchase transaction corresponding to the artwork detected by the artwork detection unit 51 exists in the blockchain network 7. Specifically, this determination is performed by determining whether or not there is a purchase transaction including the image ID extracted by the artwork detection unit 51. Artwork for which a corresponding purchase transaction does not exist in the blockchain network 7 has not been purchased and therefore cannot be used on a website. The fact that the artwork is used on a website despite this means that it is being used without permission. Therefore, the purchase history determination unit 52 decides to report artwork for which it has determined that a corresponding purchase transaction does not exist in the blockchain network 7, and notifies the report presence / absence determination unit 53 of the image ID.

[0091] The report presence / absence determination unit 53 determines whether or not a report transaction including the image ID notified by the purchase history determination unit 52 exists within the blockchain network 7. If such a report transaction exists within the blockchain network 7, it means that another third-party terminal 6 has previously discovered and reported the unauthorized use. Therefore, the report presence / absence determination unit 53 ends the processing without making a new report. On the other hand, if such a report transaction does not exist within the blockchain network 7, the report presence / absence determination unit 53 outputs the image ID to the reporting unit 54.

[0092] The reporting unit 54 generates a report indicating that unauthorized use of the artwork has been found for the image ID input from the report presence / absence determination unit 53, and issues a report transaction indicating the generated report to the blockchain network 7. After this, recording of the report transaction in the blockchain is completed by any of the miners connected to the blockchain network 7. The report transaction includes the image ID and information indicating the third party terminal 6. The information indicating the third party terminal 6 will be the payment destination when the platform portal server 3 later pays a reward for the report.

[0093] Next, referring to FIG. 8(b), the platform portal server 3 is configured to have a report acquisition unit 60, a remuneration amount determination unit 61, and a transmission unit 62 as functional blocks related to the payment of remuneration to the third party terminal 6.

[0094] The report acquisition unit 60 acquires newly issued report transactions from the blockchain network 7. This acquisition may be performed by the report acquisition unit 60 periodically checking the blockchain network 7.

[0095] The reward amount determination unit 61 determines the reward amount for the report transaction acquired by the report acquisition unit 60. In a typical example, the reward amount determination unit 61 determines the reward amount to be an amount equal to the price of the artwork minus the amount returned to the artist. For example, if the price of the artwork is 1 Ether and the amount returned to the artist is 90% of that amount, that is, 0.9 Ether, the reward amount is determined to be 0.1 Ether.

[0096] The transmission unit 62 transmits the virtual currency in the amount of the remuneration determined by the remuneration determination unit 61 to the third party terminal 6. This completes the payment of the remuneration.

[0097] Next, referring to FIG. 9, the platform portal server 3 is configured to have a receiving unit 70, a feature acquisition unit 71, a feature reading unit 72, an authenticity determination unit 73, and a transmitting unit 74 as functional blocks related to determining the authenticity of artwork.

[0098] The receiving unit 70 receives an authenticity determination request from the third party terminal 6. The authenticity determination request includes an artwork (hereinafter referred to as "artwork to be determined") that the third party terminal 6 found on a third party's WEB site, information (artist information) listed on the WEB site as the artist of the artwork to be determined, and information identifying an artwork (hereinafter referred to as "comparison artwork") that is one of the multiple artworks managed by the artwork transaction and management system 1. The information identifying the comparison artwork may be any information that can identify one of the multiple artworks managed by the artwork transaction and management system 1, for example, an image ID. Unlike the artwork detected by the artwork detection unit 51 in FIG. 8(a), the artwork to be determined may also include one that does not include an image ID.

[0099] The feature acquisition unit 71 acquires the above-mentioned artist feature and artwork feature based on the artwork to be judged. Specifically, the above-mentioned one or more values ​​(for example, the average value and variance of the pen speed, the average value and variance of the pen pressure, the average value and variance of the pen angle data, and the temporal distribution of the touch state and the hover state) are acquired from one or more stroke data constituting the artwork to be judged, and input them to the above-mentioned machine learning model. As a result, the artist feature is output from the machine learning model. In addition, the artwork feature is acquired by acquiring a plurality of values ​​indicating the characteristics of the artwork to be judged (for example, a series of pen touch coordinates each indicating the position of the pen when a pen touch is performed and a series of pen up coordinates each indicating the position of the pen when a pen up is performed) from one or more stroke data constituting the artwork to be judged.

[0100] The feature amount reading unit 72 reads out, from the feature amount database 3b, the artist feature amount stored in association with the artist indicated by the artist information, and the artwork feature amount stored in association with the comparison target artwork.

[0101] The authenticity determination unit 73 compares the artist features and artwork features acquired by the feature acquisition unit 71 with the artist features and artwork features read by the feature reading unit 72, and determines the authenticity of the artwork to be determined based on the results. Specifically, it calculates the likelihood of each of the artist features and artwork features by a predetermined calculation, and determines that the artwork to be determined is genuine if both of the calculated two likelihoods are equal to or greater than a predetermined value, and determines that the artwork to be determined is fake if either of the calculated two likelihoods is less than the predetermined value.

[0102] The transmission unit 74 returns the result of the judgment made by the authenticity judgment unit 73 to the third party terminal 6. This allows the user of the third party terminal 6 to know whether the artwork to be judged is genuine or fake.

[0103] 12 to 17, 19, and 20 are process flow diagrams showing the processing executed by the platform portal server 3. Also, Fig. 18 is a process flow diagram showing the processing executed by the third party terminal 6. Below, the processing executed by the platform portal server 3 will be explained in more detail with reference to these diagrams.

[0104] 12, the platform portal server 3 first performs a process of generating an account (contract account) on the blockchain network 7 so that the listing and purchase of artwork can be recorded on the blockchain network 7. Specifically, the platform portal server 3 sends a transaction including a contract code to the blockchain network 7 (step S1), and obtains the address of the contract account generated as a result (step S2).

[0105] Thereafter, the platform portal server 3 repeatedly executes a process of determining whether or not an artwork listing has been received from the artist terminal 4 (step S3), a process of determining whether or not an artwork purchase request has been received from the buyer terminal 5 (step S4), a process of checking whether or not a report of fraudulent use has been recorded in the blockchain network 7 (step S5), and a process of determining whether or not a request to determine the authenticity of the artwork has been received from the third-party terminal 6 (step S6).

[0106] If it is determined in step S3 that an artwork listing has been received, the platform portal server 3 executes an artwork listing process (step S7). If it is determined in step S4 that an artwork purchase request has been received, the platform portal server 3 executes an artwork sales process (step S8). If it is determined in step S5 that a fraudulent use discovery report has been recorded, the platform portal server 3 executes a reward payment process (step S9). If it is determined in step S6 that a request to determine the authenticity of the artwork has been received, the platform portal server 3 executes an authenticity determination process (step S10).

[0107] Fig. 13 is a diagram showing details of the artwork listing process executed in step S7 of Fig. 12. As shown in the figure, the platform portal server 3, which has started the artwork listing process, acquires the artwork listing including the artwork itself and the sales conditions (step S11). Then, the uploaded artwork is compared with known artworks (step S12). The details of this comparison are as described above.

[0108] Based on the result of the comparison performed in step S12, the platform portal server 3 judges whether the artwork is unique or not (step S13). As a result, if it is judged not to be unique, the platform portal server 3 returns a notice to the artist terminal 4 that the artwork cannot be exhibited, and ends the artwork exhibiting process (step S14). On the other hand, if it is judged to be unique, the platform portal server 3 receives the biometric signature data from the artist terminal 4 (step S15). In a specific example, a screen prompting the artist to sign is displayed on the display of the artist terminal 4, and the artist is prompted to input the dynamic signature data described above. The artist terminal 4 generates biometric signature data by adding each piece of information described with reference to FIG. 4 to the dynamic signature data thus input, and transmits the biometric signature data to the platform portal server 3.

[0109] Next, the platform portal server 3 acquires the artist feature and the artwork feature by the above-mentioned process and stores them in the feature database 3b (step S16), and then generates a pair of the public key 1 and the private key 1 (step S17). It also generates the data encryption key 1 and encrypts it using the public key 1 (step S18).

[0110] Next, the platform portal server 3 encrypts the artwork using the data encryption key 1 (step S19), and stores the encrypted artwork in the distributed file system 8 (step S20). After that, the platform portal server 3 issues a listing transaction including the hash value of the encrypted artwork, the biometric signature data, and the public key 1 to the contract account generated in steps S1 and S2 of Fig. 12 (step S21).

[0111] After executing step S20, the platform portal server 3 stores the pair of public key 1 and private key 1 and the data encryption key 1 encrypted in step S17 in the secure key store 3a in association with the ID of the issued listing transaction (step S22).Then, the platform portal server 3 returns the listing transaction ID and private key 1 to the artist terminal 4 (step S23), and registers the artwork thumbnail, sales conditions, and listing transaction ID in association with each other in the catalog database 9 (step S24), and ends the artwork listing process.

[0112] Figures 14 and 15 are diagrams showing details of the artwork sales process executed in step S8 in Figure 12. As shown in these figures, the platform portal server 3, which has started the artwork sales process, acquires a purchase offer including the artwork selection result in the catalog database 9, purchaser information, and price (step S30). Then, it reads the sales conditions and the listing transaction ID from the catalog database 9 (step S31), and judges whether the purchase offer is successful or not (step S32). The details of this judgment are as described above.

[0113] If it is determined in step S32 that the purchase has not been completed, the platform portal server 3 returns a notice of purchase failure to the purchaser terminal 5, and terminates the artwork sales process (step S33). On the other hand, if it is determined that the purchase has been completed, the platform portal server 3 first reads out the private key 1 and the encrypted data encryption key 1 from the secure key store 3a based on the listing transaction ID (step S34), and uses the read out private key 1 to decrypt the read out encrypted data encryption key 1 (step S35).

[0114] Next, the platform portal server 3 acquires a hash value of the encrypted artwork by referring to the listing transaction in the blockchain network 7 (step S36). Then, based on the acquired hash value, the encrypted artwork is read from the distributed file system 8, and decrypted with the data encryption key 1 acquired in step S35 (step S37).

[0115] Next, the platform portal server 3 generates a pair of public key 2 and private key 2 (step S38), and issues a purchase transaction including the purchaser information, the selling transaction ID, the amount, and the public key 2 to the contract account generated in steps S1 and S2 of FIG.

[0116] Next, the platform portal server 3 generates a watermark from the ID of the purchase transaction (step S40), and executes a watermark embedding process for embedding the generated watermark in the artwork (step S41).

[0117] Fig. 16 is a diagram showing details of the watermark embedding process executed in step S41 of Fig. 14. Note that in the following description, it is assumed that the watermark is a QR code (registered trademark). Fig. 16 also shows an example of an approach using singular value decomposition (SVD: Singular Value Decomposition) (SVD Based Approach), but the watermark embedding process may be performed using other approaches. Examples of such approaches include an approach using discrete cosine transform (DCT: Discrete Cosine Transform) (Optimal DCT-Psychovisual Threshold), an approach using encoding in the YCbCr color space (YCbCr Colour Space Encoding Approach), and an approach using multi-resolution analysis (Multi-resolution Wavelet Decomposition).

[0118] As shown in FIG. 16, the platform portal server 3 first generates a watermark, an n×n-bit QR code (registered trademark) W=(w1, w2, . . . , w n×n ) is obtained (step S50). n×n Each of these has a value of either 0 or 1.

[0119] Next, the platform portal server 3 acquires a predetermined robustness factor σ (step S51). The robustness factor σ is a value that increases the restorability of the embedded QR code (registered trademark) as it increases, but also decreases the image quality of the watermarked artwork as it increases. Therefore, it is preferable to determine an optimal σ value in advance, taking into consideration the restorability of the QR code (registered trademark) and the image quality of the watermarked artwork.

[0120] Next, the platform portal server 3 separates the m×m-bit artwork into three images I1, I2, and I3 by color channel (e.g., red, green, and blue in the RGB color model) (step S52). Then, the image with the highest entropy (i.e., the most homogeneous and least variable image) is selected from the images I1, I2, and I3 (step S53). Here, the explanation will be continued assuming that image I1 has the highest entropy and is therefore selected in step S53.

[0121] The platform portal server 3 that has selected the image I1 divides the image I1 into non-overlapping blocks B(j) of 4×4 bits each (step S54), where 1≦j≦(m / 4)×(m / 4).

[0122] Next, the platform portal server 3 uses a predetermined seed to generate a sequence of n × n pseudorandom numbers P = (p1, p2, . . . , p n×n ) is generated (step S55). k ≦(m / 4)×(m / 4).Then, the platform portal server 3 executes the processes of steps S57 to S60 for each integer k that is equal to or greater than 1 and equal to or less than n×n (step S56).

[0123] To explain the process of steps S57 to S60 in detail, the platform portal server 3 first k The th block B(p k ) (step S57). Next, the platform portal server 3 selects the selected block B(p k ) is obtained by singular value decomposition of the 4×4 diagonal matrix S(p k )=diag(s1,s2,s3,s4) is obtained (step S58). k )=U(p k )S(p k )V(p k ) T where U(p k ) and V(pk ) are each 4×4 unitary matrices.

[0124] And the robustness factor σ and the bit w k Using this diagonal matrix S(p k ) to obtain the 4×4 diagonal matrix S'(p k ) = diag(s1,s2+σ×w k , s2, s3 × 0.1) is derived (step S59). k ) to perform the inverse process of singular value decomposition to obtain WB(p k ) is generated (step S60). k )=U(p k )S'(p k )V(p k ) T By calculating WB(p k )

[0125] After all the processes of steps S57 to S60 are completed, the platform portal server 3 generates an image I1' (step S61) using the generated n×n WB(j) and the (m / 4)×(m / 4)-n×n blocks B(j) that were not selected in step S57. Specifically, of the (m / 4)×(m / 4) blocks B(j) that constitute the image I1, n×n blocks B(p1) to B(p n×n ) are WB(p1)~WB(p n×n ) to generate image I1'.

[0126] Finally, the platform portal server 3 generates a watermarked artwork using the image I1' and the images I2 and I3 (step S62). Specifically, the watermarked artwork is generated by synthesizing the images I1', I2, and I3.

[0127] Returning to Fig. 14, after completing the watermark embedding process, the platform portal server 3 generates a data encryption key 2 and encrypts it using the public key 2 (step S42). Then, as shown in Fig. 15, the pair of the public key 2 and the private key 2 and the encrypted data encryption key 2 are stored in the secure key store 3a in association with the ID of the purchase transaction (step S43).

[0128] Next, the platform portal server 3 encrypts the watermarked artwork using the data encryption key 2 (step S44), and stores the encrypted watermarked artwork in the distributed file system 8 (step S45). Thereafter, the platform portal server 3 returns the hash value of the encrypted watermarked artwork, the purchase transaction ID, and the private key 2 to the purchaser terminal 5 (step S46), and also returns the purchase transaction ID and a portion of the sales proceeds to the artist terminal 4 (step S47). Then, the remaining portion of the sales proceeds is stored in the incentive pool 3c (step S48), and the artwork sales process is terminated.

[0129] Here, the watermark reading process for reading a watermark from watermarked artwork will be described with reference to Fig. 17. Fig. 17 shows the process for reading a watermark from watermarked artwork generated by the watermark embedding process shown in Fig. 16, but it goes without saying that if the watermarked artwork is generated by another type of watermark reading process, a reading process corresponding to that process is required. Also, although the following description will be given assuming that the platform portal server 3 performs the watermark reading process, the watermark reading process may be performed by another computer.

[0130] First, the platform portal server 3 acquires a predetermined robustness factor σ (step S71). This robustness factor σ is preferably the same value as the robustness factor σ acquired in step S51 of FIG.

[0131] Next, the platform portal server 3 separates the m×m-bit watermarked artwork into three images I1, I2, and I3 for each color channel (step S71). Then, the image with the highest entropy is selected from the images I1, I2, and I3 (step S72). The processes of steps S71 and S72 are the same as those of steps S52 and S53 in Fig. 16. Here again, it is assumed that image I1 has the highest entropy and is selected in step S72.

[0132] The platform portal server 3 that has selected the image I1 divides the image I1 into non-overlapping blocks B(j) of 4×4 bits each (step S73), where 1≦j≦(m / 4)×(m / 4). This process is the same as step S54 in FIG.

[0133] Next, the platform portal server 3 uses a predetermined seed to generate a sequence of n × n pseudorandom numbers P = (p1, p2, . . . , p n×n ) is generated (step S74). k ≦(m / 4)×(m / 4). The predetermined seed used in step S74 must be the same as the seed used in step S55 of Fig. 16. The QR Code cannot be read without knowing the seed, so the seed also functions as a kind of common key.

[0134] Next, the platform portal server 3 executes the processes of steps S76 to S79 ​​for each integer k that is equal to or greater than 1 and equal to or less than n×n (step S75).

[0135] To explain the process of steps S76 to S79 ​​in detail, the platform portal server 3 first k The th block B(p k ) (step S76). Next, the platform portal server 3 selects the selected block B(p k ) is obtained by singular value decomposition of the 4×4 diagonal matrix S'(p k)=diag(s1,s2',s3',s4') is obtained (step S77). This singular value decomposition is similar to step S58 in FIG. k )=U(p k )S'(p k )V(p k ) T It is expressed by:

[0136] Next, the platform portal server 3 derives s2'-s3' (step S78). The value thus derived is the diagonal matrix S'(p k ) is derived, σ×w k Therefore, the platform portal server 3 determines whether the derived value is equal to or greater than σ / 2 (σ×w k ≧σ / 2) if w k Set 1 to w otherwise k (step S79). k is read out.

[0137] When all the processes in steps S76 to S79 ​​are completed, the platform portal server 3 reads out n×n w k Based on this, we create an n × n bit QR code W = (w1, w2, . . . , w n×n ) is obtained (step S80). This completes the reading of the QR code (registered trademark) W, which is the watermark.

[0138] FIG. 18 is a diagram showing details of the fraudulent use monitoring process executed by a plug-in installed in the browser software of the third party terminal 6 as a prerequisite for the reward payment process executed in step S9 of FIG. 12. As shown in the figure, the plug-in first determines whether a WEB site has been loaded (step S90), and if it is determined that the WEB site has been loaded, extracts images from the loaded WEB site (step S91). Then, it determines whether the extracted images include unconfirmed images (i.e., images that have not been the subject of the processes in steps S93 to S101 described later) (step S92). If it is determined in step S90 that the WEB site has not been loaded, or if it is determined in step S92 that there are no unconfirmed images, the plug-in returns to step S90 and repeats the process.

[0139] If the plug-in determines in step S92 that there are unconfirmed images, it executes the processes of steps S94 to S101 for each of the one or more unconfirmed images (step S93).

[0140] Specifically, the plug-in first extracts an image ID from the image (step S94). If the image ID cannot be extracted, the plug-in moves the process to the next image. On the other hand, if the image ID can be extracted, the plug-in refers to the blockchain network 7 and checks whether or not there is a purchase contract (purchase transaction) that includes the extracted image ID (step S96). Then, based on the result of the check, it is determined whether or not there is a purchase contract that includes the extracted image ID (step S97).

[0141] If the plug-in determines in step S97 that a purchase contract exists, it moves on to the next image. On the other hand, if the plug-in determines in step S97 that a purchase contract does not exist, it first blocks the site from being displayed (step S98). This blocking can be done, for example, by displaying a warning message that covers the entire screen of the browser software.

[0142] Next, the plug-in refers to the blockchain network 7 and checks whether there is a fraudulent use report (report transaction) corresponding to the image ID extracted in step S94 (step S99). Then, based on the result of the check, it determines whether there is a fraudulent use report including the image ID extracted in step S94 (step S100).

[0143] If the plug-in determines in step S100 that there is a report of unauthorized use, it moves on to the next image without making a new report. On the other hand, if the plug-in determines in step S100 that there is no report of unauthorized use, it issues a report transaction including the image ID, the address and content of the relevant website, and the date the unauthorized use was discovered to the contract account created in steps S1 and S2 of FIG. 12 (step S101), and moves on to the next image. After the above processing is completed for all of one or more unconfirmed images, the plug-in returns to step S90 and continues processing. As a result, the plug-in continues to monitor unauthorized use of the artwork while the browser software is running on the third-party terminal 6.

[0144] Fig. 19 is a diagram showing details of the reward payment process executed in step S9 of Fig. 12. As shown in the figure, the platform portal server 3 that has started the reward payment process retrieves and refers to the newly recorded report transaction from the blockchain network 7 to identify the third-party terminal 6 and the image ID (step S110).

[0145] Next, the platform portal server 3 withdraws the virtual currency corresponding to the identified image ID from the incentive pool 3c (step S111). The method for calculating the amount of virtual currency to be withdrawn is as described above. Finally, the platform portal server 3 transmits the virtual currency withdrawn in step S111 to the third-party terminal identified in step S110 (step S112), and ends the reward payment process.

[0146] Fig. 20 is a diagram showing details of the authenticity determination process executed in step S10 of Fig. 12. As shown in the figure, the platform portal server 3 that starts the authenticity determination process first obtains information specifying the artwork to be determined, artist information, and the artwork to be compared from the authenticity determination request (step S120). The contents of this information are as described above.

[0147] Next, the platform portal server 3 acquires the above-mentioned artist characteristics and artwork characteristics for the artwork to be judged (step S121), and further reads out artist characteristics corresponding to the artist information from the feature database 3b (step S122), and reads out artwork characteristics corresponding to the artwork to be compared from the feature database 3b (step S123).

[0148] Thereafter, the platform portal server 3 determines the authenticity of the artwork to be judged by comparing the artist features and the artwork features (step S124), returns the result of the judgment to the third-party terminal 6 (step S125), and terminates the authenticity judgment process.

[0149] As described above, according to the artwork transaction and management system 1 of this embodiment, the plug-in of the browser software of the third-party terminal 6 automatically detects and reports any unauthorized use of artwork on a website, making it possible to prevent unauthorized reproduction (use) of artwork while ensuring accessibility to the artwork.

[0150] Furthermore, since a reward can be given to the third party terminal 6 that generates a report, it becomes possible to give an incentive to the owner of the third party terminal 6 for continuing to operate the plug-in of the present invention.

[0151] Furthermore, since the third party terminal 6 issues a report transaction after checking whether or not a report transaction for the same image ID already exists, it is possible to prevent a large number of report transactions from occurring.

[0152] In addition, the artist characteristics and artwork characteristics of the artwork put up for sale are acquired and stored in a characteristics database, making it possible to later determine the authenticity of artworks circulating on the market.

[0153] Although the preferred embodiments of the present invention have been described above, the present invention is not limited to these embodiments, and it goes without saying that the present invention can be embodied in various forms without departing from the spirit of the present invention.

[0154] For example, artist features may be added to the artwork as metadata indicating the artist's fingerprint, which may be performed by, for example, the feature acquisition unit 13 shown in FIG.

[0155] In the above embodiment, an example has been described in which a watermark is generated based on a purchase transaction ID, but a watermark may be generated based on artist characteristics or artwork characteristics and embedded in the artwork to be transmitted to the purchaser terminal 5 in place of or together with a watermark based on a purchase transaction ID. The generation of a watermark based on artist characteristics or artwork characteristics may be performed, for example, by the watermark generation unit 36 ​​shown in Fig. 7. The embedding of the generated watermark may be performed, for example, by the watermark embedding processing unit 37 shown in Fig. 7. [Explanation of symbols]

[0156] 1. Artwork transaction management system 2 Network 3 Platform Portal Server 3a Secure Key Store 3b Feature database 3c Incentive Pool 4 Artist terminal 5. Purchaser terminal 6. Third Party Terminals 7. Blockchain Network 8 Distributed File Systems 9 Catalog Database 11,30,70 Receiver 12 Duplication determination section 13 Feature acquisition unit 14 Artwork encryption processing section 15 Artwork storage processing unit 16 Key Pair Generation Unit 17 Transaction Issuer 18 Key encryption processing unit 19 Catalog Generation Department 20,41,62,74 Transmitter 31 Purchase Eligibility Determination Department 32 Key decryption processing unit 33 Artwork Decoding Processing Unit 34 Key Pair Generation Unit 35 Transaction Issuer 36 Watermark Generation Unit 37 Watermark embedding processing section 38 Artwork encryption processing unit 39 Artwork storage processing unit 40 Key encryption processing unit 50 Image Extraction Section 51 Artwork detection section 52 Purchase history determination unit 53 Report status determination unit 54 Reporting Department 60 Report acquisition department 61 Remuneration Determination Department 71 Feature acquisition unit 72 Feature Readout Unit 73 Authenticity Determination Department 100 Computers 101 CPU 102 Storage device 103 Input Device 104 Output Device 105 Communication equipment P-Pen θ Azimuth σ Robustness factor φ Tilt angle ψ Rotation angle

Claims

1. inputting one or more values ​​related to stroke data associated with an artist's artwork into a machine learning model that is generated based on training an artificial intelligence program on one or more values ​​characteristic of the artist's artwork creation; outputting an artist feature value indicating characteristics of artwork created by the artist from the machine learning model; The one or more values ​​relate to at least one of a writing speed, a writing pressure value, pen angle data, and a temporal distribution of a touch state and a hover state. computer.

2. the artwork is associated with a set of pen touch coordinates indicating locations of pen touches and a set of pen up coordinates indicating locations of pen ups; outputting an artwork feature quantity indicating a feature of the artwork; the artwork feature includes the series of pen touch coordinates and the series of pen up coordinates; The computer of claim 1.

3. embedding a watermark indicative of the artwork feature in the artwork; The computer of claim 2.

4. 1. A computer-implemented method comprising: The computer includes: inputting one or more values ​​for stroke data associated with the artist's artwork into a machine learning model that is generated based on training an artificial intelligence program on one or more values ​​characteristic of the artist's artwork; outputting an artist feature value indicating characteristics of artwork created by the artist from the machine learning model; The one or more values ​​relate to at least one of a writing speed, a writing pressure value, pen angle data, and a temporal distribution of a touch state and a hover state. method.

5. the artwork is associated with a set of pen touch coordinates indicating locations of pen touches and a set of pen up coordinates indicating locations of pen ups; The computer outputs artwork feature quantities indicating characteristics of the artwork; the artwork feature includes the series of pen touch coordinates and the series of pen up coordinates; The method according to claim 4.

6. The computer embeds a watermark indicating the artwork feature amount in the artwork. The method according to claim 5.

7. inputting one or more values ​​for stroke data associated with the artist's artwork into a machine learning model that is generated based on training an artificial intelligence program on one or more values ​​characteristic of the artist's artwork; outputting an artist feature value indicating characteristics of artwork production by the artist from the machine learning model; A program for causing a computer to execute a process, The one or more values ​​relate to at least one of a writing speed, a writing pressure value, pen angle data, and a temporal distribution of a touch state and a hover state. program.

8. the artwork is associated with a set of pen touch coordinates indicating locations of pen touches and a set of pen up coordinates indicating locations of pen ups; further causing the computer to execute a process of outputting artwork feature quantities indicating features of the artwork; the artwork feature includes the series of pen touch coordinates and the series of pen up coordinates; The program according to claim 7.

9. and further causing the computer to execute a process of embedding a watermark indicative of the artwork feature amount into the artwork. The program according to claim 8.

Images