A computer device and a method for evaluating a Non-Fungible Token or a Fungible Token

Abstract

A method and device 10 for evaluating a Non-Fungible Token or a Fungible Token, comprises a processor 12 comprising an evaluation circuitry 16 which receives a first factor relating to market exposure

Description

The present disclosure relates to a computer device and a method for evaluating a Non-Fungible Token or a Fungible Token and a method for cryptographically authenticating information for evaluating a Non-Fungible Token or a Fungible Token. Background Blockchain technology has witnessed significant adoption across various industries, facilitating transparent and secure transactions through decentralised networks. Non-Fungible Tokens (NFTs) have emerged as a prominent application of blockchain technology, representing unique digital assets with distinct characteristics and ownership rights. However, the evaluation of NFTs by a computer network poses challenges due to the diverse nature of underlying assets and the need for accurate valuation methodologies. Existing computer systems for NFT evaluation often lack efficiency and fail to provide robust cybersecurity measures, leaving stakeholders vulnerable to data breaches and ownership disputes. Furthermore, the fragmentation of NFT ownership raises concerns regarding intellectual property (IP) protection and ownership rights. In essence, while NFTs hold immense promise as a novel form of digital asset, their evaluation and secure management by a computer network present significant hurdles that must be addressed to ensure the integrity, security, and trustworthiness of the blockchain ecosystem. Summary of the invention Aspects of the invention are as set out in the independent claims and optional features are set out in the dependent claims. Aspects of the invention may be provided in conjunction with each other and features of one aspect may be applied to other aspects. A first aspect of the disclosure provides a computer device for evaluating a Non-Fungible Token or a Fungible Token, comprising a processor comprising an evaluation circuitry configured to receive a first factor fmarket relating to market exposure to a cryptocurrency systematic risk, receive a second factor fcommunity relating to an effective community size, receive a third factor fstreaming relating to effective streaming data, receive a fourth factor fcashfiow relating to effective cash flow, receive a fifth factor futility relating to a utility, wherein the utility relates to a membership or a ticket for a token owner, determine a value of the Non-Fungible Token based on the first to fifth factors, or determine a value of the Fungible Token based on the first, second and fifth factors. Embodiments of the disclosure allow the computer device to overcome the problems of existing evaluation computer devices, for example: (1) From the NFT mainstream evaluation factors, it’s significant that evaluation methods mixed the evaluation factors of financial assets, art collectibles and utility coupons. For NFTs functioning as utility coupons or with similar accurate functionalities, the evaluation is clear and mature. But as other assets, these factors show the immaturity of a large proportion of nowadays’ NFTs. (2) The existing evaluation factors failed to deliver the reflection of the subjective value, which play an extremely crucial role in nowadays’ NFT as well as future NFT. For instance, art NFT’s aesthetic value cannot be demonstrated; the supportive and spiritual linkages between artists and fans are main value of a large proportion of music NFT; the community value and social value of NFT are strong and very subjective but missing in the factors. (3) From the vision and logics of NFT’s massive adoption within the general public, most of the NFTs are only valued, circulated and accepted within related small communities. As currency cryptocurrency’s success require massive adoption of a large number of users, but success of a series of NFTs merely require the acceptance within a relatively small and unique community. To certain extend, for the majority of the nowadays’ NFT, the liquidity of NFTs highly depends on the liquidity providers of a certain smart community with unique value and aesthetic. The liquidity is very limited. (4) Tangibility is only ‘realized’ through the on-chain verifiable ownership transactions, which is separated from the IP (copyright) of underlying assets (paintings and music). For IP related NFT (a large proportion of high-value NFTs) especially music, without IP protection behind the NFT, the tangibility doesn’t exist. (5) As the first factor—Scarcity itself has no fundamental value. (6) For the factor of future value (future cash value), ironically for most of the art NFT related to the IP (copyright), the NFTs are separately from the cash flow generated by the artwork, such as music and paintings. (7) According to point 4, there may be a significant risk that all other factors won’t exist if the factor of the tangibility (the ownership of IP (copyright)) cannot be ensured. (8) All of the factors are temporally appropriate for the nowadays’ NFT genre, in the vision of the massive adoption in the future the factors and evaluation methods may continue changing. It would be understood that based on these received factors, the computer device comprising a processor comprising the evaluation circuitry may be configured to propose a multifaceted approach to maximize the value of music NFTs. Firstly, by applying financial and investment theories, these digital assets may be elevated to greater profitability within the evolving market landscape. Secondly, through the implementation of psychological reward mechanisms, particularly gamification, the subjective value of NFTs and music may be directly amplified, appealing to collectors and enthusiasts on a deeper level. Lastly, leveraging the utility of music NFTs as both functional tools and instruments for creating scarcity and exclusivity further may enhance their intrinsic value, establishing them as highly desirable assets within the digital and creative realms. Optionally, the evaluation circuitry may be further configured to determine a variable a of the Non-Fungible Token or the Fungible Token based on value added via auction and promotion from an independent market.. Optionally, the factors may be adjusted by sensitivity / 3 dynamically determined by the marketing data’s linear regression. In one example, if it is p of fmarket, it determines the exposure of a market risk or a systematic risk. In some examples, a bundle of weighted-average crypto currencies is used, which can be analogous to the SP500 ETF and can represent US stock market risk or systematic risk. Optionally, the first factor fmarket may be calibrated by a proportion variable yi adjusted by derivative hedging. Optionally, the proportion variable yi may decide the percentage exposure to the sensitivity pi of the first factor fmarket. Optionally, the evaluation circuitry may be configured to receive input data relating to the derivative hedging from CVI, Cryptocurrecy volatility index, API. For calculating the fmarket, VIX may represent a part of crypto market systematic risk, but not all. Normally Coinbase or Binance cryptocurrency market index may be used to hedge the total risk. But the dynamic hedging model may not be only based on hedging the total crypto market systematic risk, but decomposite the hedging into two parts: hedging VIX, hedging the average-weighted cryptomarket index: fmarket- fvix+ frest market risk, wherein it hedges fwxto hedge corresponding part of systematic risk in dynamic hedging part. Optionally, the evaluation circuitry may be configured to receive the first factor fmarket through Coinbase or Binance cryptocurrency market index API, preferably future price data API. Optionally, the evaluation circuitry may be configured to receive the second factor fcommunity through internal API and Discord API. Optionally, the evaluation circuitry may be configured to receive the third factor / streaming through Spotify and Youtube API. Optionally, the evaluation circuitry may be configured to receive the fourth factor fcashfiow through internal API. A second aspect of the disclosure provides a method for evaluating a Non-Fungible Token or a Fungible Token by an evaluation circuitry of a processor of a computer device, comprising receiving a first factor fmarket relating to market exposure to a cryptocurrency systematic risk, receiving a second factor fcommunity relating to an effective community size, receiving a third factor fstreaming relating to effective streaming data, receiving a fourth factor fcashtiow relating to effective cash flow, receiving a fifth factor futility relating to a utility, wherein the utility relates to a membership or a ticket for a token owner; determining a value of the Non-Fungible Token based on the first to fifth factors, or determining a value of the Fungible Token based on the first, second and fifth factors. Embodiments of the disclosure allow the method to overcome the problems of existing evaluation methods, for example: (1) From the NFT mainstream evaluation factors, it’s significant that evaluation methods mixed the evaluation factors of financial assets, art collectibles and utility coupons. For NFTs functioning as utility coupons or with similar accurate functionalities, the evaluation is clear and mature. But as other assets, these factors show the immaturity of a large proportion of nowadays’ NFTs. (2) The existing evaluation factors failed to deliver the reflection of the subjective value, which play an extremely crucial role in nowadays’ NFT as well as future NFT. For instance, art NFT’s aesthetic value cannot be demonstrated; The supportive and spiritual linkages between artists and fans are main value of a large proportion of music NFT; The community value and social value of NFT are strong and very subjective but missing in the factors. (3) From the vision and logics of NFT’s massive adoption within the general public, most of the NFTs are only valued, circulated and accepted within related small communities. As currency cryptocurrency’s success require massive adoption of a large number of users, but success of a series of NFTs merely require the acceptance within a relatively small and unique community. To certain extend, for the majority of the nowadays’ NFT, the liquidity of NFTs highly depends on the liquidity providers of a certain smart community with unique value and aesthetic. The liquidity is very limited. (4) Tangibility is only ‘realized’ through the on-chain verifiable ownership transactions, which is separated from the IP(copyright) of underlying assets(paintings and music). For IP related NFT (a large proportion of high-value NFTs) especially music, without IP protection behind the NFT, the tangibility doesn’t exist. (5) As the first factor—Scarcity itself has no fundamental value. (6) For the factor of future value (future cash value), ironically for most of the art NFT related to the IP (copyright), the NFTs are separately from the cash flow generated by the artwork, such as music and paintings. (7) According to point 4, there may be a significant risk that all other factors won’t exist if the factor of the tangibility (the ownership of IP (copyright)) cannot be ensured. (8) All of the factors are temporally appropriate for the nowadays’ NFT genre, in the vision of the massive adoption in the future the factors and evaluation methods may continue changing. It would be understood that based on these received factors, the methods may propose a multifaceted approach to maximize the value of music NFTs. Firstly, by applying financial and investment theories, these digital assets may be elevated to greater profitability within the evolving market landscape. Secondly, through the implementation of psychological reward mechanisms, particularly gamification, the subjective value of NFTs and music may be directly amplified, appealing to collectors and enthusiasts on a deeper level. Lastly, leveraging the utility of music NFTs as both functional tools and instruments for creating scarcity and exclusivity further may enhance their intrinsic value, establishing them as highly desirable assets within the digital and creative realms. Optionally, determining a variable a of the Non-Fungible Token or the Fungible Token may be further based on value added via auction and promotion from an independent market. Optionally, the factors may be adjusted by sensitivity / 3 dynamically determined by the marketing data’s linear regression. Optionally, the first factor fmarket may be calibrated by a proportion variable yi adjusted by derivative hedging. Optionally, the proportion variable y? may decide the percentage exposure to the sensitivity / 3i of the first factor fmarket. Optionally, the method may further comprise receiving input data relating to the derivative hedging from CVI, Cryptocurrecy volatility index, API. For calculating the fmarket, VIX may represent a part of crypto market systematic risk, but not all. Normally Coinbase or Binance cryptocurrency market index may be used to hedge the total risk. But the dynamic hedging model may not be only based on hedging the total crypto market systematic risk, but decomposite the hedging into two parts: hedging VIX, hedging the average-weighted cryptomarket index: fmarket= fvix+ frest market risk, wherein it hedges fwxto hedge corresponding part of systematic risk in dynamic hedging part. Optionally, the receiving the first factor fmarket may comprise receiving the first factor fmarket through Coinbase or Binance cryptocurrency market index API, preferably future price data API. Optionally, the receiving the second factor fcommunity may comprise receiving the second factor through internal API and Discord API. Optionally, the receiving the third factor fstreaming may comprise receiving the third factor through Spotify and Youtube API. Optionally, the receiving the fourth factor fcash now may comprise receiving the fourth factor fcash flow through internal API. A third aspect of the disclosure provides a method for cryptographically authenticating information for the computer device and the method for evaluating a Non-Fungible Token or a Fungible Token, comprising: - inputting data including a message and a secret key KO; - creating HMAO, Hash Message Authentication Code, comprising - performing an operation KO XOR ipad, wherein ipad is block-sized inner padding; - appending the message to KO XOR ipad to obtain KO XOR ipad || message; - inputting KO XOR ipad || message into a hash function HASH to obtain HASH(K0 XOR ipad || message); - performing an operation KO XOR opad, wherein opad is block-sized outer padding; - obtaining (KO XOR opad) || (HASH (KO XOR ipad || message)); - obtaining HASH((K0 XOR opad) || (HASH (KO XOR ipad || message))). Embodiments of the disclosure allow the method or cryptographically authenticating information using HMAC (Hash Message Authentication Code) is an approach for creating digital signatures using different hash algorithms like MD5, SHA1, SHA256, SHA512, etc. HMAC is typically used for digital signatures (DA) which provides data Integrity and authentication. This is a unified approach for applying a digital signature with a private key. The utilization of HMAC presents a robust solution for ensuring data integrity and authenticity in diverse computing environments. HMAC offers significant advantages, including strong data integrity through unique authentication codes, resistance to tampering, authentication of message origin, computational efficiency, and versatility across different data types and communication protocols. By leveraging HMAC, organizations can fortify their data security measures, safeguarding against unauthorized access, tampering, and spoofing attacks, thereby enhancing trust and reliability in data transmission and storage systems. It will be appreciated that in cloud computing environments, HMAC may be employed to authenticate data exchanged between clients and servers, ensuring the integrity and confidentiality of sensitive information stored in remote servers. Within the context of financial transactions, HMAC may be integrated into payment processing systems to validate the authenticity of transaction requests and prevent fraudulent activities, bolstering the security of online banking and e-commerce platforms. Within the realm of loT (Internet of Things), HMAC may be applied to authenticate data transmitted between interconnected devices, ensuring the integrity of sensor data, command signals, and device communications in smart home, industrial automation, and automotive applications. Embodiments of the disclosure allow that the information hierarchy structure may be to realize the information structure for special information flow and governance. Encryption mechanism may be used for Cyber security to protect every part of the information communications between all parts of the system. Especially for the main hierarchy structure. Evaluation method may support intrinsic value determination, serving as reference price in auction or other market activities. Evaluation method may serve as an absolute value in fund / staking pool. Derivative dynamic hedging may exclude the cryptocurrency systematic risk and keep the token-specific risk for the evaluation, through the evaluation circuitry. For the fund / staking pool, derivative dynamic hedging may serve as a tactical opportunity to control the market systematic exposure, which may be decided by the fund / staking pool. Evaluation method and fund pool as well as tokenomics may decide the minting / issuing of the fungible token, for example the governance tokens, wherein tokenomics is a term that refers to the study and analysis of the economic aspects of a cryptocurrency or blockchain project, with a particular focus on the design and distribution of its native digital tokens All the factors in the equations and their corresponding changes may be penetrating through all parts of the system. The IP protection structure may protect the underlying assets of non-fungible tokens. Drawings Embodiments of the disclosure will now be described, by way of example only, with reference to the accompanying drawings, in which: Fig. 1 is an illustration of a diagram of an example of a computer device for evaluating a Non-Fungible Token or a Fungible Token. Fig. 2 is an illustration of a diagram of an example of a method for evaluating a Non-Fungible Token or a Fungible Token. Fig.3 is an illustration of a diagram of an example of a method for cryptographically authenticating information for evaluating a Non-Fungible Token or a Fungible Token. Fig. 4 is an illustration of a diagram of an example of a system for evaluating a Non-Fungible Token or a Fungible Token. Soecific description The following detailed description illustrates exemplary embodiments of the present disclosure and the ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practising the present disclosure are also possible. Fig. 1 is an illustration of a diagram of a first computer device for evaluating a Non-Fungible Token or a Fungible Token. The computer device 10 comprises a processor 12 and a memory 14. The processor comprises an evaluation circuitry 16 configured to receive factors via an interface 18. receive a first factor fmarket relating to market exposure to a cryptocurrency systematic risk, receive a second factor / community relating to an effective community size, receive a third factor fstreaming relating to effective streaming data, receive a fourth factor / cashflow relating to effective cash flow, receive a fifth factor futility relating to a utility, wherein the utility relates to a membership or a ticket for a token owner, determine a value of the Non-Fungible Token based on the first to fifth factors, or determine a value of the Fungible Token based on the first, second and fifth factors. It would be understood that based on these factors, the evaluation circuitry 16 may propose a multifaceted approach to maximize the value of music NFTs. Firstly, by applying financial and investment theories, these digital assets may be elevated to greater profitability within the evolving market landscape. Secondly, through the implementation of psychological reward mechanisms, particularly gamification, the subjective value of NFTs and music may be directly amplified, appealing to collectors and enthusiasts on a deeper level. Lastly, leveraging the utility of music NFTs as both functional tools and instruments for creating scarcity and exclusivity further may enhance their intrinsic value, establishing them as highly desirable assets within the digital and creative realms. The evaluation circuitry 16 of the processor 12 may be further configured to determine a variable a of the Non-Fungible Token or the Fungible Token based on value added via auction and promotion from an independent market. Optionally, the factors may be adjusted by sensitivity / 3 dynamically determined by the marketing data’s linear regression. Optionally, the first factor fmarket may be calibrated by a proportion variable yt adjusted by derivative hedging. Optionally, the proportion variable yi may decide the percentage exposure to the sensitivity Pi of the first factor fmarket. Optionally, the evaluation circuitry 16 of the processor 12 may be configured to receive input data relating to the derivative hedging from CVI, Cryptocurrecy volatility index, API. For calculating the fmarket, VIX may represent a part of crypto market systematic risk, but not all. Normally Coinbase or Binance cryptocurrency market index may be used to hedge the total risk. But the dynamic hedging model may not be only based on hedging the total crypto market systematic risk, but decomposite the hedging into two parts: hedging VIX, hedging the average-weighted cryptomarket index: fmarket= fvix+ frest market risk, wherein it hedges fwxto hedge corresponding part of systematic risk in dynamic hedging part. Optionally, the evaluation circuitry 16 of the processor 12 may be configured to receive the first factor fmarket through Coinbase or Binance cryptocurrency market index API, preferably future price data API. Optionally, the evaluation circuitry 16 of the processor 12 may be configured to receive the second factor fcommumty through internal API and Discord API. Optionally, the evaluation circuitry 16 of the processor 12 may be configured to receive the third factor fstreammg through Spotify and Youtube API. Optionally, the evaluation circuitry 16 of the processor 12 may be configured to receive the fourth factor fcashfiow through internal API. Fig. 2 is an illustration of a diagram of an example of a method for controlling a terminal device using a magnetoelectric converter. The method for evaluating a Non-Fungible Token or a Fungible Token comprises, in a computer device: receiving 101a first factor fmarket relating to market exposure to a cryptocurrency systematic risk, receiving 102 a second factor fcommunity relating to an effective community size, receiving 103 a third factor fstreammg relating to effective streaming data, receiving 104 a fourth factor fcashfiow relating to effective cash flow, receiving 105 a fifth factor futility relating to a utility, wherein the utility relates to a membership or a ticket for a token owner; determining 106 a value of the Non-Fungible Token based on the first to fifth factors, or determining a value of the Fungible Token based on the first, second and fifth factors. It would be understood that based on these factors, the methods may propose a multifaceted approach to maximize the value of music NFTs. Firstly, by applying financial and investment theories, these digital assets may be elevated to greater profitability within the evolving market landscape. Secondly, by integrating psychological reward systems, especially through gamification, the perceived value of NFTs and music can be significantly heightened, captivating collectors and enthusiasts on a profound level. Lastly, leveraging the utility of music NFTs as both functional tools and instruments for creating scarcity and exclusivity further may enhance their intrinsic value, establishing them as highly desirable assets within the digital and creative realms. Optionally, determining 106 a variable a of the Non-Fungible Token or the Fungible Token may be further based on value added via auction and promotion from an independent market. Optionally, the factors may be adjusted by sensitivity dynamically determined by the marketing data’s linear regression. Optionally, the first factor fmarket may be calibrated by a proportion variable y? adjusted by derivative hedging. Optionally, the proportion variable y? may decide the percentage exposure to the sensitivity / 3i of the first factor fmarket. Optionally, the method may further comprise receiving input data relating to the derivative hedging from CVI, Cryptocurrecy volatility index, API. For calculating the fmarket, VIX may represent a part of crypto market systematic risk, but not all. Normally Coinbase or Binance cryptocurrency market index may be used to hedge the total risk. But the dynamic hedging model may not be only based on hedging the total crypto market systematic risk, but decomposite the hedging into two parts: hedging VIX, hedging the average-weighted cryptomarket index: fmarket= fvix+ frest market risk, wherein it hedges fwxto hedge corresponding part of systematic risk in dynamic hedging part. Optionally, the receiving the first factor fmarket may comprise receiving the first factor fmarket through Coinbase or Binance cryptocurrency market index API, preferably future price data API. Optionally, the receiving the second factor fcommunity may comprise receiving the second factor through internal API and Discord API. Optionally, the receiving the third factor fstreaming may comprise receiving the third factor through Spotify and Youtube API. Optionally, the receiving the fourth factor fcash now may comprise receiving the fourth factor fcash flow through internal API. Fig.3 is an illustration of a diagram of an example of a method for cryptographically authenticating information for evaluating a Non-Fungible Token or a Fungible Token. The method for cryptographically authenticating information comprises: - inputting 301 data including a message and a secret key KO; - creating 302 HMAC, Hash Message Authentication Code, comprising - performing 3021 an operation K0 XOR ipad, wherein ipad is block-sized inner padding; - appending 3022 the message to K0 XOR ipad to obtain K0 XOR ipad || message; - inputting 3023 K0 XOR ipad || message into a hash function HASH to obtain HASH(K0 XOR ipad || message); - performing 3024 an operation KO XOR opad, wherein opad is block-sized outer padding; - obtaining 3025 (KO XOR opad) || (HASH (KO XOR ipad || message)); - obtaining 3026 HASH((K0 XOR opad) || (HASH (KO XOR ipad || message))). Embodiments of the disclosure allow the method for cryptographically authenticating information using HMAC (Hash Message Authentication Code) to create digital signatures using different hash algorithms like MD5, SHA1, SHA256, SHA512, etc. HMAC is typically used for digital signatures (DA) which provides data Integrity and authentication. This is a unified approach for applying a digital signature with a private key. The utilization of HMAC presents a robust solution for ensuring data integrity and authenticity in diverse computing environments. HMAC offers significant advantages, including strong data integrity through unique authentication codes, resistance to tampering, authentication of message origin, computational efficiency, and versatility across different data types and communication protocols. By leveraging HMAC, organizations can fortify their data security measures, safeguarding against unauthorized access, tampering, and spoofing attacks, thereby enhancing trust and reliability in data transmission and storage systems. It will be appreciated that in cloud computing environments, HMAC may be employed to authenticate data exchanged between clients and servers, ensuring the integrity and confidentiality of sensitive information stored in remote servers. Within the context of financial transactions, HMAC may be integrated into payment processing systems to validate the authenticity of transaction requests and prevent fraudulent activities, bolstering the security of online banking and e-commerce platforms. Within the realm of loT (Internet of Things), HMAC may be applied to authenticate data transmitted between interconnected devices, ensuring the integrity of sensor data, command signals, and device communications in smart home, industrial automation, and automotive applications. Embodiments of the disclosure allow that the information hierarchy structure may be to realize the information structure for special information flow and governance. Encryption mechanism may be used for Cyber security to protect every part of the information communications between all parts of the system. Especially for the main hierarchy structure. Evaluation method may support intrinsic value determination, serving as reference price in auction or other market activities. Evaluation method may serve as an absolute value in fund / staking pool. Derivative dynamic hedging may exclude the cryptocurrency systematic risk and keep the token-specific risk for the evaluation, through the evaluation circuitry. For the fund / staking pool, derivative dynamic hedging may serve as a tactical opportunities to control the market systematic exposure, which may be decided by another 2 in fund / staking pool. Evaluation method and fund pool as well as tokenomics may decide the minting / issuing of the fungible token, for example the governance tokens. All the factors in the equations and their corresponding changes may be penetrating through all parts of the system. The IP protection structure may protect the underlying assets of non-fungible tokens. Example 1: key length <block size Input data: Message: “Hello” X48656C6C 6F Secret Key: “Key” -+ X4B6579 Constants for our case hash algorithm (SHA1) with block size 64 bytes: ipad (in HEX): X36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 (x36 repeated 64 time) opad (in HEX): X5C5C5C5C 56 / 5^356 / 5^3 5^35^35(356 / 56 / 5^35^35^3 5^35(35(35^3 56 / 5^35^35(3 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C (x5C repeated 64 time) Steps for creating HMAC comprise: 1. If the key length <block size, we need to add Os until the key length equals the block size. In our case, the key length is 3 bytes, and the block size is 64 bytes. So new key is KO = 4B657900 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 2. Performing the operation KO XOR ipad KO XOR ipad = 7D534F36 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 3. Now, we append the message to KO XOR ipad (KO XOR ipad) || message = 7D534F36 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 48656C6C 6F 4. Putting the result of the previous operation into the SHA-1 hash. You should input into the hash function: 7D534F3636363636363636363636363636363636363636363636363636363636 36363636363636363636363636363636363636363636363636363636363636364 8656C6C6F sha1(K0 XOR ipad || message) = 8e32567d57353a91515458d65b4cc7802450172c 5. Performing the operation KO XOR opad. KO XOR opad = 17392550 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 6. Appending to the result of the previous operation the hash obtained in step 4. (KO XOR opad) || (sha1(K0 XOR ipad || message)) = 17392550 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 8E32567D 57353A91 515458D6 5B4CC780 24501720 7. Putting the result of step 6 into the SHA-1 hash. HMAC = 173ac40fb6ac57cc7524594c523bea1bdd54836a Example 2: key length = block size Input data: Message: “Hello” X48656C6C 6F Secret Key: “4q72JHgX89z3BkFMt6cwQxL1rD28jpN5UfVhlZYPbCSeuGovRaWmA0sD9ECtX7Jf’ -+ X34713732 4A486758 38397A33 426B464D 74366377 51784C31 72443238 6A704E35 55665668 495A5950 62435365 75476F76 5261576D 41307344 39454374 58374A66 Constants for our case hash algorithm (SHA1) with block size 64 bytes: ipad (in HEX): X36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 (x36 repeated 64 time) opad (in HEX): X5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C cpcpcpcp cpcpcpcp cpcpcpcp cpcpcpcp cpcpcpEp rpcpcpcp cpcpcpep JL'JV'JU'JU ^ / ^^^- / ^^- / ^^- / \Jx- / vJ\- / \Jk / v / \- / xJVz\Jv^vJ\- / U\- / vJv / v- / k- / x- / \- / >-J\- / 5C5C5C5C 5C5C5C5C 5C5C5C5C (x5C repeated 64 time) Steps for creating HMAC comprise: 1. If the key length = block size, then we do nothing. In our case, with a key length of 64 bytes, we proceed with no additional action. So new key is KO = 34713732 4A486758 38397A33 426B464D 74366377 51784C31 72443238 6A704E35 55665668 495A5950 62435365 75476F76 5261576D 41307344 39454374 58374A66 2. Performing the operation K0 XOR ipad. KO XOR ipad = 02470104 7C7E516E 0E0F4C05 745D707B 42005541 674E7A07 4472040E 5C467803 6350605E 7F6C6F66 54756553 43715940 6457615B 77064572 0F737542 6E017C50 3. Appending the message (K0 XOR ipad || message) to K0 XOR ipad. (K0 XOR ipad) || message = 02470104 7C7E516E 0E0F4C05 745D707B 42005541 674E7A07 4472040E 50467803 6350605E 7F6C6F66 54756553 43715940 6457615B 77064572 0F737542 6E017C50 48656C6C 6F 4. Putting the result of the previous operation into the SHA-1 hash. You should input into the hash function: 024701047C7E516E0E0F4C05745D707B42005541674E7A074472040E5O4678 036350605E7F6C6F6654756553437159406457615B770645720F7375426E017 C5048656C6C6F sha1(K0 XOR ipad || message) = 5fa962fde86832f2d5935b8be0229987e510f99f 5. Performing the operation K0 XOR opad. KO XOR opad = 682D6B6E 16143B04 6465266F 1E371A11 286A3F2B 0D24106D 2E186E64 36201269 093A0A34 1506050C 3E1F0F39 291B332A 0E3D0B31 1D6C2F18 65191F28 046B163A 6. Appending to the result of the previous operation the hash obtained in step 4. (KO XOR opad) || (sha1(K0 XOR ipad || message)) = 682D6B6E 16143B04 6465266F 1E371A11 286A3F2B 0D24106D 2E186E64 362C1269 093A0A34 1506050C 3E1F0F39 291B332A 0E3D0B31 1D6C2F18 65191F28 046B163A 5FA962FD E86832F2 D5935B8B E0229987 E510F99F 7. Putting the result of step 6 into the SHA-1 hash. HMAC = 62e1eaf2a7075bceb8e0022ae7d3e3d6f7271609 Example 3: key length >block size Input data: Message: “Hello” -+ X48656C6C 6F Secret Key: “Y0S5INaG35isu0FJNIEPQeC5V9VCb5jPQ6cVBVVTKRov0Un7Wv6kDsVzfTdx5djqg9b QakXf3vxf5IU1sOnjZoUzKu” -+ X59305335 494E6147 33356973 7530464A 4E6C4550 51654335 56395643 62356A50 51366356 42565654 4B526F76 30556E37 5776366B 4473567A 66546478 35646A71 67396251 616B5866 33767866 35495531 734F6E6A 5A6F557A 4B75 Constants for our case hash algorithm (SHA1) with block size 64 bytes: ipad (in HEX): X36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 (x36 repeated 64 time) opad (in HEX): X5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C cccf'czpcn cocr'cncr' EncnccEC cr'cf'cr'cr' OC / OwOL / OC / oOoLzOwwC / oC / OC / OL / OLz 0w0wt)C / 0C / oOoOt)CzOO oOoOoOoO oOoOOwOC / 5C5C5C5C 5C5C5C5C 5C5C5C5C (x5C repeated 64 time) Steps for creating HMAC comprise: 1. If the key length >block size, we first hash the key, and then add Os until its length becomes 64 bytes. In our case, with a key length of 90 bytes, we perform SHA1(Key). SHA1(Key) = 20e82c4d0379ee74fbe125e3b5be8b3f634a06e7. Currently, the length of SHA1(Key) is 20 bytes, so we add Os until the length becomes 64 bytes. So KO = 20E82C4D 0379EE74 FBE125E3 B5BE8B3F 634A06E7 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 00000000 2. Performing the operation KO XOR ipad. KO XOR ipad 16DE1A7B 354FD842 CDD713D5 8388BD09 557C30D1 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 3. Appending the message (KO XOR ipad || message) to KO XOR ipad. (KO XOR ipad) || message = 16DE1A7B 354FD842 CDD713D5 8388BD09 557C30D1 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 36363636 48656C6C 6F 4. Putting the result of the previous operation into the SHA-1 hash. You should input into the hash function: 16de1 a7b354fd842cdd713d58388bd09557c30d13636363636363636363636363 63636363636363636363636363636363636363636363636363636363636363648 656c6c6f sha1(K0 XOR ipad || message) = a79535b0b1fd1d5aff741fc0e1bbd2c627076c60 5. Performing the operation KO XOR opad. KO XOR opad = 7CB47011 5F25B228 A7BD79BF E9E2D763 3F165ABB 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 6. Appending to the result of the previous operation the hash obtained in step 4. (KO XOR opad) || (sha1(K0 XOR ipad || message)) =7CB47011 5F25B228 A7BD79BF E9E2D763 3F165ABB 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C 5C5C5C5C A79535B0 B1FD1D5A FF741FC0 E1BBD2C6 27076C60 7. Putting the result of step 6 into the SHA-1 hash. HMAC = 45fac385c1a6c3404593b8943c3d1da70da0594b Fig. 4 is an illustration of a diagram of an example of a system for evaluating a Non-Fungible Token or a Fungible Token. The system for evaluating a Non-Fungible Token or a Fungible Token comprises an Evaluation Circuitry40, Fund pool / Staking pool 43, Bundle Structure 46, Cybersecurity Circuitry 45, Information Hierarchy Structure 44 and Derivative Mathematical Hedging Circuitry 47. The evaluation circuitry 40 may offer the evaluation reference for Fund pool / Staking pool 43, Fund pool / Staking pool 43 may adjust the [3 through hedging fvix and frest market risk (through hedging a weighted-average bundle equation) in Derivative Mathematical Hedging Circuitry 47. Fund pool / Staking pool 43 also referential dividends distribution value through equation’s a; Bundle Structure 46 may only protect the ownership of underlying asset of tokens for example music or paintings. Information Hierarchy Structure 44 may execute the process of ownership management to ensure ownership protection based on Bundle Structure 46. Cybersecurity Circuitry 45 may protect all the related information flow, for example, the on-chain(on external block chain) or internal data transfer in Information Hierarchy Structure 44 may be protected through only revealing a part of the information not all the information though this Cybersecurity mechanism. Information Hierarchy Structure 44 will decide the extent or degree of hedging in Derivative Mathematical Hedging Circuitry 47, which may be determined through voting in Information Hierarchy Structure 44. The evaluation circuitry 40 and APIs 411 and 412 may determine the non-fungible token and fungible tokens’ values: Except for a, all other parts may be reference evaluation for auction and secondary market. But it may be absolute value in the fund pool / staking pool (token pool). Evaluation Circuitry 40 may evaluate the Non-fungible token and fungible token as follows: For NFT (Non-funqible token) f 00 <Z + n=J(_Y Pi fMarket I” Pzfcommunity “I" Psfstreaming + Plfcash flow + Ps futility) + Wherein a: Value added via auction and promotion from independent market, the broad cryptocurrency market effects may be reflected by the Market factor. p: Sensitivity dynamically determined by the marketing data’s linear regression, Factors without frequently updated actual data may be conducted by time-series regression. y: A proportion decides the percentage exposure to pr. This will be adjusted by derivative hedging in part 2. 2 When <7<0.15 y = —-— a>0.15 y=0 Input data may come from CVI (Cryptocurrecy volatility index) API. fMarket premium- Market exposure to the cryptocurrency systematic risk through Coinbase or Binance cryptocurrency market index API, especially future price data API. fcommunity- Factor about effective community size (Come from number of real owners, discord community...) Through internal API and Discord API fstreaming- Factor about effective streaming data through Spotify and Youtube API (Spotify, Youtube...) fcash flow- Factor about effective cash flow, which reflects fundamental financial value. Through internal API for data collection. Source come from diagram 1. futility- Factor about the utility about membership, tickets for the token owner. Only for quantifiable parts. fscaredty- Based on the uniqueness of the token as well as supply and demand, this may be correlation with fcommuntty’ it requires principal component analysis further. £ : Unexplainable components For fungible token: f O) (Z + n=^YPl fMarket T PzfCommunity^ P3 futility) + £ Same as the Non-fungible token, except for the factor’s categories. The formula is only for the pricing when tokens issued. Derivative hedging: 1. Common hedge: Method: Cryptocurrency futures in Binance and Coin base with short positions. Hedging factor Delta=1 / p1 Short hedging exposure= oo △ * S * Bitcoin + (^2 / ^) / 5^+ ^3 / ^^fuSDT + ^4, / ^^fsOL + ^s / ^^fxRP n=l + ( / kt / wr) wherein W: Total market w1: market value of corresponding cryptocurrency. Value S: Corresponding portfolio size Rebalancing: when market volatility exceeds 0.05a(monthly volitility), weight hedging model may be rebalanced. may be estimated by regression, too. A: Hedging delta. f: Exposures to corresponding cryptocurrencies. Fund pool / Stakinq pool (Token pool) 43: Dividend policy for NFT: The NFT may be classified into different tranches according to value, each may have its own aggregated factors(exposures a,p,f): Dynamically distributed fungible tokens = at - aL 1 + £ ” (y(pt -pt-^fMarket + (Pt ~ Pt-Community + (Pt -Pt-lVstreaming + ~Pt-Ofcash flow + (Pt -Pt-l)futility+- ■ ■ ■ ) + £t - £t-l + Tt - Tt-1 -(C=SN(d)~Ke.J^d» Minted fungible tokens: fungible token—coins of the platform. Minted may be decided on the Tokenomics in execution layer: Fundamental equation may be Distributed currency= ^inflation of the currency)* premium(Based on the membership hierarchy) Dividend may be distributed through USDT except for the Fungible token part. 0-2 y: It’s mainly decided by the voting from governance tokens or by when o-<0.15 y = <7>0.15 y=0 t: Expected inflation by tokenomics 2. Investment under extreme market scenario: When cr>0.15, purchase put option at point where market Gamma of call options(market upturn) or put options(Market down turn) are highest. C=SN(d^ C: Call price S: Current stock price K: Strike price t: time to maturity r: risk-free rate N: Nominal distribution IP protection: Binding the IP NFT with legal contract to realize the IP protection: The NFT may be standardized ERC721 token. But the NFT may have a corresponding legal contract in cloud storage fundamentally sharing the name. We may seamlessly bind the NFT with the legal contract through internal management to guarantee the IP protection. And it may be enhanced by transaction in NFT of legal contract. The binding may be realized in the Name and Description firstly, here we may use one harsh encryption to decide the description to connect to our contract stored in the cloud. The Information Hierarchy Structure 44 (1) Music NFT: ERC721 standard; Pointing to certain music’s audio file; The royalties distribution may be based on this token; Extra Utility: Premium membership Ownership of the fractional shares of a certain music; Accessibility to the certain musician’s discord. (2) Musician NFT: ERC721 standard; Pointing to an image of a standardized badge; Totally 6 images, each represents a certain level of the musician; Issue criteria: Musician who issued 10 pieces of music(Not the number of the NFTs representing the fractional shares but the number of pieces of music) in a platform. 2nd level: issuing another 20 pieces of music. 3rd level: issuing another 30 pieces of music. 4th level: issuing another 40 pieces of music. 5th level: issuing another 50 pieces of music. The 6th NFT may be given to the famous musician who are already celebrities as artists as a certificated badge in platform; Extra Utility: This badge can be used in the musician portrait in the platform. (3) Collctor NFT: ERC721 standard; Pointing to an image of a standardized badge; Totally 5 images, each represents a certain level of the musician; Issue criteria: Collectors who owned 10 music NFT (Number of the NFTs representing the fractional shares) in the platform. 2nd level: owning another20 music NFTs. 3 rd level: owning another 30 music NFTs. 4th level: owning another40 music NFTs. 5th level: owning another 50 music NFTs; Extra Utility: This badge can be used in the collector portrait; Accessibility to different collector communities in different levels. (4) Token: ERC20 standard; Utility token in the platform; Possible utility (Depending on the fundraising ways like ICO): Crypto currency to purchase music NFT; Governance token; Special utility token to have a discount or exchange for tickets of off-line and on-line event and functionalities. Cybersecurity Circuitry 45 is configured to perform a method for cryptographically authenticating information for the system comprises: - inputting 301 data including a message and a secret key K0; - creating 302 HMAC, Hash Message Authentication Code, comprising - performing 3021 an operation K0 XOR ipad, wherein ipad is block-sized inner padding; - appending 3022 the message to K0 XOR ipad to obtain K0 XOR ipad || message; - inputting 3023 K0 XOR ipad || message into a hash function to obtain HASH(K0 XOR ipad || message); - performing 3024 an operation K0 XOR opad, wherein opad is block-sized outer padding; - obtaining 3025 (K0 XOR opad) || (HASH (K0 XOR ipad || message)); - obtaining 3026 HASH((K0 XOR opad) || (HASH (K0 XOR ipad || message))). HMAC (Hash Message Authentication Code) is used to create digital signatures using different hash algorithms like MD5, SHA1, SHA256, SHA512, etc. HMAC is typically used for digital signatures (DA) which provides data Integrity and authentication. This is a unified approach for applying a digital signature with a private key. The utilization of HMAC presents a robust solution for ensuring data integrity and authenticity in diverse computing environments. HMAC offers significant advantages, including strong data integrity through unique authentication codes, resistance to tampering, authentication of message origin, computational efficiency, and versatility 5 across different data types and communication protocols. By leveraging HMAC, organizations can fortify their data security measures, safeguarding against unauthorized access, tampering, and spoofing attacks, thereby enhancing trust and reliability in data transmission and storage systems.

Claims

1. A computer device for evaluating a Non-Fungible Token or a Fungible Token, comprisinga processor comprising an evaluation circuitry configured toreceive a first factor fmarket relating to market exposure to a cryptocurrency systematic risk, receive a second factor fcommunity relating to an effective community size, receive a third factor / streaming relating to effective streaming data, receive a fourth factor fcashnow relating to effective cash flow,receive a fifth factor fumy relating to a utility, wherein the utility relates to a membership or a ticket for a token owner,determine a value of the Non-Fungible Token based on the first to fifth factors, or determine a value of the Fungible Token based on the first, second and fifth factors.

2. The computer device of claim 1, wherein the evaluation circuitry is further configured to determine a variable a of the Non-Fungible Token or the Fungible Token based on value added via auction and promotion from an independent market.

3. The computer device of claim 1 or 2, wherein the factors are adjusted by sensitivity / 3 dynamically determined by the marketing data’s linear regression.

4. The computer device of any of claims 1 to 3, wherein the first factor fmarket is calibrated by a proportion variable yi adjusted by derivative hedging.

5. The computer device of claim 4, wherein the proportion variable yi decides the percentage exposure to the sensitivity [3i of the first factor fmarket.

6. The computer device of any of claims 1 to 5, wherein the evaluation circuitry is configured to receive input data relating to the derivative hedging from a CVI, Cryptocurrecy volatility index, API.

7. The computer device of any of claims 1 to 6, wherein the evaluation circuitry is configured to receive the first factor fmarket through at least one of a Coinbase or Binancecryptocurrency market index API, preferably future price data API.

8. The computer device of any of claims 1 to 7, wherein the evaluation circuitry is configured to receive the second factor fcommunity through internal API and Discord API.

9. The computer device of any of claims 1 to 8, wherein the evaluation circuitry is configured to receive the third factor fstreaming through at least one of Spotify and Youtube API.

10. The computer device of any of claims 1 to 9, wherein the evaluation circuitry is configured to receive the fourth factor fcash flow through an internal API.

11. A method for evaluating a Non-Fungible Token or a Fungible Token by an evaluation circuitry of a processor of a computer device, comprisingreceiving a first factor fmarket relating to market exposure to a cryptocurrency systematic risk,receiving a second factor fcommunity relating to an effective community size,receiving a third factor fstreaming relating to effective streaming data,receiving a fourth factor fcash flow relating to effective cash flow,receiving a fifth factor futility relating to a utility, wherein the utility relates to a membership or a ticket for a token owner;determining a value of the Non-Fungible Token based on the first to fifth factors, or determining a value of the Fungible Token based on the first, second and fifth factors.

12. The method of claim 11, wherein determining a variable a of the Non-Fungible Token or the Fungible Token is further based on value added via auction and promotion from an independent market.

13. The method of any of claims 10 to 12, wherein the factors are adjusted by sensitivity / 3 dynamically determined by the marketing data’s linear regression.

14. The method of any of claims 10 to 13, wherein the first factor fmarket is calibrated by a proportion variable yi adjusted by derivative hedging.

15. The method of any of claims 14, wherein the proportion variable yi decides the percentage exposure to the sensitivity pi of the first factor fmarket.

16. The method of any of claims 10 to 15, further comprising receiving input data relating to the derivative hedging from a CVI, Cryptocurrecy volatility index, API.

17. The method of any of claims 10 to 16, wherein the receiving the first factor fmarket comprising receiving the first factor fmarket through Coinbase or Binance cryptocurrency market index APIs, preferably future price data API.

18. The method of any of claims 10 to 17, wherein the receiving the second factor / community comprising receiving the second factor through internal API and Discord API.

19. The method of any of claims 10 to 18, wherein the receiving the third factor / streaming comprising receiving the third factor through at least one of Spotify and Youtube APIs.

20. The method of any of claims 10 to 19, wherein the receiving the fourth factor / cashflow comprising receiving the fourth factor fcash flow through an internal API.

21. A non-transitory computer-readable medium storing instructions that perform the method of any of the claims 10 to 20.

22. A method for cryptographically authenticating information for the computer device of claims 1 to 10 and the method of 11 to 20, comprising- inputting data including a message and a secret key K0;- creating HMAC, Hash Message Authentication Code, comprising- performing an operation K0 XOR ipad, wherein ipad is the block-sized inner padding;- appending the message to K0 XOR ipad to obtain K0 XOR ipad || message;- inputting K0 XOR ipad || message into a hash function HASH to obtain HASH (K0 XOR ipad || message);- performing an operation K0 XOR opad, wherein opad is the block-sized outerpadding;- obtaining (KO XOR opad) || (HASH (KO XOR ipad || message));- obtaining HASH ((KO XOR opad) || (HASH (KO XOR ipad || message))).31

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