Encryption method and system for data asset privacy protection based on block chain

Abstract

The invention discloses a blockchain-based data asset privacy protection encryption method and system, and the method achieves the storage of metadata of data assets through a blockchain, thereby facilitating the combination of the properties of the blockchain and the natural law applied to the data storage of the blockchain. The accuracy of metadata interaction between the management end and the data acquisition end is achieved, and the use requirement of a user for data assets can be met. Besides, the method in the specification also combines the difference between data assets in the aspect of value, realizes the encryption of metadata based on natural laws, can identify illegal data acquisition ends through the encryption technical means, limits the access of the illegal data acquisition ends, effectively avoids the stealing of the digital assets by lawbreakers, and improves the security of the data acquisition ends. And the security of the data assets is improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing for management, supervision, or prediction purposes. In particular, it relates to an encryption method and system for privacy protection of data assets based on blockchain. Background Art

[0002] Blockchain (English name: blockchain or block chain) is a block-chain storage, tamper-proof, secure and trustworthy decentralized distributed ledger. It combines technologies such as distributed storage, peer-to-peer transmission, consensus mechanism, and cryptography. It records transactions and information through an ever-growing data block chain (Blocks) to ensure the security and transparency of data.

[0003] With the continuous deepening of the research on blockchain technology, blockchain technology is not only applied to the management of transaction information, but now it is also applied to the management of data assets.

[0004] As the types of data being managed have expanded, the original management logic has become less applicable. For example, transaction information emphasizes its accuracy, and the purpose of managing it through blockchain is mainly to prevent it from being tampered with by criminals. Higher requirements are put forward for the security of data assets. It not only requires preventing the tampering of data assets, but also requires restricting access to them. That is to say, even if criminals know its content, it will have a great impact on its security.

[0005] Therefore, how to strictly implement the privacy protection of data assets has become an urgent problem to be solved. Summary of the Invention

[0006] Embodiments of this application provide an encryption method and system for privacy protection of data assets based on blockchain to at least partially solve the above technical problems.

[0007] Embodiments of this application adopt the following technical solutions: In a first aspect, embodiments of this application provide an encryption method for privacy protection of data assets based on blockchain. The method uses an encryption system for privacy protection of data assets based on blockchain. The encryption system for privacy protection of data assets based on blockchain includes a management end and a data acquisition end that are communicatively connected. The method is executed by the management end. The method includes: Determine at least two target time nodes. The target time nodes are selected from among the many time nodes in which reference factors affect the value of the target data asset. Based on a specified fixed-value algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference. Store the metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; the reference difference and the reference ciphertext obtained by encrypting the reference difference with the target key are locally stored by the management end; the target key is obtained according to a key generation protocol; the key generation protocol is a protocol that uses a password-based key derivation function; the key derivation function uses the time ciphertext generated based on the target time node as the password. When detecting a metadata acquisition request for the target data asset from the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, read the metadata and return data to the data acquisition end based on the metadata acquisition request; the pending difference is pre-configured in the data acquisition end, and when the data acquisition end is legal, the pending difference is the same as the reference difference.

[0008] In an optional embodiment of this specification, the method further includes: The specified valuation algorithm is determined according to the nature of the target data asset; the specified valuation algorithm is one of the following: Metcalfe's Law, Black-Scholes Model, Pair Trading / Mean Reversion Strategy, Monte Carlo Simulation, PoW Mechanism Analysis, Fractal Market Hypothesis, Quantum Financial Model, On-chain Data Analysis, Social Media Sentiment Model, Thermodynamic Metaphor Model.

[0009] In an optional embodiment of this specification, the method further includes: The key generation protocol is used to obtain the target key through a dynamic key generation method according to the password-based key derivation function; during the execution of the dynamic key generation, the real-time salt value of the password-based key derivation function is determined at the configuration time of the pending difference in the data acquisition end; when the real-time salt value is updated, regenerate the reference ciphertext according to the key generation protocol and update it.

[0010] In an optional embodiment of this specification, the method further includes: At the data acquisition end locally, according to the real-time salt value generation rule in the key generation protocol, based on the configuration time of the pending difference in the data acquisition end, update the locally stored salt value to obtain a pending salt value. When the blockchain-based data asset privacy protection encryption system detects a metadata acquisition request for the target data asset from the data acquisition end, if the pending salt value parsed from the metadata acquisition request matches the locally stored real-time salt value, execute parsing the pending difference from the metadata acquisition request.

[0011] In an alternative embodiment of this specification, the method further includes: The metadata may further include any one of the following: descriptive data of the target data asset, structured data of the target data asset, management data of the target data asset, and technical data of the target data asset.

[0012] In an alternative embodiment of this specification, the method further includes: When a metadata acquisition request for the storage address in the metadata is detected at the data acquisition end, perform matching based on the real-time salt value.

[0013] In an alternative embodiment of this specification, the method further includes: When a metadata acquisition request for the target data asset other than the storage address is detected at the data acquisition end, directly return the corresponding metadata to the data acquisition end.

[0014] In an alternative embodiment of this specification, the method further includes: The reference factors include at least one of the following: data quality, data application scenario, law and compliance, technical factors, market environment, data life cycle, and external ecosystem.

[0015] In a second aspect, an embodiment of the present application further provides an encryption system for data asset privacy protection based on a blockchain. The encryption system for data asset privacy protection based on a blockchain includes a management end and a data acquisition end that are communicatively connected: The management end is configured to: determine at least two target time nodes; the target time nodes are selected from among the many time nodes in which the reference factors affect the value of the target data asset; Based on a specified fixed-value algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference; Store the metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; the reference difference and a reference ciphertext obtained by encrypting the reference difference based on a target key are locally stored by the management end; the target key is obtained according to a key generation protocol; the key generation protocol is a protocol using a password-based key derivation function; the key derivation function uses a time ciphertext generated based on the target time node as the password; When a metadata acquisition request for the target data asset is detected at the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, the metadata is read to return data to the data acquisition end based on the metadata acquisition request; the pending difference is pre-configured at the data acquisition end, and when the data acquisition end is legal, the pending difference is the same as the reference difference.

[0016] In a third aspect, an embodiment of the present application further provides an electronic device, including: a processor; and a memory arranged to store computer-executable instructions, which when executed cause the processor to execute the method steps described in the first aspect.

[0017] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by an electronic device including multiple application programs, the electronic device is caused to execute the method steps described in the first aspect.

[0018] The above at least one technical solution adopted in the embodiment of the present application can achieve the following beneficial effects: The method in this specification stores the metadata of data assets through a blockchain, which is beneficial to combining the nature of the blockchain and the natural laws applied when the blockchain stores data, realizing the accuracy of the interaction of metadata between the management end and the data acquisition end, and meeting the user's usage requirements for data assets. In addition, the method in this specification also combines the differences in value between data assets, realizes the encryption of metadata based on natural laws, and can identify illegal data acquisition ends through this encryption technical means and restrict their access, effectively avoiding the theft of data assets by lawbreakers and improving the security of data assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments and descriptions thereof of the present application are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings: Figure 1 is a schematic process diagram of an encryption method for data asset privacy protection based on a blockchain provided by an embodiment of this specification; Figure 2 is a schematic structural diagram of an electronic device in an embodiment of this specification. DETAILED DESCRIPTION

[0020] The present invention will be further described in detail below in conjunction with the specific embodiments and the accompanying drawings. Similar elements in different embodiments are denoted by related similar element numbers. In the following embodiments, many detailed descriptions are provided to enable a better understanding of the present application. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification, which is to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and the general technical knowledge in the art.

[0021] In addition, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can also be reordered or adjusted in a manner obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for clearly describing a certain embodiment and do not mean that they are the necessary sequences, unless it is stated that a certain sequence must be followed.

[0022] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the described objects and do not have any sequential or technical meaning. The "connection" and "coupling" mentioned in the present application, unless otherwise specified, both include direct and indirect connection (coupling).

[0023] The technical solutions provided by the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0024] The method in this specification adopts an encryption system for data asset privacy protection based on blockchain. The encryption system for data asset privacy protection based on blockchain includes a management end and a data acquisition end that are communicatively connected. The data acquisition end can be one or more. The access rights of different data acquisition ends to different blocks and / or different data on the same block can be the same or different. The method in this specification is executed by the management end.

[0025] As Figure 1 shown, the encryption method for data asset privacy protection based on blockchain in this specification includes the following steps: S100: Determine at least two target time nodes.

[0026] The target time nodes in this specification are selected from the time nodes experienced during the formation process of data assets. For example, data asset A was formed during the time period from January 1, 2000 to January 2, 2005. Then the target time nodes are within the period from January 1, 2000 to January 2, 2005. This design is for the accuracy of the valuation of data assets. If at a certain time node after the formation of data asset A (such as January 3, 2010), the holder of data asset A chooses to make it public, it will cause its value to decrease significantly. The impact caused by this time that seriously deviates from the value of the asset itself should be avoided.

[0027] The target time nodes in this specification are selected from the many time nodes where reference factors have an impact on the value composition of the target data asset.

[0028] In an optional embodiment of this specification, the reference factors are the factors that have an impact on the value composition of data assets. For example: data quality (such as accuracy, integrity, consistency, etc.), data application scenarios (such as business relevance, scenario scarcity, monetization potential, etc.), law and compliance (such as data ownership, compliance risk, cross-border restrictions, etc.), technical factors (such as accessibility, security, storage and processing costs, etc.), market environment (such as supply and demand relationship, competitive substitution, industry trend, etc.), data life cycle (such as time decay, historical value, etc.), external ecosystem (such as data householdness, third-party dependence, etc.). Based on the above reference factors, data assets show different values at different times. For example, for the aforementioned data asset A, at 5% of the data progress was just completed on September 1, 2000. At this time, due to the relatively serious lack of integrity of data asset A, its value is not high. The integrity of data assets (and other aspects of value manifestation) often does not grow linearly with time. This is reflected in data asset A that at 95% of the data progress was completed on September 12, 2000, resulting in a relatively significant increase in the value of data asset A at the time node of September 12, 2000. Then September 12, 2000 may become the target time node.

[0029] In addition, events that have a significant impact on the value composition of data assets may also occur at other time nodes other than September 12, 2000. This impact may not only increase the value of data assets, but also may decrease the value of data assets. These time nodes (alternative time nodes) may all become the target time node. As for what degree of value impact can be called a "significant impact", a threshold can be set based on manual experience. For example, calculate the value of the data asset at different time nodes respectively, and take the time node where the difference between the value of the adjacent previous time node is greater than the threshold as the alternative time node. Then select the target time node from the alternative time nodes.

[0030] In an alternative embodiment, the target time node can be selected from the alternative time nodes based on manual experience. In another alternative embodiment, an existing sampling algorithm can be used to sample the target time node from the alternative time nodes. Whatever the technical means for selecting the target time node, it will bring a certain degree of randomness to the selection of the target time node.

[0031] Data assets are unique, which makes the distribution of the value reflected at different time nodes in the time dimension also unique and difficult to replicate. Unless the complete data asset has been obtained, it is impossible to replicate the value distribution of different time nodes of the data asset. This characteristic is different from the transaction information stored in the blockchain in the prior art. The technical means in this specification combines natural laws and uses this characteristic to encrypt the data asset, making the technical means used in encryption also closely related to the content of the data asset and having uniqueness and being difficult to replicate, which effectively improves the security of the data asset. Further, even a party who knows the content of the data asset is difficult to replicate this encryption method because the selection of the target time node is random, and this randomness is very difficult to replicate, further improving the security of the data asset.

[0032] S102: Based on a specified valuation algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference.

[0033] The process of determining the difference from the difference between the values of different target time nodes is irreversible. That is to say, the difference can be determined through different values, but the value cannot be determined through the difference. Since the value is also a part of the data asset to a certain extent and there is a need to prevent privacy leakage, the technical means in this specification uses the difference (reference difference) to perform verification in the data interaction process instead of using the value, which is beneficial to the protection of the information of the value of the data asset.

[0034] The specified valuation algorithm in this specification is determined according to the nature of the target data asset and is optionally determined based on manual experience. Under the condition that it is allowed, the algorithms for valuation in related technologies are applicable to this specification under the condition that it is allowed.

[0035] In an alternative embodiment of this specification, the specified valuation algorithm is one of the following: Black-Scholes model, Metcalfe's law, Monte Carlo simulation, pair trading / mean reversion strategy, fractal market hypothesis, PoW mechanism analysis, on-chain data analysis, quantum financial model, thermodynamic metaphor model, social media sentiment model.

[0036] Among them, the natural laws applied in the Black-Scholes model (option pricing) are: Brownian motion and stochastic processes. The mechanism is: assume that the price of the data asset follows geometric Brownian motion and simulate the short-term random price fluctuations. The formula is: \( dS = \mu S dt + \sigma S dW \) (\( W \) is the Wiener process). For example, the Bitcoin options market uses an improved BS model (considering volatility smile) for pricing.

[0037] The natural laws applied in Metcalfe's law (network value evaluation) are: complex system theory (network effect). The mechanism is: the network value \( V \propto N^2 \) (\( N \) is the number of users). For example, the growth of DeFi users on Ethereum has pushed its market value beyond the threshold.

[0038] The natural laws applied in Monte Carlo simulation (extreme risk pricing) are: Brownian motion + critical point of complex systems. The mechanism is: generate random price paths and simulate black swan events (such as flash crashes). Combine with the GARCH model to capture the volatility clustering effect.

[0039] The natural laws applied in pair trading / mean reversion strategy are: mean reversion (statistics). The mechanism is: utilize the price difference between correlated assets (such as BTC / ETH) to revert to the long-term mean. Statistical arbitrage: go long on undervalued assets and short on overvalued assets.

[0040] The natural laws applied in the fractal market hypothesis (price volatility analysis) are: fractal geometry. The mechanism is: identify the self-similar structure of the candlestick chart at different time scales (hours / weeks). Use the Hurst exponent to judge the trend persistence (\( H>0.5 \) indicates a trending market).

[0041] The natural laws applied in the miner game model (PoW mechanism analysis) are: game theory and Nash equilibrium. The mechanism is: the equilibrium of miners' computing power competition determines the security cost of the Bitcoin network. Dynamically adjust the mining difficulty to maintain a 10-minute block interval.

[0042] The natural laws applied in on-chain data analysis (market sentiment prediction) are: information theory (Shannon entropy). The mechanism is: predict trends through entropy reduction signals such as address activity and large transfers. Glassnode metrics (such as SOPR) quantify investors' profit and loss sentiment.

[0043] The natural laws applied in the quantum financial model (explaining price mutations) are: metaphors of quantum mechanics (superposition state, tunneling). The mechanism is: the price is in a "stable / collapse" superposition state before collapse. The sudden change in market sentiment is analogous to the quantum tunneling effect.

[0044] The natural law applied by the thermodynamic metaphor model (market entropy assessment) is: the law of entropy increase. The mechanism is: using market volatility to measure the entropy value (high volatility = high disorder). DeFi protocols inject liquidity through automated market makers (AMMs) to reduce entropy.

[0045] The natural law applied by the social media sentiment model (Meme coin pricing) is: group behavior dynamics (herd effect). The mechanism is: there is a strong correlation between the Reddit / Twitter sentiment index and the price. The reflexive cycle: price increase → more discussions → further price increase.

[0046] It can be seen that the technical means adopted by the technical solution in this specification are based on natural laws, and the mechanisms it relies on also conform to natural laws.

[0047] S104: Store the metadata of the target data asset in the blockchain.

[0048] In the technical solution of this specification, the data asset is not stored in the blockchain, but stored at a certain address in the cloud to further enhance its concealment. This address can only be accessed under the control of the system in this specification.

[0049] The metadata of the target data asset in this specification includes: the storage of the target data asset; the reference difference and the reference ciphertext obtained by encrypting the reference difference based on the target key are locally stored by the management terminal; the target key is obtained according to the key generation protocol. The key generation protocol is a protocol based on the password-based key derivation function (PBKDF); the key derivation function uses the time ciphertext generated based on the target time node as the password.

[0050] The key generation protocol is pre-loaded in the management terminal for encryption. The key generation protocol is a logic used during encryption, rather than a specific algorithm with fixed parameters. In the technical solution of this specification, the key derivation function is different for different data assets. For example, for the aforementioned data asset A, its target time nodes are September 12, 2000 (which can be simplified to the array 20000912) and March 6, 2005 (which can be simplified to the array 20050306). Since the alternative time nodes of different data assets are different, and the selection of the target time node is random, the data constructed from the target time node is unique and cannot be replicated. In an optional embodiment of this specification, in order to enhance the confidentiality of the time node, the array can also be encrypted to obtain the time ciphertext. Technical means that can be applied to data encryption in the prior art are applicable to this specification under the condition of permission. For efficiency, the hash algorithm can be used to encrypt the data to obtain the time ciphertext.

[0051] The encryption method of the key derivation function changes with the change of the password. Since the target time node is random and the time ciphertext is the encrypted result, the password is a random rune combined with the characteristics of the data asset, which is difficult to replicate and is beneficial to improving the security of the data asset.

[0052] In another optional embodiment of this specification, in addition to the randomness brought by the password, a key generation protocol can also be obtained by combining the key derivation function with a dynamic key. The target key is obtained by the method of dynamic key generation based on the password-based key derivation function; during the process of generating the dynamic key, the real-time salt value (to achieve real-time update) of the password-based key derivation function is determined at the configuration moment of the data acquisition end by the to-be-determined difference; when the real-time salt value is updated, the reference ciphertext is regenerated and updated. Each time the management end updates the password and / or salt value (updating the password means re-determining the target time node, and the salt value may also change accordingly), the data acquisition end also synchronously updates accordingly. Since the configuration moment is usually unique, it is beneficial to realize the supervision of the management end over the data acquisition end and prevent illegal data acquisition ends from passing off the spurious as the genuine.

[0053] In this embodiment, password-based key derivation (PBKDF) and dynamic key generation are used in a password-based encryption scheme (PBES), and the key is derived from the password (time ciphertext) and the salt value (real-time salt value). This scheme can be used to generate a dynamic key, and the specific steps are as follows: Key derivation: Use the password (P), salt value (S), number of iterations (c), and key length (dkLen) to generate an exported key (DK) through a key derivation function (such as PBKDF2). The inputs of the key derivation function include: P: Password, that is, the time ciphertext. S: Salt value, which can be a byte sequence used to increase the randomness and security of the key. c: Number of iterations, used to increase the computational complexity and prevent brute force cracking. dkLen: The length of the exported key. The dynamic nature of this embodiment is reflected in that different keys can be dynamically generated by changing the salt value (S), thereby realizing dynamic encryption.

[0054] S106: When detecting a metadata acquisition request of the data acquisition end for the target data asset, if the to-be-determined ciphertext obtained by encrypting the to-be-determined difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, read the metadata and return the data to the data acquisition end based on the metadata acquisition request.

[0055] As mentioned above, the to-be-determined difference in this specification is pre-configured in the data acquisition end. When the data acquisition end is legal, the to-be-determined difference is the same as the reference difference.

[0056] In this specification, the process of encryption according to the key generation protocol is also a way for the management end to achieve self-verification. If the result of encrypting a specific difference by the management end is different from the reference ciphertext, on the one hand, it may be that the data acquisition end is illegal; on the other hand, it may also be that the management end has been attacked, resulting in problems in the previous update process, or the management end has been tampered with. At this time, on the one hand, the data acquisition behavior of this data acquisition end should be prohibited, and the management end should also be disconnected from the blockchain, and the management end should be prohibited from accessing the blockchain.

[0057] In a further optional embodiment, at the local end of the data acquisition end, according to the real-time salt value generation rule in the key generation protocol, based on the specific difference at the configuration moment of the data acquisition end, the salt value is updated to obtain a specific salt value; when the encryption system for protecting the privacy of data assets based on the blockchain detects a metadata acquisition request of the data acquisition end for the target data asset, if the specific salt value parsed from the metadata acquisition request matches the real-time salt value stored locally, then the specific difference parsed from the metadata acquisition request is executed. This additional matching verification of the salt value helps to further improve security. Optionally, to improve efficiency, when detecting a metadata acquisition request of the data acquisition end for the storage address in the metadata, the matching based on the real-time salt value can be executed. When detecting a metadata acquisition request of the data acquisition end for metadata other than the storage address of the target data asset, the corresponding metadata is directly returned to the data acquisition end.

[0058] In an optional embodiment of this specification, in addition to the storage address, the metadata may also include any one of the following: the structured data of the target data asset (describing the internal structure and organization method of the data asset, helping users understand the components and interrelationships of the asset. For example, file format, file size, etc.), the management data of the target data asset (information used to manage and maintain the data asset, including the creation, modification, and access permissions of the asset, etc.), the technical data of the target data asset (describing the technical details of the data asset, helping users understand the technical requirements and compatibility of the asset, such as encoding format, etc.).

[0059] The above at least one technical solution adopted in the embodiments of the present application can achieve the following beneficial effects: The method in this specification stores the metadata of data assets through a blockchain, which is conducive to combining the nature of the blockchain and the natural laws applied when the blockchain stores data, realizing the accuracy of the interaction of metadata between the management end and the data acquisition end, and meeting the user's usage requirements for data assets. In addition, the method in this specification also combines the differences in value between data assets, realizes the encryption of metadata based on natural laws, and can identify illegal data acquisition ends and restrict their access through this encryption technical means, effectively avoiding the theft of digital assets by criminals and improving the security of data assets.

[0060] Furthermore, this specification also provides an encryption system for data asset privacy protection based on a blockchain. The encryption system for data asset privacy protection based on a blockchain includes a management end and a data acquisition end that are communicatively connected: The management end is configured to: determine at least two target time nodes; the target time nodes are selected from among the many time nodes that affect the value composition of the target data asset due to reference factors; Based on a specified fixed-value algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference; Store the metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; the reference difference and the reference ciphertext obtained by encrypting the reference difference based on a target key are locally stored by the management end; the target key is obtained according to a key generation protocol; the key generation protocol is a protocol that uses a password-based key derivation function; the key derivation function uses the time ciphertext generated based on the target time node as the password; When detecting a metadata acquisition request from the data acquisition end for the target data asset, if the pending ciphertext obtained by encrypting the pending difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, read the metadata and return data to the data acquisition end based on the metadata acquisition request; the pending difference is pre-configured in the data acquisition end, and when the data acquisition end is legal, the pending difference is the same as the reference difference.

[0061] This system can execute the method in any of the foregoing embodiments and can obtain the same or similar technical effects, which will not be elaborated here.

[0062] Figure 2 It is a schematic structural diagram of an electronic device according to an embodiment of the present application. Please refer to Figure 2, at the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. Among them, the memory may include internal memory, such as high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk memory, etc. Of course, the electronic device may also include other hardware required for other services.

[0063] The processor, network interface, and memory can be interconnected through the internal bus, and the internal bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 2 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0064] The memory is used to store programs. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include internal memory and non-volatile memory, and provide instructions and data to the processor.

[0065] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming a cryptographic device for protecting the privacy of data assets based on blockchain at the logical level. The processor executes the program stored in the memory and is specifically used to execute any one of the foregoing cryptographic methods for protecting the privacy of data assets based on blockchain.

[0066] As described above in this application Figure 1An encryption method for data asset privacy protection based on blockchain disclosed in the illustrated embodiments can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor or by instructions in the form of software. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0067] The electronic device can also execute Figure 1 an encryption method for data asset privacy protection based on blockchain and implement Figure 1 the functions of the illustrated embodiments, which will not be elaborated in the embodiments of the present application.

[0068] The embodiments of the present application also propose a computer-readable storage medium that stores one or more programs. The one or more programs include instructions that, when executed by an electronic device including multiple application programs, execute any of the foregoing encryption methods for data asset privacy protection based on blockchain.

[0069] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0070] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0071] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0072] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0073] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0074] The memory may include non-permanent memory in the computer-readable medium, random access memory (RAM), and / or non-volatile memory in the form of, for example, read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0075] A computer-readable medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information accessible by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0076] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or apparatus comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising the element.

[0077] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, system or computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] The above description is only for the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. An encryption method for data asset privacy protection based on blockchain, characterized in that, The method adopts an encryption system for privacy protection of data assets based on blockchain; the encryption system for privacy protection of data assets based on blockchain includes a management end and a data acquisition end that are communicatively connected, and the method is executed by the management end; the method includes: Determine at least two target time nodes; the target time nodes are selected from among the many time nodes in which reference factors affect the value of the target data asset. Based on a specified valuation algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference. Store the metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; the reference difference and the reference ciphertext obtained by encrypting the reference difference based on a target key are stored locally by the management end; the target key is obtained according to a key generation protocol; the key generation protocol is a protocol that uses a password-based key derivation function; the key derivation function uses the time ciphertext generated based on the target time node as the password. When a metadata acquisition request for the target data asset from the data acquisition end is detected, if the pending ciphertext obtained by encrypting the pending difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, read the metadata to return data to the data acquisition end based on the metadata acquisition request; the pending difference is pre-configured in the data acquisition end, and when the data acquisition end is legal, the pending difference is the same as the reference difference.

2. The method according to claim 1, wherein The method further includes: The specified valuation algorithm is determined according to the nature of the target data asset; the specified valuation algorithm is one of the following: Metcalfe's Law, Black-Scholes Model, Pair Trading / Mean Reversion Strategy, Monte Carlo Simulation, PoW Mechanism Analysis, Fractal Market Hypothesis, Quantum Financial Model, On-chain Data Analysis, Social Media Sentiment Model, Thermodynamic Metaphor Model.

3. The method according to claim 1, wherein The method further includes: The key generation protocol is used to obtain a target key through a dynamic key generation method according to a password-based key derivation function; during the execution of the dynamic key generation, the real-time salt value of the password-based key derivation function is determined at the configuration time of the pending difference in the data acquisition end; when the real-time salt value is updated, regenerate the reference ciphertext according to the key generation protocol and update it.

4. The method according to claim 3, wherein The method further includes: At the data acquisition end locally, based on the real-time salt value generation rule in the key generation protocol and the configuration time of the pending difference in the data acquisition end, update the locally stored salt value to obtain a pending salt value. When the encryption system for privacy protection of data assets based on blockchain detects a metadata acquisition request for the target data asset from the data acquisition end, if the pending salt value parsed from the metadata acquisition request matches the locally stored real-time salt value, execute parsing the pending difference from the metadata acquisition request.

5. The method according to claim 4, characterized in that, The method further includes: The metadata may also include any one of the following: descriptive data of the target data asset, structured data of the target data asset, management data of the target data asset, and technical data of the target data asset.

6. The method according to claim 5, wherein The method further includes: When a metadata acquisition request for the storage address in the metadata is detected at the data acquisition end, perform matching based on the real-time salt value.

7. The method according to claim 5, characterized in that The method further includes: When a metadata acquisition request for the metadata of the target data asset other than the storage address is detected at the data acquisition end, directly return the corresponding metadata to the data acquisition end.

8. The method according to claim 1, wherein The method further includes: The reference factors include at least one of the following: data quality, data application scenario, law and compliance, technical factors, market environment, data life cycle, and external ecosystem.

9. An encryption system for data asset privacy protection based on blockchain, characterized in that, The encryption system for data asset privacy protection based on blockchain includes a management end and a data acquisition end that are communicatively connected: The management end is configured to: determine at least two target time nodes; the target time nodes are selected from among the many time nodes when the reference factors affect the value of the target data asset; Based on a specified fixed-value algorithm, determine the difference in the value of the target data asset at different target time nodes as a reference difference; Store the metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; The reference difference and the reference ciphertext obtained by encrypting the reference difference based on the target key are locally stored by the management end; The target key is obtained according to a key generation protocol; the key generation protocol is a protocol that uses a password-based key derivation function; The key derivation function uses the time ciphertext generated based on the target time node as the password; When a metadata acquisition request for the target data asset is detected at the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference parsed from the metadata acquisition request with the target key matches the reference ciphertext, read the metadata to return data to the data acquisition end based on the metadata acquisition request; The pending difference is pre-configured at the data acquisition end, and when the data acquisition end is legal, the pending difference is the same as the reference difference.

10. An electronic device, including: A processor; And A memory arranged to store computer-executable instructions, and when the executable instructions are executed, the processor executes the method according to any one of claims 1 to 8.

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