An encryption method and system for data asset privacy protection based on blockchain

Abstract

This application discloses a blockchain-based encryption method and system for protecting the privacy of data assets. By storing metadata about data assets through blockchain, this method, combined with the properties of blockchain and the natural laws applied when storing data, helps ensure the accuracy of metadata interaction between management and data acquisition terminals, thereby meeting user needs for data asset usage. Furthermore, the method disclosed herein also incorporates the differences in value between data assets to achieve natural law-based encryption of metadata. This encryption technology can identify illegal data acquisition terminals and restrict their access, effectively preventing the theft of data assets by unscrupulous individuals and improving the security of data assets.

Description

Technical Field

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

[0002] Blockchain (English name: blockchain or block chain) is a decentralized distributed ledger with block chain storage, non-tamperability, security and reliability. It combines distributed storage, point-to-point transmission, consensus mechanism, cryptography and other technologies to record transactions and information through a growing data block chain to ensure data security and transparency.

[0003] As people's research on blockchain technology continues to deepen, blockchain technology is not only used in the management of transaction information, but is now also applied to the management of data assets.

[0004] As the types of data being managed expand, existing management logic becomes less applicable. For example, transaction information prioritizes accuracy, and managing it through blockchain primarily aims to prevent tampering. The security of data assets presents even higher requirements, requiring not only protection from tampering but also restricted access. In other words, even if criminals gain access to data, it can significantly impact security.

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

[0006] The embodiments of the present application provide an encryption method and system for protecting the privacy of data assets based on blockchain to at least partially solve the above-mentioned technical problems.

[0007] The embodiments of this application adopt the following technical solutions:

[0008] In a first aspect, embodiments of the present application provide a blockchain-based encryption method for protecting the privacy of data assets. The method employs a blockchain-based encryption system for protecting the privacy of data assets. The blockchain-based encryption system for protecting the privacy of data assets comprises a management terminal and a data acquisition terminal in communication connection. The method is executed by the management terminal. The method comprises:

[0009] Determine at least two target time nodes; the target time nodes are selected from a plurality of time nodes where reference factors influence the value of the target data asset;

[0010] Based on a specified valuation algorithm, determine the difference in value of the target data asset at different target time points as a reference difference;

[0011] The metadata of the target data asset is stored in a blockchain; the metadata includes: the storage address of the target data asset; the reference difference value, and the reference ciphertext obtained by encrypting the reference difference value based on the target key, which are stored locally on the management terminal; 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 a time ciphertext generated based on the target time node as a password;

[0012] When a metadata acquisition request for the target data asset is detected from the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference value 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 value is pre-configured at the data acquisition end, and if the data acquisition end is legal, the pending difference value is the same as the reference difference value.

[0013] In an optional embodiment of this specification, the method further includes:

[0014] The designated valuation algorithm is determined according to the nature of the target data asset; the designated 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.

[0015] In an optional embodiment of this specification, the method further includes:

[0016] The key generation protocol is used to obtain a target key through a dynamic key generation method based on 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 based on the pending difference at the configuration time of the data acquisition end; when the real-time salt value is updated, the reference ciphertext is regenerated according to the key generation protocol and updated.

[0017] In an optional embodiment of this specification, the method further includes:

[0018] At the data acquisition end, according to the real-time salt value generation rule in the key generation protocol, based on the configuration time of the pending difference value at the data acquisition end, the locally stored salt value is updated to obtain the pending salt value;

[0019] When the blockchain-based data asset privacy protection encryption system detects the 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, the pending difference value is parsed from the metadata acquisition request.

[0020] In an optional embodiment of this specification, the method further includes:

[0021] 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.

[0022] In an optional embodiment of this specification, the method further includes:

[0023] When detecting a metadata acquisition request from the data acquisition end for the storage address in the metadata, performing matching based on the real-time salt value.

[0024] In an optional embodiment of this specification, the method further includes:

[0025] When detecting that the data acquisition end has requested metadata other than the storage address for the target data asset, the corresponding metadata is directly returned to the data acquisition end.

[0026] In an optional embodiment of this specification, the method further includes:

[0027] The reference factors include at least one of the following: data quality, data application scenarios, laws and compliance, technical factors, market environment, data life cycle, and external ecology.

[0028] In a second aspect, an embodiment of the present application further provides an encryption system for protecting the privacy of data assets based on blockchain, wherein the encryption system for protecting the privacy of data assets based on blockchain includes a management end and a data acquisition end connected in communication:

[0029] The management terminal is configured to: determine at least two target time nodes; the target time nodes are selected from a plurality of time nodes that influence the value of the target data asset according to reference factors;

[0030] Based on a specified valuation algorithm, determine the difference in value of the target data asset at different target time points as a reference difference;

[0031] The metadata of the target data asset is stored in a blockchain; the metadata includes: the storage address of the target data asset; the reference difference value, and the reference ciphertext obtained by encrypting the reference difference value based on the target key, which are stored locally on the management terminal; 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 a time ciphertext generated based on the target time node as a password;

[0032] When a metadata acquisition request for the target data asset is detected from the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference value 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 value is pre-configured at the data acquisition end, and if the data acquisition end is legal, the pending difference value is the same as the reference difference value.

[0033] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0034] processor; and

[0035] A memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method steps of the first aspect.

[0036] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by an electronic device including multiple applications, the electronic device executes the method steps described in the first aspect.

[0037] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0038] The method described in this specification uses blockchain to store metadata for data assets. This facilitates combining the properties of blockchain and the natural laws applied when storing data on the blockchain, ensuring accurate metadata interaction between management and data acquisition terminals, and meeting user needs for data asset usage. Furthermore, the method described in this specification also incorporates the differences in value between data assets to achieve natural law-based encryption of metadata. This encryption technology can identify illegal data acquisition terminals and restrict their access, effectively preventing the theft of data assets by unscrupulous elements and improving the security of data assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] 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 of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0040] Figure 1 A schematic diagram of a blockchain-based encryption method for protecting data asset privacy provided in an embodiment of this specification;

[0041] Figure 2 This is a schematic diagram of the structure of an electronic device in an embodiment of this specification. DETAILED DESCRIPTION

[0042] The present invention will be further described in detail below with reference to the accompanying drawings by way of specific embodiments. Similar elements in different embodiments are numbered with associated similar elements. In the following embodiments, many detailed descriptions are provided to enable the present application to be better understood. However, those skilled in the art will readily appreciate that some of the features may be omitted under different circumstances, or may 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. This is to avoid overwhelm the core of the present application with excessive descriptions, and for those skilled in the art, it is not necessary to describe these related operations in detail. They will fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0043] In addition, the features, operations, or characteristics described in the specification may be combined in any appropriate manner to form various embodiments. Furthermore, the steps or actions in the method description may be reordered or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various sequences in the specification and drawings are provided solely for the purpose of clearly describing a particular embodiment and are not intended to be mandatory, unless otherwise specified.

[0044] The serial numbers assigned to components herein, such as "first," "second," etc., are used solely to distinguish the objects being described and do not convey any sequential or technical meaning. References to "connection" and "coupling" herein, unless otherwise specified, include both direct and indirect connections (couplings).

[0045] The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

[0046] The method described herein utilizes a blockchain-based encryption system for protecting the privacy of data assets. This system includes a communication-connected management terminal and a data acquisition terminal. The data acquisition terminal can be one or more, and different data acquisition terminals can have the same or different access rights to different blocks and / or different data on the same block. The method described herein is executed by the management terminal.

[0047] like Figure 1 As shown, the encryption method for data asset privacy protection based on blockchain in this specification includes the following steps:

[0048] S100: Determine at least two target time nodes.

[0049] The target time points in this specification are selected from the time points during the data asset's formation process. For example, if Data Asset A was formed between January 1, 2000, and January 2, 2005, then the target time points would be between January 1, 2000, and January 2, 2005. This design is intended to ensure the accuracy of the data asset's valuation. If the holder of Data Asset A chooses to disclose it at a certain point after its formation (for example, January 3, 2010), its value will significantly decrease. The impact of such a significant deviation from the original asset value should be avoided.

[0050] The target time nodes in this specification are selected from the many time nodes where reference factors influence the value of the target data assets.

[0051] In an optional embodiment of this specification, reference factors are factors that influence the value of data assets. For example: data quality (such as accuracy, completeness, consistency, etc.), data application scenarios (such as business relevance, scenario scarcity, monetization potential, etc.), laws and compliance (such as data ownership, compliance risks, cross-border restrictions, etc.), technical factors (such as accessibility, security, storage and processing costs, etc.), market environment (such as supply and demand relationships, competitive substitution, industry trends, etc.), data life cycle (such as time-sensitive data decay, historical value, etc.), external ecology (such as data household, third-party dependence, etc.). Based on the above reference factors, data assets exhibit different values ​​at different times. For example, the aforementioned data asset A had just completed 5% of the data progress on September 1, 2000. At this time, due to the serious lack of integrity of data asset A, its value was not high. The integrity of data assets (and their value in other aspects) often doesn't grow linearly over time. This is reflected in Data Asset A, which had 95% of its data progress completed on September 12, 2000. This resulted in a significant increase in value at that time. Therefore, September 12, 2000, could be the target date.

[0052] In addition, events other than September 12, 2000, could have significantly impacted the value of data assets. This impact might not only increase the value of the data assets but also decrease it. These time points (alternative time points) could all become target time points. As for the degree of impact that qualifies as a "significant impact," a threshold can be set based on empirical experience. For example, the value of the data asset at different time points could be calculated, and the time points with a difference in value from the previous adjacent time point greater than a threshold could be selected as candidate time points. The target time point could then be selected from these candidate time points.

[0053] In one optional embodiment, the target time node can be selected from the candidate time nodes based on manual experience. In another optional embodiment, an existing sampling algorithm can be used to sample the target time node from the candidate time nodes. Regardless of the technical means used to select the target time node, a certain degree of randomness will be introduced into the selection of the target time node.

[0054] Data assets are all unique, which makes the distribution of their value 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 data assets at different time nodes. This feature is different from the transaction information stored in the blockchain in the prior art. The technical means in this specification combines the laws of nature and uses this feature to realize the encryption of data assets, so that the technical means used in encryption are also closely related to the content of the data assets, and are also unique and difficult to replicate, which is beneficial to improve the security of data assets. Furthermore, even a party who knows the content of the data asset will find it difficult to replicate this encryption method, because the selection of the target time node is random, and this randomness is difficult to replicate, further improving the security of data assets.

[0055] S102: Based on a specified fixed value algorithm, determine the difference in value of the target data asset at different target time nodes as a reference difference.

[0056] The process of determining the difference between values ​​at different target time points is irreversible. That is, while the difference can be determined from different values, the value cannot be determined from the difference. Because value is, to a certain extent, part of the data asset and is necessary to prevent privacy leaks, the technical means described in this specification use the difference (reference difference) to perform verification during data interaction, rather than using the value, to facilitate the protection of the value of data assets.

[0057] The designated value algorithm in this specification is determined based on the properties of the target data asset, and can optionally be determined based on manual experience. Where conditions permit, the algorithms used for value determination in related technologies are applicable to this specification where conditions permit.

[0058] In an optional embodiment of the present 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, and social media sentiment model.

[0059] The Black-Scholes model (for option pricing) applies the natural laws of Brownian motion and stochastic processes. Its mechanism assumes that data asset prices follow geometric Brownian motion, simulating short-term random price fluctuations. The formula is: \( dS = \mu S dt + \sigma S dW \) (\( W \) is a Wiener process). For example, the Bitcoin options market uses a modified BS model (which considers the volatility smile) for pricing.

[0060] Metcalfe's Law (network value assessment) applies the natural law of complex systems theory (network effects). Its mechanism is: network value \(V \propto N^2\) (\(N\) is the number of users). For example, Ethereum's DeFi user growth has pushed its market capitalization above a threshold.

[0061] Monte Carlo simulation (extreme risk pricing) leverages the natural laws of Brownian motion combined with critical points in complex systems. Its mechanism involves generating random price paths to simulate black swan events (such as flash crashes). It also incorporates the GARCH model to capture volatility clustering effects.

[0062] Pairs trading / mean reversion strategies utilize the natural law of mean reversion (statistics). The mechanism is to exploit 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.

[0063] The fractal market hypothesis (price fluctuation analysis) applies the natural law of fractal geometry. Its mechanism involves identifying self-similar structures in candlestick charts at different time scales (hourly / weekly). The Hurst exponent is used to determine trend persistence (H > 0.5 indicates a trending market).

[0064] The miner game model (PoW mechanism analysis) applies the natural laws of game theory and Nash equilibrium. The mechanism is that the equilibrium of miner computing power competition determines the security cost of the Bitcoin network. The mining difficulty is dynamically adjusted to maintain a 10-minute block interval.

[0065] On-chain data analysis (market sentiment prediction) applies the natural law of information theory (Shannon entropy). The mechanism is to predict trends using entropy-reducing signals such as address activity and large transfers. Glassnode indicators (such as SOPR) quantify investor sentiment regarding profit and loss.

[0066] The quantum finance model (explaining price fluctuations) uses natural laws based on quantum mechanical metaphors (superposition and tunneling). The mechanism is that prices are in a superposition of stability and collapse before they collapse. Sudden market fluctuations are analogous to the quantum tunneling effect.

[0067] The thermodynamic metaphor model (market entropy assessment) applies the natural law of increasing entropy. Its mechanism is to measure entropy using market volatility (high volatility = high disorder). DeFi protocols reduce entropy by injecting liquidity through automated market makers (AMMs).

[0068] The social media sentiment model (Memecoin pricing) applies the natural law of group behavior dynamics (herding). The mechanism is the strong correlation between Reddit / Twitter sentiment and price. A reflexive cycle: price increases → more discussion → further increases.

[0069] It can be seen that the technical means adopted in the technical solutions in this specification are based on natural laws, and the mechanisms they rely on are also in line with natural laws.

[0070] S104: Storing the metadata of the target data asset in the blockchain.

[0071] In the technical solution described in this specification, data assets are not stored in the blockchain, but rather at a certain address in the cloud to further enhance their confidentiality. This address is only accessible under the control of the system described in this specification.

[0072] The target data asset metadata in this specification includes: the storage of the target data asset; the reference difference value and the reference ciphertext encrypted using the target key, stored locally on the management end; the target key is derived according to a key generation protocol. The key generation protocol is a password-based key derivation function (PBKDF); the key derivation function uses the time ciphertext generated based on the target time node as the password.

[0073] The key generation protocol is pre-loaded on the management end and is used to perform encryption. The key generation protocol is the logic used during encryption, not 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, the aforementioned data asset A has target time nodes of September 12, 2000 (which can be simplified to the array 20000912) and March 6, 2005 (which can be simplified to the array 20050306). Because different data assets have different alternative time nodes, and the selection of target time nodes is random, the data constructed from the target time nodes is unique and cannot be replicated. In an optional embodiment of this specification, to enhance the confidentiality of the time nodes, the array can also be encrypted to obtain a time ciphertext. Technical means that can be applied to data encryption in the existing technology are applicable to this specification, where conditions permit. For efficiency reasons, a hash algorithm can be used to encrypt the data to obtain the time ciphertext.

[0074] The encryption method of the key derivation function changes with the password. Since the target time node is random and the time ciphertext is the result of encryption, the password is a rune with randomness that combines the characteristics of data assets. It is difficult to replicate and is conducive to improving the security of data assets.

[0075] In another optional embodiment of this specification, in addition to the randomness provided by the password, a key generation protocol can also be derived by combining a key derivation function with a dynamic key. The target key is derived through a dynamic key generation method using a password-based key derivation function. During the dynamic key generation process, the real-time salt value (to achieve real-time updates) of the password-based key derivation function is determined based on the pending difference at the configuration time of the data acquisition terminal. When the real-time salt value is updated, the reference ciphertext is regenerated and updated. Each time the management terminal 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 terminal is also updated accordingly. Since the configuration time is generally unique, this facilitates the management terminal's supervision of the data acquisition terminal and prevents illegal data acquisition terminals from spoofing.

[0076] In this embodiment, password-based key derivation (PBKDF) and dynamic key generation are combined in a password-based encryption scheme (PBES). The key is derived from a password (a time ciphertext) and a salt (a real-time salt). This scheme can be used to generate dynamic keys. The specific steps are as follows: Key derivation: A derived key (DK) is generated using a key derivation function (such as PBKDF2) using the password (P), salt (S), number of iterations (c), and key length (dkLen). The inputs to the key derivation function include: P: the password, which is the time ciphertext; S: the salt, which can be a byte sequence and is used to increase the randomness and security of the key; c: the number of iterations, which is used to increase computational complexity and prevent brute force attacks; dkLen: the length of the derived key. The dynamic nature of this embodiment is reflected in the fact that by changing the salt (S), different keys can be dynamically generated, thereby achieving dynamic encryption.

[0077] S106: When a metadata acquisition request for the target data asset is detected 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, the metadata is read to return data to the data acquisition end based on the metadata acquisition request.

[0078] As mentioned above, the pending difference value in this specification is pre-configured at the data acquisition end. If the data acquisition end is legal, the pending difference value is the same as the reference difference value.

[0079] In this document, encryption using a key generation protocol is also a method for the management end to achieve self-verification. If the result of the management end's encryption of the pending difference differs from the reference ciphertext, it may indicate that the data acquisition end is legitimate. Alternatively, it may be that the management end has been attacked, causing problems with the previous update process, or that the management end has been tampered with. In this case, the data acquisition end should be prohibited from acquiring data and disconnected from the blockchain, prohibiting access to the blockchain.

[0080] In a further optional embodiment, at the data acquisition end, the salt value is updated locally based on the real-time salt value generation rules in the key generation protocol and the pending difference value at the configuration time of the data acquisition end to obtain the pending salt value; when the blockchain-based data asset privacy protection encryption system detects the 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, then the pending difference value is parsed from the metadata acquisition request. The added salt value matching verification is conducive to further improving security. Optionally, to improve efficiency, when a metadata acquisition request for the storage address in the metadata is detected from the data acquisition end, a match based on the real-time salt value can be performed. When a metadata acquisition request for the target data asset other than the storage address is detected from the data acquisition end, the corresponding metadata is directly returned to the data acquisition end.

[0081] In an optional embodiment of this specification, in addition to the storage address, the metadata may also include any of the following: structured data of the target data asset (describing the internal structure and organization of the data asset to help users understand the components and relationships of the asset. For example, file format, file size, etc.), management data of the target data asset (information used to manage and maintain data assets, including asset creation, modification, and access rights, etc.), and technical data of the target data asset (describing the technical details of the data asset to help users understand the technical requirements and compatibility of the asset, such as encoding format, etc.).

[0082] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0083] The method described in this specification uses blockchain to store metadata for data assets. This facilitates combining the properties of blockchain and the natural laws applied when storing data on the blockchain, ensuring accurate metadata interaction between management and data acquisition terminals, and meeting user needs for data asset usage. Furthermore, the method described in this specification also incorporates the differences in value between data assets to achieve natural law-based encryption of metadata. This encryption technology can identify illegal data acquisition terminals and restrict their access, effectively preventing the theft of data assets by unscrupulous elements and improving the security of data assets.

[0084] Furthermore, this specification also provides an encryption system for protecting the privacy of data assets based on blockchain, wherein the encryption system for protecting the privacy of data assets based on blockchain includes a management end and a data acquisition end connected in communication:

[0085] The management terminal is configured to: determine at least two target time nodes; the target time nodes are selected from a plurality of time nodes that influence the value of the target data asset according to reference factors;

[0086] Based on a specified valuation algorithm, determine the difference in value of the target data asset at different target time points as a reference difference;

[0087] The metadata of the target data asset is stored in a blockchain; the metadata includes: the storage address of the target data asset; the reference difference value, and the reference ciphertext obtained by encrypting the reference difference value based on the target key, which are stored locally on the management terminal; 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 a time ciphertext generated based on the target time node as a password;

[0088] When a metadata acquisition request for the target data asset is detected from the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference value 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 value is pre-configured at the data acquisition end, and if the data acquisition end is legal, the pending difference value is the same as the reference difference value.

[0089] The system can execute the method in any of the aforementioned embodiments and can achieve the same or similar technical effects, which will not be described in detail here.

[0090] Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 2At the hardware level, the electronic device includes a processor and, optionally, an internal bus, a network interface, and memory. The memory may include internal memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for its services.

[0091] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 2 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0092] The memory is used to store programs. Specifically, the program may include program code, which includes computer operating instructions. The memory may include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0093] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming a blockchain-based encryption device for protecting the privacy of data assets. The processor executes the program stored in the memory and is specifically used to implement any of the aforementioned blockchain-based encryption methods for protecting the privacy of data assets.

[0094] The above application Figure 1The blockchain-based encryption method for protecting the privacy of data assets disclosed in the illustrated embodiments can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the aforementioned method can be performed by hardware integrated logic circuits within the processor or by software instructions. The aforementioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can 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, or discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly executed by a hardware decoding processor or by a combination of hardware and software modules within the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0095] The electronic device may also perform Figure 1 An encryption method for data asset privacy protection based on blockchain, and implement Figure 1 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.

[0096] An embodiment of the present application also proposes a computer-readable storage medium, which stores one or more programs, and the one or more programs include instructions. When the instructions are executed by an electronic device including multiple applications, any of the aforementioned blockchain-based encryption methods for protecting data asset privacy is executed.

[0097] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0098] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0099] These computer program instructions may 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 produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0100] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0101] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0102] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0103] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. 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 RAM (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 disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0104] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0105] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. An encryption method for protecting the privacy of data assets based on blockchain, characterized in that: The method adopts an encryption system for protecting the privacy of data assets based on blockchain; the encryption system for protecting the privacy of data assets based on blockchain includes a management terminal and a data acquisition terminal in communication connection, and the method is executed by the management terminal; the method includes: Determine at least two target time nodes; the target time nodes are selected from a plurality of time nodes where reference factors influence the value of the target data asset; Based on a specified valuation algorithm, determine the difference in value of the target data asset at different target time points as a reference difference; The metadata of the target data asset is stored in a blockchain; the metadata includes: the storage address of the target data asset; the reference difference value, and the reference ciphertext obtained by encrypting the reference difference value based on the target key, which are stored locally on the management terminal; 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 a time ciphertext generated based on the target time node as a password; When a metadata acquisition request for the target data asset is detected from the data acquisition end, if the pending ciphertext obtained by encrypting the pending difference value 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 value is pre-configured at the data acquisition end, and if the data acquisition end is legal, the pending difference value is the same as the reference difference value.

2. The method according to claim 1, wherein: The method further comprises: The designated valuation algorithm is determined according to the nature of the target data asset; the designated 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 comprises: The key generation protocol is used to obtain a target key through a dynamic key generation method based on 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 based on the pending difference at the configuration time of the data acquisition end; when the real-time salt value is updated, the reference ciphertext is regenerated according to the key generation protocol and updated.

4. The method according to claim 3, wherein: The method further comprises: At the data acquisition end, according to the real-time salt value generation rule in the key generation protocol, based on the configuration time of the pending difference value at the data acquisition end, the locally stored salt value is updated to obtain the pending salt value; When the blockchain-based data asset privacy protection encryption system detects the 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, the pending difference value is parsed from the metadata acquisition request.

5. The method according to claim 4, wherein: The method further comprises: 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.

6. The method according to claim 5, wherein: The method further comprises: When detecting a metadata acquisition request from the data acquisition end for the storage address in the metadata, performing matching based on the real-time salt value.

7. The method according to claim 5, wherein: The method further comprises: When detecting that the data acquisition end has requested metadata other than the storage address for the target data asset, the corresponding metadata is directly returned to the data acquisition end.

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

9. An encryption system for data asset privacy protection based on blockchain, characterized in that: The blockchain-based encryption system for data asset privacy protection includes a management terminal and a data acquisition terminal for communication connection: The management terminal is configured to: determine at least two target time nodes; the target time nodes are selected from a plurality of time nodes that influence the value of the target data asset according to reference factors; Based on a specified valuation algorithm, determine the difference in value of the target data asset at different target time points as a reference difference; Storing metadata of the target data asset in the blockchain; the metadata includes: the storage address of the target data asset; The reference difference value and the reference ciphertext obtained by encrypting the reference difference value based on the target key are stored locally by the management terminal; 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 a time ciphertext generated based on the target time node as a password; Upon detecting a metadata acquisition request from the data acquisition end for the target data asset, if a pending ciphertext obtained by encrypting the pending difference value 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 value is pre-configured at the data acquisition end. When the data acquisition end is legal, the pending difference value is the same as the reference difference value.

10. An electronic device comprising: processor; as well as A memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the method of any one of claims 1 to 8.

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