A method and system for secure data sharing and exchange

Abstract

This invention provides a secure data sharing and exchange method and system, relating to the field of data processing technology. The method includes: acquiring data to be shared; generating a seed vector through a data sharer and sharing the seed vector with a data consumer; generating a time-varying access state vector for implicit decoding in the data consumer based on the seed vector and a random Hermitian matrix; generating a fuzzy state vector about the data to be shared in the data sharer using orthogonal projection technology based on the time-varying access state vector; sending the fuzzy state vector to the data consumer; and performing dot-product implicit decoding on the fuzzy state vector in the data consumer using the pre-stored time-varying access state vector to complete the secure sharing of the data to be shared. The entire process, combining orthogonal projection technology and time-varying access state vectors, not only ensures the security of data sharing but also guarantees efficient and real-time data exchange.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for secure data sharing and exchange. Background Technology

[0002] Secure data sharing and exchange refers to the process of exchanging and sharing data between data sharers and data consumers while ensuring data privacy and security. This process utilizes technologies such as encryption, access control, and decoding to ensure that shared data is not accessed or tampered with by unauthorized users. Its core objective is to protect the confidentiality, integrity, and availability of data, preventing data leakage or damage during the exchange process.

[0003] With the rapid development of information technology and the arrival of the big data era, data has become an indispensable asset for businesses and individuals. However, the exchange of data is often accompanied by risks of privacy breaches and information misuse. Secure data sharing and exchange can ensure that all parties prevent the leakage of sensitive information, protect personal privacy and trade secrets, and reduce legal liability and reputational damage caused by data breaches. Therefore, secure data sharing and exchange is not only crucial for protecting privacy and security but also promotes the development of the digital economy and the building of social trust.

[0004] Traditional data exchange technologies often focus solely on data security, relying on explicit and highly complex encryption and decryption processes. This results in high latency during data sharing, failing to meet the real-time requirements of data sharing. Furthermore, with the rapid improvement of computing power, traditional explicit encryption schemes are easily cracked through brute force, leading to security vulnerabilities in data sharing. Summary of the Invention

[0005] To address the technical problems that traditional data exchange technologies often focus solely on data security, relying on explicit and highly complex encryption and decryption processes, resulting in high latency during data sharing and failing to meet the real-time requirements of data sharing, and that with the rapid improvement of computing power, traditional explicit encryption schemes are easily cracked through brute force, leading to security vulnerabilities in data sharing, this invention provides a secure data sharing and exchange method and system.

[0006] The technical solutions provided by the embodiments of the present invention are as follows:

[0007] First aspect:

[0008] This invention provides a data secure sharing and exchange method, comprising:

[0009] Applied to a secure data sharing and exchange architecture consisting of interconnected data sharers and data consumers, the methods include:

[0010] S1: Obtain the data to be shared;

[0011] S2: Generate a seed vector through the data sharer and share the seed vector with the data consumer;

[0012] S3: Combining a random Hermitian matrix, a time-varying access state vector for implicit decoding is generated in the data consumer based on the seed vector;

[0013] S4: Based on the time-varying access state vector, generate a fuzzy state vector about the data to be shared among the data sharers using orthogonal projection techniques;

[0014] S5: Send the fuzzy state vector to the data consumer;

[0015] S6: Using the pre-stored time-varying access state vector, implicitly decode the fuzzy state vector in the data consumer to complete the secure sharing of the data to be shared;

[0016] Specifically, S4 includes:

[0017] S401: Encode the data to be shared into a data vector;

[0018] S402: An orthogonal projection operator based on time-varying access state vectors for projecting data vectors onto the orthogonal complement space of time-varying access state vectors;

[0019] S403: Encode the data vector using the orthogonal projection operator to generate an fuzzy state vector about the data to be shared.

[0020] Optionally, in S2, the seed vector is shared with the data sharer, specifically as follows:

[0021] Seed vectors are shared to data consumers via secure channels, including TLS secure channels, QKD secure channels, and IPsec secure channels.

[0022] Optionally, S3 specifically includes:

[0023] S301: Combine seed vector and Gaussian random vector to generate basic access state vector through singular value decomposition algorithm;

[0024] S302: Generate a dynamic access state vector based on the basic access state vector and a random Hermitian matrix, wherein the basic access state vector and the dynamic access state vector constitute a time-varying access state vector.

[0025] Optionally, S301 specifically includes:

[0026] S301A: Concatenate the seed vector and the Gaussian random vector along the column direction to obtain the concatenated vector;

[0027] S301B: Perform singular value decomposition on the concatenated vectors to obtain decomposed data including the left singular vector matrix;

[0028] S301C: Project the concatenated vector onto the left singular vector matrix to obtain the basic access state vector.

[0029] Optionally, after S3, it also includes:

[0030] Share the time-varying access state vector to the data sharer through a secure channel.

[0031] Optionally, the formula for the orthogonal projection operator is as follows:

[0032]

[0033] in, This represents the orthogonal projection operator. This represents the identity matrix with a security dimension of n. This represents the time-varying access state vector at time t. express The conjugate transpose of . express The outer product, express The length of the module.

[0034] Optionally, S5 specifically refers to:

[0035] The fuzzy state vector is sent to the data consumer via a public channel.

[0036] Optionally, S6 specifically includes:

[0037] S601: Calculate the dot product between the fuzzy state vector and the time-varying access state vector;

[0038] S602: Divide the calculation result by the magnitude of the time-varying access state vector;

[0039] S603: The product of the result of division and the time-varying access state vector;

[0040] S604: Summing the product result with the small error caused by floating-point calculation, we obtain the data vector of the data to be shared;

[0041] S605: Reverse encode the data vector to restore the data to be shared, and complete the secure sharing of the data to be shared.

[0042] The second aspect:

[0043] An embodiment of the present invention provides a data security sharing and exchange system, comprising:

[0044] processor;

[0045] The memory stores computer-readable instructions, which, when executed by a processor, implement the secure data sharing and exchange method as described in the first aspect.

[0046] Third aspect:

[0047] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the data secure sharing and exchange method as described in the first aspect.

[0048] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0049] In this embodiment of the invention, seed vector and time-varying access state vector generation techniques, combined with orthogonal projection technology, are used to effectively encrypt the data to be shared, avoiding the complex calculation process in traditional encryption and decryption methods, and significantly improving the real-time performance and security of data sharing. Specifically, unlike traditional schemes, this invention does not rely on complex encryption and decryption round functions, but instead uses dot product and scaling operations for efficient decryption, greatly improving decoding speed. The time-varying access state vector generated using a random Hermitian matrix and the fuzzy state vector based on orthogonal projection technology increase the difficulty of decryption, achieving an NP-hard complexity, making it virtually impossible for even computationally powerful attackers to obtain the original data through brute-force attacks, ensuring extremely high security. This scheme not only guarantees the security of data exchange but also meets the real-time requirements of data sharing. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart illustrating a data security sharing and exchange method provided in an embodiment of the present invention;

[0052] Figure 2 This is a schematic diagram of a data security sharing and exchange architecture provided in an embodiment of the present invention;

[0053] Figure 3 A schematic diagram of the decryption process for a data security sharing and exchange method provided in an embodiment of the present invention;

[0054] Figure 4 This is a schematic diagram of a data security sharing and exchange system provided in an embodiment of the present invention. Detailed Implementation

[0055] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0056] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0057] Reference manual attached Figure 1 The diagram shows a flowchart of a data security sharing and exchange method provided by an embodiment of the present invention.

[0058] Reference manual attached Figure 2 The diagram shows a schematic representation of a data security sharing and exchange architecture provided by an embodiment of the present invention.

[0059] Reference manual attached Figure 3 The diagram illustrates a decryption process of a data security sharing and exchange method provided by an embodiment of the present invention.

[0060] This invention provides a secure data sharing and exchange method, applicable to a secure data sharing and exchange architecture consisting of interconnected data sharers and data consumers.

[0061] The processing flow of a secure data sharing and exchange method may include the following steps:

[0062] S1: Obtain the data to be shared.

[0063] In this context, "data to be shared" refers to the data content owned by the data sharer that needs to be shared with the data consumer. This data can be any form of digital information, such as text, images, audio, video, database records, sensor data, etc. In this step, the data sharer collects or generates this data and prepares it for sharing.

[0064] S2: Generate a seed vector through the data sharer and share the seed vector with the data consumer.

[0065] The seed vector is an initial vector generated by the data sharers, serving as the foundation for the data encryption process. It is a randomly generated numerical vector used to subsequently generate time-varying access state vectors, ensuring the uniqueness and unpredictability of each data sharing session. The seed vector acts as the starting point for encryption during data sharing, avoiding the complexity of using keys required in traditional encryption methods.

[0066] It should be noted that by generating and sharing seed vectors, the complex encryption key exchange and encryption / decryption operations used in traditional schemes are avoided, simplifying the encryption process and enhancing the efficiency and security of data exchange.

[0067] In one possible implementation, sharing the seed vector with the data sharer in S2 specifically involves:

[0068] Seed vectors are shared to data consumers via secure channels, including TLS secure channels, QKD secure channels, and IPsec secure channels.

[0069] Understandably, data is transmitted to consumers via secure channels to ensure data security during transmission. Secure channels include TLS, QKD, and IPsec channels, each providing encryption and authentication mechanisms to prevent data interception or tampering during transmission. Through these highly secure transport protocols, the seed vector sharing process is effectively protected, ensuring data confidentiality and integrity.

[0070] S3: Combining a random Hermitian matrix, a time-varying access state vector for implicit decoding is generated in the data consumer based on the seed vector.

[0071] The random Hermitian matrix is ​​a square matrix whose elements are complex numbers, and the matrix is ​​equal to its conjugate transpose. It is used to generate time-varying access state vectors with randomness, enhancing the complexity and security of the encryption process. Mathematically, it possesses symmetry, ensuring the accuracy and unpredictability of data decoding.

[0072] Implicit decoding refers to decoding that does not require traditional explicit decryption steps (such as round function calculations in traditional encryption). Through dot product and scaling operations, data consumers can quickly recover the original data without a complex decryption process. Implicit decoding improves decoding speed and reduces computational overhead.

[0073] A time-varying access state vector is a vector generated at the data consumer based on a seed vector and a random Hermitian matrix, which changes over time. It is used to provide a dynamic decoding reference during implicit decoding. With this time-varying vector, the data consumer can accurately decode the data.

[0074] Specifically, by combining a random Hermitian matrix to generate a time-varying access state vector, each generated access state vector is unique and unpredictable. This significantly increases the complexity of data encryption, preventing unauthorized users from cracking it. Simultaneously, due to the use of an implicit decoding method, data consumers can quickly recover the original data using only a dot product operation, improving the efficiency and real-time performance of the data sharing process.

[0075] In one possible implementation, S3 specifically includes:

[0076] S301: Combine seed vector and Gaussian random vector to generate basic access state vector through singular value decomposition algorithm.

[0077] The specific formula for generating the basic access state vector is as follows:

[0078]

[0079] in, Represents the basic access state vector. Represents the seed vector. Represents a Gaussian random vector. It represents the ordered generator of basic access state vectors, including vector concatenation, singular value decomposition, and subspace projection operations.

[0080] In one possible implementation, S301 specifically includes:

[0081] S301A: Concatenate the seed vector and the Gaussian random vector along the column direction to obtain the concatenated vector.

[0082] The specific formula for concatenating vectors is:

[0083]

[0084] in, This represents the concatenation of vectors.

[0085] S301B: Perform singular value decomposition on the concatenated vectors to obtain decomposed data including the left singular vector matrix.

[0086] The specific decomposition formula is as follows:

[0087]

[0088] in, , and Let these represent the left singular vector matrix, the singular value diagonal matrix, and the right singular vector matrix, respectively, with subscripts... This indicates transpose.

[0089] S301C: Project the concatenated vector onto the left singular vector matrix to obtain the basic access state vector.

[0090] The projection formula is as follows:

[0091]

[0092] in, This represents the basic access state vector, where n represents the security dimension consistent with either S or R. This represents the transpose of the n largest singular values ​​in the left singular vector matrix.

[0093] Specifically, in this step, a concatenated vector is first obtained by concatenating a seed vector and a Gaussian random vector along the column direction. Then, singular value decomposition (SVD) is used to decompose the concatenated vector into a left singular vector matrix, a singular value diagonal matrix, and a right singular vector matrix. Finally, the concatenated vector is projected onto the left singular vector matrix to generate the basic access state vector. This process, through the mathematical properties of singular value decomposition, ensures that the generated access state vector has high randomness and unpredictability, greatly improving the security of data exchange. Furthermore, the dimension selection and projection operations make the encryption and decoding processes more efficient, while simultaneously guaranteeing the system's security and real-time performance.

[0094] S302: Generate a dynamic access state vector based on the basic access state vector and a random Hermitian matrix, wherein the basic access state vector and the dynamic access state vector constitute a time-varying access state vector.

[0095] The specific formula for generating the dynamic access state vector is as follows:

[0096]

[0097] in, and Let represent the dynamic access state vectors at time t and time t-1, respectively, and let e represent the natural constant. Let represent the random Hermitian matrix at time t, and i represent the imaginary unit.

[0098] Specifically, in this step, a basic access state vector is generated by combining a seed vector and a Gaussian random vector, using the Singular Value Decomposition (SVD) algorithm. This process ensures that the generated access state vector possesses randomness and complexity. The basic access state vector is then combined with a random Hermitian matrix to further generate a dynamic access state vector, which changes over time. The generation formula for the dynamic access state vector involves exponential operations and imaginary units, increasing the complexity and security of the decoding process. By combining the time-varying access state vector and the Gaussian random vector, data security and resistance to hacking are significantly enhanced. Simultaneously, the dynamically generated vector avoids the security risks that static data might pose, ensuring high security and unpredictability in the data exchange process.

[0099] In one possible implementation, after S3, the following is also included:

[0100] Share the time-varying access state vector to the data sharer through a secure channel.

[0101] Understandably, sharing time-varying access state vectors through secure channels ensures that data is not accessed or tampered with during transmission.

[0102] S4: Based on the time-varying access state vector, generate a fuzzy state vector about the data to be shared among the data sharers using orthogonal projection techniques.

[0103] Orthogonal projection is the process of projecting a vector onto another vector space, allowing the original data to be represented in that space. Orthogonal projection is used to associate time-varying access vectors with data to be shared, generating a "fuzzy" version of the data that cannot be easily recovered or identified during transmission. This technique ensures data privacy and encryption.

[0104] The fuzzy vector is generated using orthogonal projection technology. It is related to the original data but cannot be directly deduced from it. Due to its "fuzziness," even if intercepted by a third party, unauthorized users cannot recover the original data, ensuring data security during the sharing process.

[0105] It should be noted that generating fuzzy state vectors through orthogonal projection effectively protects data privacy. Fuzzy state vectors ensure that even if data is intercepted or blocked, it cannot be deciphered or recovered to its original form. This not only increases the security of data sharing but also ensures that data confidentiality is protected even if it is transmitted or stored in an insecure environment during the sharing process, preventing unauthorized access.

[0106] In one possible implementation, S4 specifically includes:

[0107] S401: Encode the data to be shared into a data vector.

[0108] S402: Generate an orthogonal projection operator based on time-varying access state vectors for projecting data vectors onto the orthogonal complement space of time-varying access state vectors.

[0109] In one possible implementation, the formula for the orthogonal projection operator is as follows:

[0110]

[0111] in, This represents the orthogonal projection operator. This represents the identity matrix with a security dimension of n. This represents the time-varying access state vector at time t. express The conjugate transpose of . express The outer product, express The length of the module.

[0112] The orthogonal projection operator projects a data vector onto the orthogonal complement space of the time-varying access state vector. By eliminating the part related to the time-varying access state vector, this projection operator ensures that the data is mapped to an orthogonal space, making the original data "fuzzy" and increasing data security.

[0113] It's important to note that this orthogonal projection operator projects the data vector onto the orthogonal complement space of the time-varying access state vector, ensuring data ambiguity. Even if the data is intercepted, unauthorized users cannot recover the original data from the ambiguous state vector. This enhances data security, avoids the risk of data leakage, and guarantees the privacy of data exchange.

[0114] S403: Encode the data vector using the orthogonal projection operator to generate an fuzzy state vector about the data to be shared.

[0115] The formula for the fuzzy state vector is as follows:

[0116]

[0117] in, Represents the fuzzy state vector. A data vector representing the data to be shared.

[0118] It should be noted that encoding the data vector using the orthogonal projection operator generates an fuzzy state vector. This fuzzy state vector contains some information from the original data, but it cannot directly reconstruct the original data. Its advantage lies in the fact that even if the data is intercepted or blocked during transmission, unauthorized users cannot recover the original data, thus effectively preventing data leakage. Using this method, even if an attacker obtains the fuzzy state vector, they cannot easily decipher the original data, greatly enhancing security and privacy protection during data sharing.

[0119] Specifically, first, the data to be shared is encoded into a data vector. Then, an orthogonal projection operator is generated based on the time-varying access state vector to project the data vector onto the orthogonal complement space of the time-varying access state vector. Encoding the data vector using the orthogonal projection operator generates a fuzzy state vector. This vector is related to the original data but cannot directly reconstruct it. By making the data "fuzzy" through orthogonal projection, even if the data is intercepted, unauthorized users cannot recover the original data, thus effectively protecting data privacy and security.

[0120] S5: Send the fuzzy state vector to the data consumer.

[0121] In one possible implementation, S5 specifically includes:

[0122] The fuzzy state vector is sent to the data consumer via a public channel.

[0123] It should be noted that sending fuzzy state vectors to data consumers through a public channel ensures that data sharing does not rely on dedicated channels with high security requirements, thus reducing communication costs. Furthermore, since fuzzy state vectors themselves cannot be directly deciphered, data security is still guaranteed even when transmitted over a public channel, avoiding the risk of data leakage.

[0124] S6: Using the pre-stored time-varying access state vector, perform dot product implicit decoding on the fuzzy state vector in the data consumer to complete the secure sharing of the data to be shared.

[0125] Specifically, the decryption process is called implicit decoding because it does not require explicit decryption steps (such as round function calculations in traditional encryption). The original data can be quickly recovered using only dot product and scaling operations, ensuring secure sharing while maintaining real-time performance and expanding application scenarios. If an unauthorized user extracts D from E, an NP-hard high-dimensional vector orthogonality problem needs to be solved. When the security dimension is reasonably set, such as n≥1024, even with extremely powerful computing capabilities, the cracking time far exceeds the practically feasible range, making it impossible to implement, thus ensuring the security of this sharing method.

[0126] It should be noted that by utilizing pre-stored time-varying access state vectors and employing a dot-product implicit decoding method, the original data can be quickly recovered, avoiding the complex decryption steps found in traditional encryption and decryption methods. This efficient decoding method significantly reduces computational overhead, improves decoding speed, and ensures the real-time nature of the data sharing process. Furthermore, since the high-dimensional vector orthogonality problem required for cracking is NP-hard, setting a reasonable security dimension makes brute-force attacks virtually impossible, thus guaranteeing the security of data sharing.

[0127] In one possible implementation, S6 specifically includes:

[0128] S601: Calculate the dot product between the fuzzy state vector and the time-varying access state vector.

[0129] S602: Divide the calculation result by the magnitude of the time-varying access state vector.

[0130] S603: The product of the result of division and the time-varying access state vector.

[0131] S604: Summing the product result with the small error caused by floating-point calculation, we obtain the data vector of the data to be shared.

[0132] S605: Reverse encode the data vector to restore the data to be shared.

[0133] The specific formula for calculating the data to be shared is as follows:

[0134]

[0135] in, A data vector representing the data to be shared. Represents the fuzzy state vector With time-varying access state vector dot product between express The length of the mold, This indicates a tiny error.

[0136] It should be noted that in this step, the dot product calculation between the fuzzy state vector and the time-varying access state vector provides the foundation for recovering the original data. By dividing the dot product result by the magnitude of the time-varying access state vector and combining it with the product of the time-varying access state vector, plus a small floating-point calculation error, the vector of the data to be shared is finally restored. Implicit decoding, using only mathematical operations (dot product and scaling), avoids the complex decryption steps in traditional decryption processes, thus significantly improving the speed and efficiency of data recovery. Furthermore, compensation for minor errors ensures the accuracy of the decoding process, enhancing the real-time performance and security of data sharing.

[0137] In practical applications, this scheme ensures both security and real-time performance of data during sharing. First, by generating a seed vector and sharing it through a secure channel, the complex key exchange and encryption / decryption operations of traditional encryption schemes are avoided. Next, by combining random Hermitian matrices and time-varying access state vector generation techniques, the encryption complexity of the data is increased, preventing unauthorized cracking. During the generation of the fuzzy state vector, orthogonal projection techniques are used to "blur" the data, making it impossible to recover the original data even if intercepted. Finally, implicit decoding techniques are used to recover the data solely through dot product and scaling operations, avoiding the complex decryption steps of traditional encryption and decryption, significantly improving decoding efficiency and real-time performance. The entire process not only guarantees the security of data sharing but also ensures efficient and real-time data exchange.

[0138] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0139] In this embodiment of the invention, seed vector and time-varying access state vector generation techniques, combined with orthogonal projection technology, are used to effectively encrypt the data to be shared, avoiding the complex calculation process in traditional encryption and decryption methods, and significantly improving the real-time performance and security of data sharing. Specifically, unlike traditional schemes, this invention does not rely on complex encryption and decryption round functions, but instead uses dot product and scaling operations for efficient decryption, greatly improving decoding speed. The time-varying access state vector generated using a random Hermitian matrix and the fuzzy state vector based on orthogonal projection technology increase the difficulty of decryption, achieving an NP-hard complexity, making it virtually impossible for even computationally powerful attackers to obtain the original data through brute-force attacks, ensuring extremely high security. This scheme not only guarantees the security of data exchange but also meets the real-time requirements of data sharing.

[0140] Reference manual attached Figure 4 The diagram shows a structural schematic of a data security sharing and exchange system provided by the present invention.

[0141] The present invention also provides a data security sharing and exchange system 20, applied to the above-mentioned data security sharing and exchange method, comprising:

[0142] Processor 201.

[0143] The memory 202 stores computer-readable instructions, which, when executed by the processor 201, implement the data secure sharing and exchange method as described in the method embodiment.

[0144] The data security sharing and exchange system 20 provided by the present invention can execute the above-described data security sharing and exchange method and achieve the same or similar technical effects. To avoid duplication, the present invention will not elaborate further.

[0145] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0146] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0147] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0148] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0149] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0150] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0151] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0153] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0154] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0156] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] This invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the data secure sharing and exchange method as described in the method embodiment.

[0158] The computer-readable storage medium provided by this invention can realize the steps and effects of the data secure sharing and exchange method of the above method embodiments. To avoid repetition, this invention will not repeat them.

[0159] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0160] The following points need to be explained:

[0161] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0162] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the invention, i.e., these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element or there may be intermediate elements.

[0163] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0164] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for secure data sharing and exchange, characterized in that, Applied to a secure data sharing and exchange architecture consisting of interconnected data sharers and data consumers, the methods include: S1: Obtain the data to be shared; S2: Generate a seed vector through the data sharer and share the seed vector with the data consumer; S3: Combining the random Hermitian matrix, a time-varying access state vector for implicit decoding is generated in the data consumer based on the seed vector; S4: Based on the time-varying access state vector, generate a fuzzy state vector about the data to be shared in the data sharer using orthogonal projection technology; S5: Send the fuzzy state vector to the data consumer; S6: Using the pre-stored time-varying access state vector, perform dot product implicit decoding on the fuzzy state vector in the data consumer to complete the secure sharing of the data to be shared; Specifically, S4 includes: S401: Encode the data to be shared into a data vector; S402: Generate an orthogonal projection operator based on the time-varying access state vector for projecting the data vector onto the orthogonal complement space of the time-varying access state vector; S403: Encode the data vector using the orthogonal projection operator to generate an fuzzy state vector about the data to be shared.

2. The data secure sharing and exchange method according to claim 1, characterized in that, Sharing the seed vector with the data sharer in S2 specifically means: The seed vector is shared to the data consumer via a secure channel, wherein the secure channel includes a TLS secure channel, a QKD secure channel, and an IPsec secure channel.

3. The data secure sharing and exchange method according to claim 1, characterized in that, S3 specifically includes: S301: Combine the seed vector and the Gaussian random vector to generate the basic access state vector using the singular value decomposition algorithm; S302: Generate a dynamic access state vector based on the basic access state vector and the random Hermitian matrix, wherein the basic access state vector and the dynamic access state vector constitute the time-varying access state vector.

4. The data secure sharing and exchange method according to claim 3, characterized in that, S301 specifically includes: S301A: Concatenate the seed vector and the Gaussian random vector along the column direction to obtain the concatenated vector; S301B: Perform singular value decomposition on the spliced ​​vector to obtain decomposed data including the left singular vector matrix; S301C: Project the spliced ​​vector onto the left singular vector matrix to obtain the basic access state vector.

5. The data secure sharing and exchange method according to claim 2, characterized in that, Following S3, it also includes: The time-varying access state vector is shared to the data sharer through the secure channel.

6. The data secure sharing and exchange method according to claim 1, characterized in that, The formula for the orthogonal projection operator is as follows: in, This represents the orthogonal projection operator. This represents the identity matrix with a security dimension of n. This represents the time-varying access state vector at time t. express The conjugate transpose of . express The outer product, express The length of the module.

7. The data secure sharing and exchange method according to claim 1, characterized in that, Specifically, S5 is: The fuzzy state vector is sent to the data consumer via a public channel.

8. The data secure sharing and exchange method according to claim 1, characterized in that, S6 specifically includes: S601: Calculate the dot product between the fuzzy state vector and the time-varying access state vector; S602: Divide the calculation result by the magnitude of the time-varying access state vector; S603: The product of the result of division and the time-varying access state vector; S604: Summing the product result with the small error caused by floating-point calculation, we obtain the data vector of the data to be shared; S605: Reverse encode the data vector to restore the data to be shared, and complete the secure sharing of the data to be shared.

9. A data security sharing and exchange system, characterized in that, include: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the data secure sharing and exchange method as described in any one of claims 1 to 8.

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