Data security sharing and exchanging method and system

Abstract

The invention provides a data security sharing and exchanging method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining to-be-shared data; 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 in combination with a random Hermite matrix; according to the time-varying access state vector, generating a fuzzy state vector about to-be-shared data in the data sharer through an orthogonal projection technology; sending the fuzzy vector to a data consumer; and carrying out dot product type implicit decoding on the fuzzy state vector in a data consumer by utilizing a pre-stored time-varying access state vector to complete safe sharing of the to-be-shared data. In the whole process, the orthogonal projection technology and the time-varying access state vector are combined, so that the security of data sharing is ensured, and efficient and real-time data exchange is also ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a data security sharing exchange method and system. BACKGROUND

[0002] Data security sharing exchange refers to the process of data exchange and sharing between data sharers and data consumers under the premise of ensuring data privacy and security. This process ensures that shared data cannot be accessed or tampered with by unauthorized users through encryption, access control, and decoding technologies. The core goal is to protect the confidentiality, integrity, and availability of data, and to avoid data leakage or damage during the exchange process.

[0003] With the rapid development of information technology and the advent of the big data era, data has become an indispensable asset for enterprises and individuals. However, the exchange process of data is often accompanied by the risk of privacy leakage and information abuse. Through secure sharing exchange, all parties can prevent sensitive information from being leaked while exchanging data, protect personal privacy and business secrets, and reduce legal liability and reputation loss caused by data leakage. Therefore, data security sharing exchange is not only crucial to privacy and security, but also promotes the development of digital economy and the construction of social trust.

[0004] Traditional data exchange technology often only focuses on data security, relying on explicit high-complexity encryption and decryption processes, resulting in high latency during data sharing, which cannot meet the real-time requirements of data sharing. Moreover, with the rapid improvement of computing power, traditional explicit encryption schemes are extremely vulnerable to exhaustive attacks, resulting in security risks in data sharing. SUMMARY

[0005] To solve the technical problem that traditional data exchange technology often only focuses on data security, relies on explicit high-complexity encryption and decryption processes, resulting in high latency during data sharing, which cannot meet the real-time requirements of data sharing, and with the rapid improvement of computing power, traditional explicit encryption schemes are extremely vulnerable to exhaustive attacks, resulting in security risks in data sharing, the present application provides a data security sharing exchange method and system.

[0006] The technical solutions provided by the embodiments of the present application are as follows: First aspect: The data security sharing exchange method provided by the embodiments of the present application comprises: Applied to a data security sharing exchange architecture composed of data sharers and data consumers connected to each other, the method comprises: S1: obtaining data to be shared; S2: generating a seed vector by the data sharer and sharing the seed vector with the data consumer; S3: generating a time-varying access state vector for implicit decoding in the data consumer based on the seed vector in combination with the random Hermite matrix; S4: generating a fuzzy state vector about the data to be shared in the data sharer by an orthogonal projection technique according to the time-varying access state vector; S5: sending the fuzzy state vector to the data consumer; S6: implicitly decoding the fuzzy state vector in the data consumer by using the pre-stored time-varying access state vector, and completing the secure sharing of the data to be shared; S4 specifically comprises: S401: encoding the data to be shared into a data vector; S402: generating an orthogonal projection operator for projecting the data vector to the orthogonal complement space of the time-varying access state vector based on the time-varying access state vector; S403: encoding the data vector by using the orthogonal projection operator to generate the fuzzy state vector about the data to be shared.

[0007] Optionally, the seed vector is shared to the data sharer in S2, specifically: The seed vector is shared to the data consumer through a secure channel, wherein the secure channel comprises a TLS secure channel, a QKD secure channel and an IPsec secure channel.

[0008] Optionally, S3 specifically comprises: S301: generating a basic access state vector by singular value decomposition algorithm in combination with the seed vector and a Gaussian random vector; S302: generating a dynamic access state vector in combination with the random Hermite matrix according to the basic access state vector, wherein the basic access state vector and the dynamic access state vector constitute the time-varying access state vector.

[0009] Optionally, S301 specifically comprises: S301A: splicing the seed vector and the Gaussian random vector along the column direction to obtain a spliced vector; S301B: singular value decomposition is performed on the spliced vector to obtain decomposition data comprising a left singular vector matrix; S301C: projecting the spliced vector to the left singular vector matrix to obtain the basic access state vector.

[0010] Optionally, after S3, it further comprises: The time-varying access state vector is shared to the data sharer through a secure channel.

[0011] Optionally, the formula form of the orthogonal projection operator is specifically: wherein, denotes an orthogonal projection operator, denotes a unit matrix with security dimension n, denotes a time-varying access state vector at time t, denotes the conjugate transpose of denotes the outer product of denotes the norm of

[0012] Optionally, S5 is specifically as follows: The fuzzy state vector is sent to the data consumer through a public channel.

[0013] Optionally, S6 specifically includes: S601: calculating the dot product between the fuzzy state vector and the time-varying access state vector; S602: dividing the calculation result by the norm of the time-varying access state vector; S603: taking the product of the result obtained by division and the time-varying access state vector; S604: summing the product result and the tiny error caused by floating point calculation to obtain a data vector of the data to be shared; S605: performing reverse encoding on the data vector to restore the data to be shared, thereby completing the secure sharing of the data to be shared.

[0014] Second aspect: The data security sharing exchange system provided by the embodiment of the application comprises: a processor; a memory, the memory storing computer readable instructions, the computer readable instructions being executed by the processor to implement the data security sharing exchange method of the first aspect.

[0015] Third aspect: The computer readable storage medium provided by the embodiment of the application stores a computer program, and the program is executed by the processor to implement the data security sharing exchange method of the first aspect.

[0016] The technical scheme provided by the embodiment of the application has at least the following beneficial effects: In the embodiment of the present application, the seed vector and time-varying access state vector generation technology are combined with the orthogonal projection technology to effectively encrypt the data to be shared, thereby avoiding the complex calculation process in the traditional encryption and decryption method and significantly improving the real-time performance and security of data sharing. Specifically, unlike the traditional scheme, the present application does not rely on complex encryption and decryption round functions, but performs efficient decryption through dot product and scaling operation, thereby greatly improving the decoding speed. The time-varying access state vector generated by the random Hermite matrix and the fuzzy state vector based on the orthogonal projection technology increase the difficulty of decryption, and the cracking complexity reaches the NP difficulty, so that even an attacker with strong computing power is almost impossible to obtain the original data through exhaustive brute force attack, thereby ensuring high security. The scheme not only ensures the security of data exchange, but also meets the real-time requirement of data sharing. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 A flowchart of a data security sharing exchange method provided by the embodiment of the present application is shown in the accompanying drawings. Figure 2 A structural diagram of a data security sharing exchange architecture provided by the embodiment of the present application is shown in the accompanying drawings. Figure 3 A decryption flowchart of a data security sharing exchange method provided by the embodiment of the present application is shown in the accompanying drawings. Figure 4 A structural diagram of a data security sharing exchange system provided by the embodiment of the present application is shown in the accompanying drawings. DETAILED DESCRIPTION

[0019] The technical solutions in the present application will be described below with reference to the drawings.

[0020] In order to make the technical problems, technical solutions and advantages of the present application more clear, the following will be described in detail with reference to the drawings and specific embodiments.

[0021] Reference is made to the accompanying drawings of the specification Figure 1 , which shows a flowchart of a data security sharing exchange method provided by the embodiment of the present application.

[0022] Reference is made to the accompanying drawings of the specification Figure 2 , which shows a structural diagram of a data security sharing exchange architecture provided by the embodiment of the present application.

[0023] Reference is made to the accompanying drawings of the specificationFigure 3 , shows a decryption process diagram of a data security sharing and exchange method provided by an embodiment of the present invention.

[0024] An embodiment of the present invention provides a data security sharing and exchange method, which is applied to a data security sharing and exchange architecture composed of interconnected data sharers and data consumers.

[0025] The processing flow of the data security sharing and exchange method may include the following steps: S1: Get the data to be shared.

[0026] Data to be shared refers to the data content owned by the data sharer that needs to be shared with data consumers. 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.

[0027] S2: Generate a seed vector through the data sharer and share the seed vector with the data consumer.

[0028] The seed vector is an initial vector generated by the data sharer and serves as the basis for the data encryption process. It is a randomly generated numerical vector used to subsequently generate the time-varying access state vector, ensuring uniqueness and unpredictability of each data sharing. The seed vector serves as the starting point for encryption during data sharing, avoiding the complexity of using a key in traditional encryption methods.

[0029] It should be noted that by generating and sharing seed vectors, the complex encryption key exchange and encryption and decryption operations used in traditional solutions are avoided, the encryption process is simplified, and the efficiency and security of data exchange are enhanced.

[0030] In a possible implementation, the seed vector is shared with the data sharer in S2, specifically: The seed vector is shared with the data consumer through a secure channel, where the secure channel includes a TLS secure channel, a QKD secure channel, and an IPsec secure channel.

[0031] As you can understand, data is transmitted to data consumers via secure channels, ensuring data security during transmission. Secure channels include TLS, QKD, and IPsec, each of which provides encryption and authentication mechanisms to prevent data interception or tampering during transmission. Through these highly secure transmission protocols, the seed vector sharing process is effectively protected, ensuring data confidentiality and integrity.

[0032] S3: Combined with random Hermitian matrices, a time-varying access state vector for implicit decoding is generated in the data consumer based on the seed vector.

[0033] A random Hermitian matrix is ​​a square matrix whose elements are complex numbers and equal to its conjugate transpose. It is used to generate random, time-varying access state vectors, enhancing the complexity and security of the encryption process. Its mathematical symmetry ensures the accuracy and unpredictability of data decoding.

[0034] Implicit decoding eliminates the need for traditional explicit decryption steps (such as the round function calculations used in traditional encryption). Through dot product and scaling operations, data consumers can quickly recover the original data without the complex decryption process. Implicit decoding improves decoding speed and reduces computational overhead.

[0035] The time-varying access state vector is generated by the data consumer based on a seed vector and a random Hermitian matrix. It changes over time. It provides a dynamic decoding reference during implicit decoding. This time-varying vector enables the data consumer to accurately decode the data.

[0036] 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 cracking. Furthermore, thanks to the implicit decoding method, data consumers can quickly recover the original data using only a dot product operation, improving the efficiency and real-time nature of the data sharing process.

[0037] In a possible implementation, S3 specifically includes: S301: Combining the seed vector and the Gaussian random vector, a basic access state vector is generated through a singular value decomposition algorithm.

[0038] The generation formula of the basic access state vector is as follows: in, represents the basic access state vector, represents the seed vector, represents a Gaussian random vector, Represents the basic access state vector ordered generator including vector concatenation, singular value decomposition, and subspace projection operations.

[0039] In a possible implementation, S301 specifically includes: S301A: Concatenate the seed vector and the Gaussian random vector along the column direction to obtain a concatenated vector.

[0040] The specific formula for the splicing vector is: wherein, denotes a spliced vector.

[0041] S301B: singular value decomposition is performed on the spliced vector to obtain decomposition data comprising a left singular vector matrix.

[0042] The decomposition formula is specifically: wherein, , and denote a left singular vector matrix, a singular value diagonal matrix and a right singular vector matrix respectively, and the subscript denotes transposition.

[0043] S301C: the spliced vector is projected onto the left singular vector matrix to obtain a basic access state vector.

[0044] The projection formula is specifically: wherein, denotes a basic access state vector, n denotes a security dimension consistent with the dimension of S or R, denotes the transpose of the largest n singular values in the left singular vector matrix.

[0045] Specifically, in this step, first, the seed vector and the Gaussian random vector are spliced along the column direction to obtain a spliced vector. Then, the spliced vector is decomposed into a left singular vector matrix, a singular value diagonal matrix and a right singular vector matrix through singular value decomposition. Finally, the spliced vector is projected through the left singular vector matrix to generate a basic access state vector. This process ensures that the generated access state vector has high randomness and unpredictability through the mathematical properties of singular value decomposition, greatly improves the security of data exchange, and makes the encryption and decoding process more efficient through dimension selection and projection operation, while ensuring the security and real-time performance of the system.

[0046] S302: a dynamic access state vector is generated according to the basic access state vector in combination with a random Hermite matrix, wherein the basic access state vector and the dynamic access state vector constitute a time-varying access state vector.

[0047] The generation formula of the dynamic access state vector is specifically: wherein, and denote the dynamic access state vectors at time t and time t-1 respectively, e denotes a natural constant, denotes a random Hermite matrix at time t, and i denotes an imaginary unit.

[0048] Specifically, in this step, the process ensures that the generated access state vector has randomness and complexity by combining the seed vector and the Gaussian random vector and using the singular value decomposition (SVD) algorithm. The base access state vector is combined with a random Hermitian matrix to further generate a dynamic access state vector that changes over time. The generation formula of the dynamic access state vector involves exponential operation and imaginary unit, increasing the complexity and security of the decoding process. By combining the time-varying access state vector and the Gaussian random vector, the security and anti-cracking ability of the data are greatly enhanced, while the dynamically generated vector avoids the security risks that static data may bring, ensuring the high security and unpredictability of the data exchange process.

[0049] In one possible implementation, after S3, further comprising: Sharing the time-varying access state vector to the data sharer through a secure channel.

[0050] It can be understood that by sharing the time-varying access state vector through a secure channel, it is ensured that the data will not be accessed or tampered with by unauthorized access during transmission.

[0051] S4: According to the time-varying access state vector, generate a fuzzy state vector about the data to be shared in the data sharer through orthogonal projection technology.

[0052] The orthogonal projection technology is a process of projecting one vector onto another vector space, so that the original data can be represented in that space. The orthogonal projection technology is used to associate the time-varying access state vector with the data to be shared, thereby generating a "fuzzy" version of the data, so that the data cannot be easily recovered or identified during transmission. This technology ensures the privacy and encryption effect of the data.

[0053] The fuzzy state vector is generated by the orthogonal projection technology, which is related to the original data but cannot be directly inferred back to the original data. Due to its "fuzziness", even if intercepted by a third party, unauthorized users cannot recover the original data, ensuring the security of the data during sharing.

[0054] It should be noted that the fuzzy state vector is generated by the orthogonal projection technology, effectively protecting the privacy of the data. The fuzzy state vector makes it impossible to crack or recover the original data even if the data is intercepted or intercepted. This not only increases the security of data sharing, but also ensures that even if the data is transmitted or stored in an insecure environment during sharing, the confidentiality of the data is still protected, preventing unauthorized access.

[0055] In one possible implementation, S4 specifically comprises: S401: Encode the data to be shared into a data vector.

[0056] S402: Generating an orthogonal projection operator for projecting the data vector into the orthogonal complement space of the time-varying access state vector based on the time-varying access state vector.

[0057] In one possible implementation, the formula form of the orthogonal projection operator is specifically: wherein, represents the orthogonal projection operator, represents a unit matrix with a security dimension of n, represents the time-varying access state vector at time t, represents the conjugate transpose of, represents the outer product of, represents the modulus of.

[0058] The orthogonal projection operator is used to project the data vector into the orthogonal complement space of the time-varying access state vector. This projection operator eliminates the part related to the time-varying access state vector, ensuring that the data is mapped to an orthogonal space, so that the original data becomes "fuzzy", increasing the security of the data.

[0059] It should be noted that this orthogonal projection operator makes the data vector projected into the orthogonal complement space of the time-varying access state vector, ensuring the fuzziness of the data. Even if the data is intercepted, an unauthorized user cannot recover the original data from the fuzzy state vector. In this way, the security of the data is enhanced, avoiding the risk of data leakage, while ensuring the privacy of data exchange.

[0060] S403: Encoding the data vector using the orthogonal projection operator to generate a fuzzy state vector about the data to be shared.

[0061] The formula form of the fuzzy state vector is specifically: wherein, represents the fuzzy state vector, represents the data vector of the data to be shared.

[0062] It should be noted that the data vector is encoded by the orthogonal projection operator to generate the fuzzy state vector, which contains part of the information of the original data, but cannot directly restore the original data. The advantage is that the fuzzy state vector makes it impossible for unauthorized users to recover the original data even if the data is intercepted or intercepted during transmission, thereby effectively preventing data leakage. Through this method, even if the attacker obtains the fuzzy state vector, it is difficult to crack the original data, greatly enhancing the security and privacy protection in the data sharing process.

[0063] Specifically, first, the data to be shared is encoded into a data vector, and then a time-varying access state vector is generated based on the orthogonal projection operator for projecting the data vector to the orthogonal complement space of the time-varying access state vector. By encoding the data vector through the orthogonal projection operator, a fuzzy state vector is generated, which is related to the original data but cannot directly restore the original data. By using the orthogonal projection technology, the data becomes "fuzzy", and even if the data is intercepted, unauthorized users cannot recover the original data, thereby effectively protecting the privacy and security of the data.

[0064] S5: Send the fuzzy state vector to the data consumer.

[0065] In one possible implementation, S5 is specifically: Send the fuzzy state vector to the data consumer through a public channel.

[0066] It should be noted that sending the fuzzy state vector to the data consumer through a public channel ensures that the data does not rely on a special channel with high security requirements during sharing, reducing communication costs. At the same time, since the fuzzy state vector itself cannot be directly cracked, even if it is transmitted over a public channel, the security of the data is still guaranteed, avoiding the risk of data leakage.

[0067] S6: Use the pre-stored time-varying access state vector to perform point-wise implicit decoding of the fuzzy state vector in the data consumer, completing the secure sharing of the data to be shared.

[0068] Specifically, the decryption process is called implicit decoding because it does not require an explicit decryption step (such as traditional encryption round function calculation), but only through point multiplication and scaling operations can the original data be quickly recovered, ensuring real-time security sharing while ensuring real-time performance, expanding application scenarios. If an unauthorized user extracts D from E, it needs to solve the NP-hard high-dimensional vector orthogonal problem, and when the security dimension is reasonably set, such as n ≥ 1024, even in the case of extremely strong computing power, the cracking time is far beyond the actual feasible range, making it impossible to achieve, ensuring the security of the sharing method.

[0069] It should be noted that by utilizing pre-stored time-varying access state vectors and a dot-product implicit decoding method, the original data can be quickly recovered, avoiding the complex decryption steps required in traditional encryption and decryption methods. This efficient decoding method significantly reduces computational overhead, improves decoding speed, and ensures the real-time nature of data sharing. Furthermore, since the high-dimensional vector orthogonality problem required for cracking is NP-hard, setting a reasonable security dimension makes brute-force cracking virtually impossible, thereby ensuring the security of data sharing.

[0070] In a possible implementation, S6 specifically includes: S601: Calculate the dot product between the fuzzy state vector and the time-varying access state vector.

[0071] S602: Divide the calculation result by the modulus of the time-varying access state vector.

[0072] S603: Take the product of the result of the division and the time-varying access state vector.

[0073] S604: Sum the product result and the small error caused by the floating-point calculation to obtain a data vector of the data to be shared.

[0074] S605: Reversely encode the data vector to restore the data to be shared.

[0075] The calculation formula for the data to be shared is as follows: in, A data vector representing the data to be shared, Represents the fuzzy state vector With time-varying access state vector The dot product between express The module length, Indicates a minor error.

[0076] It's important to note that in this step, the dot product calculation between the fuzzy state vector and the time-varying access state vector provides the basis for recovering the original data. By dividing the dot product result by the modulus of the time-varying access state vector and combining it with the product of the time-varying access state vector, and adjusting for minor floating-point errors, the vector of the data to be shared is ultimately restored. Implicit decoding relies solely on mathematical operations (dot products and scaling), avoiding the complex decryption steps required in traditional decryption, significantly improving the speed and efficiency of data recovery. Furthermore, by compensating for minor errors, the decoding process is highly accurate, enhancing the real-time nature and security of data sharing.

[0077] In the actual application process, the scheme ensures the security and real-time performance of data in the sharing process. First, by generating a seed vector and sharing through a secure channel, the complex key exchange and encryption and decryption operations in the traditional encryption scheme are avoided. Then, combined with the random Hermite matrix and time-varying access state vector generation technology, the encryption complexity of the data is increased to prevent unauthorized cracking. In the process of generating the fuzzy state vector, the data becomes "fuzzy" through the orthogonal projection technology, so that even if it is intercepted, the original data cannot be recovered. Finally, through the implicit decoding technology, the data is recovered only by dot product and scaling operation, avoiding the complex decryption steps in the traditional encryption and decryption, greatly improving the decoding efficiency and real-time performance. The whole process not only guarantees the security of data sharing, but also ensures efficient and real-time data exchange.

[0078] The technical scheme provided by the embodiment of the application has at least the following beneficial effects: In the embodiment of the application, the seed vector and time-varying access state vector generation technology are combined with the orthogonal projection technology to effectively encrypt the data to be shared, avoiding the complex calculation process in the traditional encryption and decryption method, and significantly improving the real-time performance and security of data sharing. Specifically, unlike the traditional scheme, the present application does not rely on complex encryption and decryption round functions, but performs efficient decryption through dot product and scaling operation, greatly improving the decoding speed. The time-varying access state vector generated by the random Hermite matrix and the fuzzy state vector based on the orthogonal projection technology increase the difficulty of decryption, and the cracking complexity reaches the NP difficulty, so that even an attacker with strong computing power is almost impossible to obtain the original data through exhaustive brute force cracking, ensuring extremely high security. The scheme not only guarantees the security of data exchange, but also meets the real-time performance requirements of data sharing.

[0079] Reference is made to the accompanying drawings Figure 4 , which shows a structural schematic diagram of a data security sharing exchange system provided by the application.

[0080] The application further provides a data security sharing exchange system 20 applied to the above-mentioned data security sharing exchange method, comprising: a processor 201.

[0081] a memory 202, the memory 202 storing computer readable instructions, the computer readable instructions being executed by the processor 201 to realize the data security sharing exchange method of the method embodiment.

[0082] The data security sharing exchange system 20 provided by the application can execute the above-mentioned data security sharing exchange method and achieve the same or similar technical effects. To avoid repetition, the application will not be described again.

[0083] It should be appreciated that a processor in the embodiments of the present application can be a central processing unit (CPU). The processor can also be other general purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general purpose processor can be a microprocessor or the processor can be any conventional processor.

[0084] It should also be appreciated that the memory in the embodiments of the present application can be a volatile memory or a nonvolatile memory, or can include both volatile and nonvolatile memory. The nonvolatile memory can be a read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically EPROM (EEPROM), or flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example, and not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0085] The above-described embodiments can be implemented in whole or in part by software, hardware (such as a circuit), firmware, or any combination thereof. When implemented in software, the above-described embodiments can be implemented in the form of 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, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0086] It should be understood that the term "and / or" herein merely describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. In addition, the character " / " herein generally represents that the associated objects before and after it are in an "or" relationship, but it can also represent an "and / or" relationship, which can be understood according to the context before and after it.

[0087] In the present application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0088] It should be understood that in various embodiments of the present application, the size of the sequence number of the above-described processes does not mean the order of execution, and the execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0089] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed 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 implementation should not be considered beyond the scope of the present application.

[0090] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0091] In several embodiments provided by the present application, 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 schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0092] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0093] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit.

[0094] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or parts of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0095] The embodiment of the present application provides a computer readable storage medium, which stores a computer program. The program is executed by a processor to realize the data security sharing exchange method described in the method embodiment.

[0096] The computer readable storage medium provided by the present application can realize the steps and effects of the data security sharing exchange method of the above-mentioned method embodiment. To avoid repetition, the present application will not be described again.

[0097] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0098] The following points need to be explained: (1) The drawings of the embodiments of the present application only involve the structures related to the embodiments of the present application, and other structures can refer to the usual design.

[0099] (2) For the sake of clarity, the thickness of the layers or regions is magnified or reduced in the drawings used to describe the embodiments of the present application, that is, the drawings are not drawn according to the actual proportion. It can be understood that when an element such as a layer, a film, a region or a substrate is referred to as being located "on" or "under" another element, the element can be "directly" located on or under another element or there can be an intermediate element.

[0100] (3) In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other to obtain new embodiments.

[0101] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A data security sharing and exchange method, characterized in that: The method is applied to a data security sharing and exchange architecture consisting of interconnected data sharers and data consumers, including: S1: Get the data to be shared; S2: Generate a seed vector through the data sharer, and share the seed vector with the data consumer; S3: generating a time-varying access state vector for implicit decoding in the data consumer based on the seed vector in combination with a random Hermitian matrix; S4: generating a fuzzy state vector of the to-be-shared data in the data sharer by using an orthogonal projection technique according to the time-varying access state vector; S5: Sending 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 secure sharing of the data to be shared; Wherein, the S4 specifically includes: S401: Encode the data to be shared into a data vector; S402: generating an orthogonal projection operator for projecting the data vector to an orthogonal complement space of the time-varying access state vector based on the time-varying access state vector; S403: Encode the data vector using the orthogonal projection operator to generate a fuzzy state vector of the data to be shared.

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

3. The data security sharing and exchange method according to claim 1, characterized in that: The S3 specifically includes: S301: Combining the seed vector and the Gaussian random vector, generating a basic access state vector by using a 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 security sharing and exchange method according to claim 3, characterized in that: The S301 specifically includes: S301A: Concatenate the seed vector and the Gaussian random vector along a column direction to obtain a concatenated vector; S301B: performing singular value decomposition on the concatenated vector to obtain decomposition data including a left singular vector matrix; S301C: Project the concatenated vector onto the left singular vector matrix to obtain the basic access state vector.

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

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

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

8. The data security sharing and exchange method according to claim 1, characterized in that: The 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 modulus of the time-varying access state vector; S603: taking the product of the result of the division and the time-varying access state vector; S604: summing the product result and a small error caused by floating-point calculation to obtain a data vector of the data to be shared; S605: Reversely encode the data vector to restore the data to be shared, thereby completing secure sharing of the data to be shared.

9. A data security sharing and exchange system, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for secure data sharing and exchange according to any one of claims 1 to 8 is implemented.

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