Intelligent door lock encryption and decryption method and system based on biological information

Abstract

The invention discloses an intelligent door lock encryption and decryption method and system based on biological information. The method comprises the steps that the biological information of a user is acquired; performing coding processing on the biological information to obtain biological characteristic data of the biological information; based on a random attribute set, obtaining an encryption private key and access structure data, and encrypting the biological characteristic data by using the access structure data to obtain a biological characteristic ciphertext; based on the encryption private key, decrypting the biological characteristic ciphertext to obtain biological characteristic data; wherein the access structure data comprises an access structure tree and an access structure attribute value. According to the method, the random attribute set is introduced in the biological information encryption and decryption process, so that the safety in the biological information recording and transmission process is improved.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a smart door lock encryption and decryption method and system based on biometric information. Background Art

[0002] With the continuous development of smart home technology, smart door locks based on biometric information are becoming more and more popular. The principle is to collect the user's biometric information, such as fingerprints, faces, irises, etc., to identify the user, and unlock the door lock through verification and matching. In this process, data encryption technology is widely used in the collection, transmission and storage of biometric information.

[0003] At present, smart door locks also use biometric matching and verification algorithms to ensure that only authorized users can unlock. In addition, in order to ensure the security of biometric information, smart door locks also use physical protection measures, such as protective covers and fingerprint protection films.

[0004] However, smart door locks based on biometric information still have some shortcomings and risks in data encryption. Biometric features cannot be changed, and once biometric information is leaked or misused, the user's safety and privacy will be threatened. Summary of the invention

[0005] In order to solve at least one of the technical problems mentioned above, the present invention provides an encryption and decryption method for a smart door lock based on biometric information.

[0006] In a first aspect, a method for encrypting and decrypting a smart door lock based on biometric information is provided, the method comprising:

[0007] Obtaining the user's biometric information;

[0008] Encoding the biometric information to obtain biometric characteristic data of the biometric information;

[0009] Based on the random attribute set, an encryption private key and access structure data are obtained, and the biometric data is encrypted using the access structure data to obtain a biometric ciphertext;

[0010] Decrypting the biometric ciphertext based on the encrypted private key to obtain biometric data;

[0011] Wherein, accessing structural data includes: accessing the structure tree and accessing structural attribute values.

[0012] Preferably, after encoding the biometric information to obtain the biometric characteristic data of the biometric information, the method further includes:

[0013] Calculate feature mutual information on the biometric data, select features with mutual information values ​​greater than a first preset value and merge them into a first feature set, and merge unselected features into a second feature set;

[0014] The first feature set and the second feature set are combined to calculate mutual information, and features with mutual information values ​​less than a second preset value are discarded to obtain biometric data after dimensionality reduction;

[0015] The biometric data to be converted is determined as the biometric data.

[0016] Preferably, before obtaining the encrypted private key and access structure data based on the random attribute set, the process further includes obtaining a public key and a master private key, specifically including:

[0017] Based on the security parameter λ, randomly select a large prime number q = 1 mod (2λ) and a positive integer p, where p < < q, gcd (p, q) = 1, and let f (x) = x n +1∈Z[x], is the ring of integer polynomials of f(x) and q, is the error distribution, the system randomly selects a∈R q and sk∈R q , select the uniform random error term e∈χ, let pk=a·sk+pe∈R q ; For each attribute name a in the system i , randomly selected and the error term e i ∈χ, calculate Get the public key and the master private key

[0018] Preferably, the encryption private key is obtained according to the master private key, the public key and the random attribute set, and the process is as follows:

[0019] Randomly select e'∈χ and calculate D=sk+pe'∈R q , determine the attribute value in the random attribute set The corresponding attribute name is a i , choose uniform random error term calculate Get the encrypted private key

[0020] Preferably, the access structure tree is constructed by using Shamir's threshold secret sharing method.

[0021] Preferably, encrypting the biometric data using the access structure data to obtain a biometric ciphertext includes:

[0022] Set the attribute value of the access structure tree to Randomly select r∈R q and error terms e”,e” e,l ∈χ, calculate C0=pk·r·s+m+pe”∈R q , Get the biometric ciphertext

[0023] Preferably, decrypting the biometric ciphertext based on the encryption private key to obtain biometric data includes:

[0024] Determine whether the user attribute name satisfies the access structure tree;

[0025] If not satisfied, decryption fails;

[0026] If satisfied, calculate Among them, L l is the Lagrange coefficient, I A To decrypt the attribute set, the biometric data m=m'mod p is obtained.

[0027] In a second aspect, a smart door lock encryption and decryption system based on biometric information is provided, the system comprising:

[0028] A data acquisition unit, used to acquire the user's biometric information;

[0029] A data encoding unit, used for encoding the biometric information to obtain biometric characteristic data of the biometric information;

[0030] A data encryption unit, used to obtain an encryption private key and access structure data based on a random attribute set, and encrypt the biometric data using the access structure data to obtain a biometric ciphertext;

[0031] The data decryption unit is used to decrypt the biometric ciphertext based on the encryption private key to obtain biometric data; wherein the access structure data includes: an access structure tree and access structure attribute values.

[0032] In a third aspect, an electronic device is provided, comprising: a processor and a memory, the memory being used to store computer program code, the computer program code comprising computer instructions, and when the processor executes the computer instructions, the electronic device executes the smart door lock encryption and decryption method based on biometric information as described in any one of the above items.

[0033] In a fourth aspect, a computer-readable storage medium is provided, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the smart door lock encryption and decryption method based on biometric information as described in any one of the above items.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention discloses a method and system for encrypting and decrypting a smart door lock based on biometric information. The method comprises obtaining the biometric information of a user; encoding the biometric information to obtain the biometric data of the biometric information; obtaining an encryption private key and access structure data based on a random attribute set, and encrypting the biometric data using the access structure data to obtain a biometric ciphertext; decrypting the biometric ciphertext based on the encryption private key to obtain the biometric data; wherein the access structure data comprises: an access structure tree and an access structure attribute value. The present invention introduces a random attribute set in the process of biometric information encryption and decryption, thereby improving the security of the biometric information recording and transmission process.

[0036] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0038] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0039] Figure 1 A schematic diagram of a flow chart of a biometric information-based smart door lock encryption and decryption method provided by an embodiment of the present invention;

[0040] Figure 2 A schematic diagram of a biometric information-based smart door lock encryption and decryption system provided by an embodiment of the present invention

[0041] Figure 3 A schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0044] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0045] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0046] In addition, in order to better illustrate the present invention, numerous specific details are provided in the following specific embodiments. It should be understood by those skilled in the art that the present invention can be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present invention.

[0047] At present, there are still some shortcomings and risks in data encryption of smart door locks based on biometric information. Biometric features cannot be changed. Once biometric information is leaked or misused, the user's security and privacy will be threatened. To this end, the present invention provides an encryption and decryption method for smart door locks based on biometric information, which improves the security of biometric information by performing encryption based on a random attribute set during the recording and transmission of biometric information.

[0048] Example 1

[0049] Provides a smart door lock encryption and decryption method based on biometric information, reference Figure 1 , methods include:

[0050] S100, obtaining biometric information of the user;

[0051] It should be noted that biometric information refers to measurable and identifiable information of individual physical characteristics. Common biometric information includes but is not limited to fingerprints, facial images, irises, voiceprints, etc. These biometric information can be obtained in different ways. Fingerprint information can be obtained by scanning and collecting the fingerprint surface patterns through a fingerprint sensor. Facial images can be captured through cameras and algorithms. Iris features can be obtained by scanning the user's eye iris image through infrared light and a high-resolution camera. Voiceprint information is recorded and analyzed by a voice recognition device to record and analyze the user's voice features. In this embodiment, facial images are used as the authentication information required for unlocking the door.

[0052] S200, encoding the biometric information to obtain biometric characteristic data of the biometric information;

[0053] The encoding process may be a convolution process, or a combination of a convolution process, a normalization process, and an activation process.

[0054] In one possible implementation, the facial image of the user is encoded step by step through multiple coding layers in sequence, wherein each coding layer includes convolution processing, normalization processing and activation processing, and the convolution processing, normalization processing and activation processing are connected in series in sequence, that is, the output data of the convolution processing is the input data of the normalization processing, and the output data of the normalization processing is the input data of the activation processing. The convolution processing can be implemented by convolving the data of the input coding layer with a convolution kernel. By convolving the input data of the coding layer, feature information can be extracted from the input data of the coding layer, and the size of the input data of the coding layer can be reduced to reduce the amount of calculation for subsequent processing. By normalizing the data after convolution processing, the correlation between different data in the data after convolution processing can be removed, and the distribution difference between different data in the data after convolution processing can be highlighted, which is conducive to continuing to extract feature information from the normalized data through subsequent processing. The activation processing can be implemented by substituting the normalized data into the activation function. Optionally, the activation function is a rectified linear unit (ReLU).

[0055] S300, based on the random attribute set, obtaining an encryption private key and access structure data, and using the access structure data to encrypt the biometric data to obtain a biometric ciphertext;

[0056] S400, decrypting the biometric ciphertext based on the encryption private key to obtain biometric data; wherein the access structure data includes: an access structure tree and access structure attribute values.

[0057] It should be noted that the random attribute set consists of two parts: attribute name and attribute value. Assume that the system has n different attribute names, that is, N = (a1, a2, ..., a n ), where a i Represents the attribute name. Define each attribute name has n i Different attribute values, that is, each attribute name set in, Represents the attribute name a i The specific attribute values ​​that can be selected are: in, And the user can only choose to set one attribute value under each attribute name. For example, random attribute set 1 is (face skin gloss information: xxxxx, face skin color information: aaaaaa, face wrinkle information: bbbbbb, ..., face skin texture information: hhhhhh).

[0058] The access structure data is represented by (τ, Z), where (τ, Z) is the access structure tree, and the leaf nodes of the access structure tree correspond to the attribute names in the random attribute set. is a randomly assigned attribute value, and Z is hidden in the ciphertext during encryption. A decryption user's attribute set satisfies (τ, Z) if and only if , the ciphertext can be decrypted.

[0059] Preferably, after encoding the biometric information to obtain the biometric characteristic data of the biometric information, the method further includes:

[0060] Calculate feature mutual information on the biometric data, select features whose mutual information values ​​are greater than a first preset value and merge them into a first feature set, and merge unselected features into a second feature set;

[0061] The first feature set and the second feature set are combined to calculate mutual information, and features with mutual information values ​​less than a second preset value are discarded to obtain biometric data after dimensionality reduction;

[0062] The biometric data that is subsequently converted is determined as the biometric data.

[0063] It should be noted that the mutual information method is used to delete redundant or irrelevant features in the original feature space according to certain criteria and select a set of feature subsets to shorten the algorithm running time and improve the algorithm accuracy.

[0064] As an effective measure of uncertainty, mutual information theory is widely used in feature selection. Assume that the feature set is F, and F = {f1, f2, ..., fm}, where m represents the number of features. Assume that the label set is C, and C = {c1, c2, ..., cs}, where s represents the number of label values ​​in this data set. Assume f i is any feature in F, p(f i ) is a discrete probability density function, then a feature f i The surprise value (surprise value refers to the information brought by a specific event) is: I(f i )=-log2p(f i ). Let f i is any feature in F, where l represents feature f i The number of eigenvalues ​​of i The information entropy (information entropy is a mathematical measure of uncertain phenomena. The larger its value, the greater the uncertainty, and the more information is needed to determine the occurrence of an event) is defined as:

[0065] Let f i is any feature in F, then feature f i The mutual information (the amount of information contained in a random variable about another random variable. The larger the mutual information, the more important the feature, and vice versa) of the label set C is defined as:

[0066] In this embodiment, the mutual information I(f i ,C) are sorted in descending order, and the features whose mutual information values ​​are greater than the first preset value are selected as the first feature set. The influence of these features is crucial. The first feature set is combined with the remaining features (the second feature set) as a condition to calculate the mutual information I (f 1j ,f 2j ), sort them in ascending order, select the features whose mutual information value is less than the second preset value, reduce the redundancy of the features, and use them as auxiliary feature sets to avoid repeated calculations and improve the speed of feature selection.

[0067] Preferably, before obtaining the encrypted private key and accessing the structure data based on the random attribute set, the public key and the master private key are obtained, specifically including:

[0068] Based on the security parameter λ, randomly select a large prime number q = 1 mod (2λ) and a positive integer p, where p < < q, gcd (p, q) = 1, and let f (x) = x n +1∈Z[x], is the ring of integer polynomials of f(x) and q, is the error distribution, the system randomly selects a∈R q and sk∈R q , select the uniform random error term e∈χ, let pk=a·sk+pe∈R q ; For each attribute name a in the system i , randomly selected and the error term e i ∈χ, calculate Get the public key and the master private key

[0069] Preferably, the encryption private key is obtained according to the master private key, the public key and the random attribute set, and the process is as follows:

[0070] Randomly select e'∈χ and calculate D=sk+pe'∈R q , determine the attribute value in the random attribute set The corresponding attribute name is a i , choose uniform random error term calculate Get the encrypted private key

[0071] Preferably, the access structure tree is constructed using Shamir's threshold secret sharing method.

[0072] It should be noted that the Lagrange coefficient L is first defined i,S , for i∈Z qand set S, we have The extended Shamir threshold secret sharing method is as follows:

[0073] 1) Let P = {P1, P2, ..., P n} is the participant set, t is the threshold, s∈R q is the password to be shared.

[0074] 2) The sharer chooses a polynomial of order t-1 Among them, a j ∈R q And a j ≠0.

[0075] 3) The sharer selects n different elements Participants P i Calculate i =f(x i )∈R q , and (x i ,s i ) is sent to participant P i .

[0076] 4) Any t users can reconstruct s using the Lagrange interpolation method, given that but make So share the secret

[0077]

[0078] The access tree is constructed using the extended Shamir threshold secret sharing method, and the leaf nodes are associated with the attribute name a set by the encryptor. i Correspondingly, among them, a i ∈τ, and let l be the attribute name index of the leaf node in the access tree. Secret sharing is as follows. Randomly select a ring element s∈R q , set the root node of the access tree to s, mark the node as allocated, mark its child nodes as unallocated, and perform the following operations on all unallocated non-leaf nodes. If the operator is ∨, and its child nodes are unallocated, assign the ring element s to its child nodes and mark them as allocated; if the operator is ∧, and its child nodes are unallocated, randomly select the ring element s l ∈R q (j=1,2,…,n-1), where n is the number of its child nodes, and the nth child node is assigned as a ring element And mark it as assigned; if the operator is of and its child nodes are not assigned, a polynomial of order t-1 is randomly selected Using Shamir(t,n) threshold secret sharing method, s∈R qSplit, where t is the threshold value and n is the number of child nodes, then its child node l is assigned the ring element s l =f(l) and marked as allocated.

[0079] Preferably, the biometric data is encrypted using the access structure data to obtain a biometric ciphertext, including:

[0080] Let the attribute value of the access structure tree be Randomly select r∈R q and error terms e”,e” e,l ∈χ, calculate C0=pk·r·s+m+pe”∈R q , Get biometric ciphertext

[0081] Preferably, the biometric ciphertext is decrypted based on the encryption private key to obtain the biometric data, including:

[0082] Determine whether the user attribute name satisfies the access structure tree;

[0083] If not satisfied, decryption fails;

[0084] If satisfied, calculate Among them, L l is the Lagrange coefficient, I A To decrypt the attribute set, the biometric data m=m'mod p is obtained.

[0085] Example 2

[0086] Provides a smart door lock encryption and decryption system based on biometric information, reference Figure 2 ,include:

[0087] A data acquisition unit, used to acquire the user's biometric information;

[0088] A data encoding unit, used for encoding the biometric information to obtain biometric characteristic data of the biometric information;

[0089] A data encryption unit, used to obtain an encryption private key and access structure data based on a random attribute set, and to encrypt the biometric data using the access structure data to obtain a biometric ciphertext;

[0090] The data decryption unit is used to decrypt the biometric ciphertext based on the encryption private key to obtain the biometric data; wherein the access structure data includes: an access structure tree and access structure attribute values.

[0091] In some embodiments, the functions or modules included in the system provided by the disclosed embodiments of the present invention can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0092] Example 3

[0093] See also Figure 3 , Figure 3 The structure diagram of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 3 The electronic device 600 shown includes: at least one processor 601, a memory 602, at least one network interface 604 and other user interfaces 603. The various components in the electronic device 600 are coupled together via a bus system 605. It is understood that the bus system 605 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 605 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, the bus system 605 is not shown in FIG. Figure 3 Various buses are labeled as bus system 605 .

[0094] The user interface 603 may include a display, a keyboard, or a pointing device (eg, a mouse, a trackball, a touch pad, or a touch screen).

[0095] It can be understood that the memory 602 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 602 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0096] In some implementations, the memory 602 stores the following elements, executable units or data structures, or a subset thereof, or an extended set thereof: an operating system 6021 and an application 6022 .

[0097] The operating system 6021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application 6022 includes various application programs, such as a media player (Media Player), a browser (Browser), etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present invention can be included in the application 6022.

[0098] In an embodiment of the present invention, by calling the program or instructions stored in the memory 602, specifically, the program or instructions stored in the application 6022, the processor 601 is used to execute the steps of a smart door lock encryption and decryption method based on biometric information provided by each method embodiment.

[0099] Example 4

[0100] A computer-readable storage medium is provided, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the smart door lock encryption and decryption method based on biometric information provided in any of the above embodiments.

[0101] Those skilled in the art will appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0102] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

[0103] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A smart door lock encryption and decryption method based on biometric information, characterized in that: The method comprises: Obtain user's biometric information; Encoding the biometric information to obtain biometric characteristic data of the biometric information; Based on the random attribute set, an encryption private key and access structure data are obtained, and the biometric data is encrypted using the access structure data to obtain a biometric ciphertext; Decrypting the biometric ciphertext based on the encrypted private key to obtain biometric data; Wherein, accessing structural data includes: accessing the structure tree and accessing structural attribute values.

2. According to the biometric information-based smart door lock encryption and decryption method of claim 1, it is characterized in that: After encoding the biometric information to obtain the biometric characteristic data of the biometric information, the method further includes: Calculate feature mutual information on the biometric data, select features with mutual information values ​​greater than a first preset value and merge them into a first feature set, and merge unselected features into a second feature set; The first feature set and the second feature set are combined to calculate mutual information, and features with mutual information values ​​less than a second preset value are discarded to obtain biometric data after dimensionality reduction; The biometric data to be converted is determined as the biometric data.

3. According to the biometric information-based smart door lock encryption and decryption method of claim 1, it is characterized in that: Before obtaining the encrypted private key and access structure data based on the random attribute set, the method further includes obtaining the public key and the master private key, specifically including: Based on the security parameter λ, a large prime number q = 1 mod (2λ) and a positive integer p are randomly selected, where p < < q, gcd (p, q) = 1, and is the ring of integer polynomials of f(x) and q, is the error distribution, the system randomly selects a∈R q and sk∈R q , select the uniform random error term e∈χ, let pk=a·sk+pe∈R q ; For each attribute name a in the system i , randomly selected and the error term e i ∈χ, calculate Get the public key and the master private key 4. According to the biometric information-based smart door lock encryption and decryption method of claim 3, it is characterized in that: The encryption private key is obtained according to the master private key, the public key and the random attribute set, and the process is as follows: Randomly select e'∈χ and calculate D=sk+pe'∈R q , determine the attribute value in the random attribute set The corresponding attribute name is a i , choose uniform random error term calculate Get the encrypted private key 5. According to the biometric information-based smart door lock encryption and decryption method of claim 1, it is characterized in that: The access structure tree is constructed by using Shamir's threshold secret sharing method.

6. According to claim 4, a biometric information-based smart door lock encryption and decryption method is characterized in that: The step of encrypting the biometric data using the access structure data to obtain a biometric ciphertext includes: Let the attribute value of the access structure tree be Randomly select r∈R q and error terms e”,e” e,l ∈χ, calculate C0=pk·r·s+m+pe”∈R q , Get the biometric ciphertext 7. According to claim 5, a biometric information-based smart door lock encryption and decryption method is characterized in that: The decrypting the biometric ciphertext based on the encryption private key to obtain the biometric data includes: Determine whether the user attribute name satisfies the access structure tree; If not satisfied, decryption fails; If satisfied, calculate Among them, L l is the Lagrange coefficient, I A To decrypt the attribute set, the biometric data m=m'mod p is obtained.

8. An intelligent door lock encryption and decryption system based on biometric information, characterized in that: The system comprises: A data acquisition unit, used to acquire the user's biometric information; A data encoding unit, used for encoding the biometric information to obtain biometric characteristic data of the biometric information; A data encryption unit, used to obtain an encryption private key and access structure data based on a random attribute set, and encrypt the biometric data using the access structure data to obtain a biometric ciphertext; The data decryption unit is used to decrypt the biometric ciphertext based on the encryption private key to obtain biometric data; wherein the access structure data includes: an access structure tree and access structure attribute values.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store computer program codes, wherein the computer program codes include computer instructions. When the processor executes the computer instructions, the electronic device executes the biometric information-based smart door lock encryption and decryption method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the biometric information-based smart door lock encryption and decryption method as described in any one of claims 1 to 7.

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