Smart medical information encryption method, system and device and storage medium

Abstract

The invention discloses an intelligent medical information encryption method, system and device and a storage medium, and the method comprises the steps: S1, obtaining original medical data information, and dividing the original medical data information to obtain a plurality of information blocks; s2, dynamically compressing the original medical data information according to an information block to obtain compressed medical data information; s3, encrypting the compressed medical data information by adopting an encryption algorithm based on fractional order Fourier transformation and a double-chaotic system; and S4, carrying out classification processing on the encrypted medical data information, and storing the encrypted medical data information according to different categories of the encrypted medical data information. The encryption performance and the statistical aggression resistance are good, and the encryption effect is good.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to a method, system, device and storage medium for encrypting intelligent medical information. Background Art

[0002] With the development of computer technology, the medical information of patients has basically been archived electronically. The content recorded in the medical information of patients belongs to the personal privacy of patients. Therefore, it is very necessary to take corresponding measures to prevent the leakage of patients' medical information. At the same time, due to the large amount of medical information data, storing it requires a large amount of storage space, increasing the transmission and storage costs.

[0003] Currently, to prevent the leakage of patients' medical information, the more common method is to open exclusive accounts and set the medical information to be accessible only to specified accounts (such as doctor accounts and corresponding patient accounts). However, using such a method, the role of preventing information leakage is limited, and there is still a risk of leakage of patients' medical information. Therefore, how to provide an effective solution to effectively prevent the leakage of medical data information has become an urgent problem in the prior art. Summary of the Invention

[0004] The present invention aims at the deficiencies in the prior art and provides a method, system, device and storage medium for encrypting intelligent medical information.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent medical information encryption method includes the following steps:

[0007] S1. Obtain the original medical data information and divide the original medical data information to obtain a number of information blocks;

[0008] S2. Dynamically compress the original medical data information according to the information blocks to obtain compressed medical data information;

[0009] S3. Use an encryption algorithm based on fractional Fourier transform and double chaotic systems to encrypt the compressed medical data information;

[0010] S4. Classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information.

[0011] To optimize the above technical solutions, the specific measures taken further include:

[0012] Further, S1 is specifically:

[0013] Taking n pieces of original medical data information as one round, using H i to represent the original medical data information in the i-th round, each piece of original medical data information in each round is divided into several information blocks, and F f is used to represent the f-th information block.

[0014] Furthermore, S2 is specifically as follows:

[0015] S21: Taking n pieces of original medical data information as one round, the original medical data information in the i-th round is represented as H i , and calculate the exclusive OR value of the information blocks in two consecutive pieces of original medical data information in the current round;

[0016] S22: Assign a counter to each information block. When the exclusive OR value of the information block is not equal to 0, increment the counter of this information block by one; when the exclusive OR value of the information block is equal to 0, do not change the value of its counter;

[0017] S23: When H i W j = H i W n , arrange the information blocks in ascending order of the counter values to obtain the arrangement order of the information blocks in the (i + 1)-th round, and clear the counter; where H i represents the original medical data information in the i-th round, H i W j is the j-th piece of medical data information in the i-th round of medical data information, and H i W n refers to the last piece of medical data information in the i-th round of medical data information; n is the total number of pieces of medical data information in the i-th round of medical data information;

[0018] S24: Reorganize the medical data information according to the arrangement order of the information blocks;

[0019] S25: Compress the reorganized medical data information to obtain the compressed medical data information; specifically including:

[0020] S251: Calculate the exclusive OR value of the corresponding information in the current piece of medical data information and the previous piece of medical data information in the i-th round of medical data information H i ;

[0021] S252: Assign a reorganization information header position to each exclusive OR value. When the exclusive OR value is 0, its corresponding reorganization information header position is also 0;

[0022] S253: Fill in each exclusive OR value and the reorganization information header position to achieve information compression.

[0023] Furthermore, S3 is specifically as follows:

[0024] S31. Obtain the compressed medical data information and perform DCT transformation. The compressed medical data information after transformation is represented by P;

[0025] S32. Generate two chaotic sequences through the Henon mapping, and its formula is: Starting from the (l + 1)-th term of the two sequences, intercept t terms to obtain two new sequences, which are respectively represented by the first chaotic sequence α′ and the second chaotic sequence β′, and sort the two new sequences from small to large. Calculate the position information of the two new sequences in the original chaotic sequence and record the position index; where, α l refers to the l-th chaotic value in the first chaotic sequence, and β l refers to the l-th chaotic value in the second chaotic sequence, and n is a non-negative number;

[0026] S33. Sort P according to the first chaotic sequence α′ to obtain the first row scrambling matrix ind a , and then sort the compressed medical data information P according to the second chaotic sequence β′ to obtain the second row scrambling matrix ind b ; Use the initial value in the Henon chaotic mapping and the chaotic system control parameter θ as the encryption key;

[0027] S34. Multiply the first row scrambling matrix ind a by the compressed medical data information P to obtain the matrix D. Perform the DFRFT transformation on it in the horizontal direction to obtain the complex matrix U. Multiply it by the second row scrambling matrix ind b to obtain the matrix O. Perform the DFRFT transformation on O in the vertical direction to finally obtain the encrypted complex matrix and obtain the amplitude spectrum;

[0028] S35. Randomly select a certain row and the corresponding column in the plaintext data, a total of 8 rows and the corresponding 8 columns are selected, and 1 group of optimal sequences composed of 0 and 1 are obtained through the optimization algorithm; in this sequence, 0 corresponds to the Logistic chaos, and 1 corresponds to the optimization algorithm. Encrypt the compressed medical data information multiple times according to the order of the optimal sequence; in the first encryption, use the matrix P after DCT processing as the input, and in each subsequent encryption, use the amplitude spectrum as the input for the next encryption; obtain the final ciphertext result.

[0029] Furthermore, S4 is specifically:

[0030] If the attribute of the encrypted medical data information exists, calculate the information gain of the encrypted medical data information using the attribute, and classify the encrypted medical data information according to the information gain;

[0031] If the attributes of the encrypted medical data information are lost, obtain the posterior probability, and the class to which the encrypted medical data information belongs is the class with the highest posterior probability.

[0032] Further, the information gain of the encrypted medical data information is calculated using the attributes, and the classification of the encrypted medical data information according to the information gain is specifically as follows:

[0033] Calculate the total expected information, and the formula is:

[0034] I(s1, s2,..., s i ,..., s m ) = -∑p i log2(p i )

[0035] Where, I(s1, s2,..., s i ,..., s m ) represents the total expected information, s m represents the number of samples in the m-th class, p i represents the probability that any sample belongs to class C i , C i represents the information class, i = 1, 2,..., m, and its quantity is represented by m; the number of samples in class C i is represented by s i .

[0036] Taking the attribute A as the standard, perform a partitioning process on all the encrypted medical data information to form v subsets (S1, S2,..., S v ), and calculate the amount of information E(A) required for the subsets to complete classification;

[0037] Solve for the information gain value:

[0038] Gain(A) = I(s1, s2,..., s i ,..., s m ) - E(A)

[0039] In the formula, Gain(A) represents the information gain value,

[0040] Classify the encrypted medical data information using the information gain.

[0041] The present invention also proposes an intelligent medical information encryption system, including:

[0042] An acquisition module, configured to acquire the original medical data information and partition the original medical data information to obtain a plurality of information blocks;

[0043] A compression module, configured to dynamically compress the original medical data information according to information blocks to obtain compressed medical data information;

[0044] An encryption module, configured to encrypt the compressed medical data information by using an encryption algorithm based on fractional Fourier transform and double chaotic systems;

[0045] A storage module, configured to classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information.

[0046] The present invention also provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the intelligent medical information encryption method as described above is implemented.

[0047] The present invention also provides a computer-readable storage medium storing a computer program, and the computer program causes a computer to execute the intelligent medical information encryption method as described above.

[0048] The beneficial effects of the present invention are as follows:

[0049] 1. Secure encryption is performed by using an encryption algorithm based on fractional Fourier transform and double chaotic systems to implement the encryption processing of information, so that the encryption performance and anti-statistical attack ability are good, and a good encryption effect is achieved.

[0050] 2. The encrypted medical data information is classified for data storage, so as to realize the automatic classification and storage of medical information and effectively complete the automated management of medical information. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is an implementation flowchart of the intelligent medical information encryption method proposed by the present invention;

[0052] Figure 2 is a schematic structural diagram of the intelligent medical information encryption system proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0054] Embodiment 1

[0055] The present invention provides a method for encrypting intelligent medical information, and its overall process is as Figure 1 shown, including the following steps:

[0056] S1. Obtain the original medical data information, and divide the original medical data information to obtain a number of information blocks; S1 is specifically:

[0057] Taking n pieces of original medical data information as one round, using H i to represent the original medical data information in the i-th round, divide each piece of original medical data information in each round into a number of information blocks, and use F f to represent the f-th information block.

[0058] S2. Dynamically compress the original medical data information according to the information blocks to obtain compressed medical data information; S2 is specifically:

[0059] S21. Taking n pieces of original medical data information as one round, the original medical data information in the i-th round is represented as H i , calculate the exclusive OR value of the information blocks in two consecutive pieces of original medical data information in the current round;

[0060] S22. Assign a counter to each information block. When the exclusive OR value of the information block is not equal to 0, increment the counter of this information block by one; when the exclusive OR value of the information block is equal to 0, do not change the value of its counter;

[0061] S23. When H i W j = H i W n , arrange the information blocks in ascending order of the counter values to obtain the arrangement order of the information blocks in the (i + 1)-th round, and clear the counter; where H i represents the original medical data information in the i-th round, H i W j is the j-th piece of medical data information in the i-th round of medical data information, and H i W n refers to the last piece of medical data information in the i-th round of medical data information; n is the total number of pieces of medical data information in the i-th round of medical data information;

[0062] S24. Reorganize the medical data information according to the arrangement order of the information blocks;

[0063] S221. When holds, then do not reorganize the j-th piece of medical data information W j ; where H0 is the medical data information in the first round, and H i is the medical data information in the i-th round, and W1 is the first piece of medical data information in the first round;

[0064] When is established, the order of the information blocks is fixed as the order in the initial round, and the medical data information is reorganized through a two-dimensional matrix. In this two-dimensional matrix, the first column is designated as the l-th information block F f , and the second number in each row is designated as the (f + 4)-th information block F f+4 ;

[0065] When H i ≠ H0 is established, the information is reorganized through a two-dimensional matrix according to the order of other rounds. In this two-dimensional matrix, the first number in each row is designated as F4, F5, …, F f+3 , and the second number in each row is designated as F f+4 ;

[0066] S25. Compress the reorganized medical data information to obtain compressed medical data information; specifically including:

[0067] S251. Calculate the exclusive OR value of the current piece of medical data information in the i-th round of medical data information H i and the corresponding information in the previous piece of medical data information;

[0068] S252. Assign a reorganized information header position to each exclusive OR value. When the exclusive OR value is 0, its corresponding reorganized information header position is also 0;

[0069] S253. Fill in each exclusive OR value and the reorganized information header position to achieve information compression.

[0070] S3. Use an encryption algorithm based on the fractional Fourier transform and double chaotic systems to encrypt the compressed medical data information; S3 is specifically as follows:

[0071] S31. Obtain the compressed medical data information and perform DCT transformation. The compressed medical data information after transformation is represented by P;

[0072] S32. Generate two chaotic sequences through the Henon map, and its formula is: Starting from the (l + 1)-th item of the two sequences, intercept t items to obtain two new sequences, which are respectively represented by the first chaotic sequence α′ and the second chaotic sequence β′, and sort the two new sequences from small to large. Calculate the position information of the two new sequences in the original chaotic sequence and record the position index; among them, α l refers to the l-th chaotic value in the first chaotic sequence, β l refers to the l-th chaotic value in the second chaotic sequence, and n is a non-negative number;

[0073] S33. Sort P according to the first chaotic sequence α′ to obtain the first row scrambling matrix ind a, then sort the compressed medical data information P according to the second chaotic sequence β′ to obtain the second row scrambling matrix ind b ; use the initial value in the Henon chaotic map and the chaos system control parameter θ as the encryption key;

[0074] S34. Multiply the first row scrambling matrix ind a by the compressed medical data information P to obtain the matrix D. Perform the DFRFT transform on it in the horizontal direction to obtain the complex matrix U. Multiply it by the second row scrambling matrix ind b to obtain the matrix O. Perform the DFRFT transform on O in the vertical direction to finally obtain the encrypted complex matrix and obtain the amplitude spectrum;

[0075] S35. Randomly select a certain row and the corresponding column in the plaintext data, a total of 8 rows and the corresponding 8 columns are selected, and 1 group of optimization sequences composed of 0 and 1 are obtained through the optimization algorithm; in this sequence, 0 corresponds to the Logistic chaos and 1 corresponds to the optimization algorithm. Encrypt the compressed medical data information multiple times according to the order of the optimization sequence; in the first encryption, use the matrix P after DCT processing as the input, and in each subsequent encryption, use the amplitude spectrum as the input for the next encryption; obtain the final ciphertext result.

[0076] S4. Classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information. S4 is specifically as follows:

[0077] If the attribute of the encrypted medical data information exists, calculate the information gain of the encrypted medical data information using the attribute, and classify the encrypted medical data information according to the information gain; the specific process of calculating the information gain of the encrypted medical data information using the attribute and classifying the encrypted medical data information according to the information gain is as follows:

[0078] Calculate the total expected information, and the formula is:

[0079] I(s1, s2,..., s i ,..., s m ) = -∑p i log2(p i )

[0080] where, I(s1, s2,..., s i ,..., s m ) represents the total expected information, s m represents the number of samples in the mth category, p i represents the probability that any sample belongs to the category C i of, Ci Indicates the information category, i = 1, 2, …, m, and its quantity is represented by m; C i The number of samples in the category is represented by s i Indicates

[0081] Taking the attribute A as the standard, all encrypted medical data information is partitioned to form v subsets (S1, S2, …, S v ), and calculate the amount of information E(A) required for the subsets to complete classification;

[0082] Solve the information gain value:

[0083] Gain(A) = I(s1, s2, …, s i , …, s m ) - E(A)

[0084] In the formula, Gain(A) represents the information gain value,

[0085] Classify the encrypted medical data information using the information gain.

[0086] If the attribute of the encrypted medical data information is lost, obtain the posterior probability, and the category to which the encrypted medical data information belongs is the category with the highest posterior probability.

[0087] Embodiment 2

[0088] The present invention proposes a smart medical information encryption system corresponding to the method of Embodiment 1. The structure of the system is as Figure 2 shown, including:

[0089] An acquisition module, configured to acquire the original medical data information and partition the original medical data information to obtain a plurality of information blocks;

[0090] A compression module, configured to dynamically compress the original medical data information according to the information blocks to obtain compressed medical data information;

[0091] An encryption module, configured to encrypt the compressed medical data information by using an encryption algorithm based on the fractional Fourier transform and a double chaotic system;

[0092] A storage module, configured to classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information.

[0093] The implementation manners of each module and the module functions in the system are completely consistent with the steps of the method in Embodiment 1, so details are not described herein again.

[0094] Embodiment 3

[0095] The present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the intelligent medical information encryption method as described in Embodiment 1 is implemented.

[0096] Embodiment 4

[0097] The present invention provides a computer-readable storage medium storing a computer program, which causes a computer to execute the intelligent medical information encryption method as described in Embodiment 1.

[0098] In the embodiments disclosed in the present application, the computer storage medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of the computer storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0099] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed in the present application can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the present application.

[0100] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the concept of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art in the technical field, several improvements and refinements made without departing from the principle of the present invention should be regarded as within the protection scope of the present invention.

Claims

1. A smart medical information encryption method, characterized in that: The following steps are involved: S1. Obtaining original medical data information, and dividing the original medical data information to obtain a plurality of information blocks; S2. Dynamically compressing the original medical data information according to the information block to obtain compressed medical data information; S3, using an encryption algorithm based on fractional Fourier transform and dual chaotic system to encrypt the compressed medical data information; S4. Classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information.

2. The smart medical information encryption method according to claim 1, characterized in that: S1 is specifically: Take n pieces of original medical data as one round, and use H i To represent the original medical data information of the i-th round, each piece of original medical data information of each round is divided into several information blocks, and F f Represents the fth information block.

3. The smart medical information encryption method according to claim 1, characterized in that: S2 is specifically: S21, n pieces of original medical data are considered as one round, and the original medical data of round i is represented as H i , calculate the XOR value of the information blocks in two consecutive original medical data information in the current round; S22, allocating a counter to each information block, when the XOR value of the information block is not equal to 0, the counter of the information block is incremented by one; when the XOR value of the information block is equal to 0, the counter value is not changed; S23, when H i W j =H i W n When the information blocks are arranged in the order of the counter value from small to large, the arrangement order of the information blocks in round i+1 is obtained, and the counter is cleared; wherein, H i H represents the original medical data information of the i-th round. i W j is the jth piece of medical data information in the i-th round of medical data information, H i W n refers to the last piece of medical data information in the i-th round of medical data information; n is the total number of medical data information in the i-th round of medical data information; S24, reorganizing the medical data information according to the arrangement order of the information blocks; S25, compressing the reorganized medical data information to obtain compressed medical data information; specifically including: S251, calculate the i-th round of medical data information H i The XOR value of the current piece of medical data information and the corresponding information in the previous piece of medical data information; S252, assigning a reorganization information header position to each XOR value, when the XOR value is 0, the corresponding reorganization information header position is also 0; S253, fill in the XOR values ​​and reorganize the information header to achieve information compression.

4. The smart medical information encryption method according to claim 1, characterized in that: S3 is specifically: S31, obtaining compressed medical data information, and performing DCT transformation, wherein the transformed compressed medical data information is represented by P; S32. Generate two chaotic sequences through Henon mapping, the formula is: Starting from the l+1th item of the two sequences, intercept the tth item to obtain two new sequences, which are represented by the first chaotic sequence α′ and the second chaotic sequence β′ respectively. The two new sequences are sorted from small to large, and the position information of the two new sequences in the original chaotic sequence is calculated, and the position index is recorded; where α l refers to the lth chaotic value in the first chaotic sequence, β l Refers to the lth chaotic value in the second chaotic sequence, n is a non-negative number; S33, sort P according to the first chaotic sequence α′, and obtain the first row of the scrambled matrix ind a Then, the compressed medical data information P is sorted according to the second chaotic sequence β′ to obtain the second row of the scrambled matrix ind b ; With the initial value in the Henon chaotic map and the chaotic system control parameter θ is the encryption key; S34, scramble the first row of matrix ind a Multiply it with the compressed medical data information P to obtain the matrix D, perform DFRFT transformation in the horizontal direction on it, and obtain the complex matrix U, which is combined with the second row scrambling matrix ing b Multiply them to get the matrix O, perform DFRFT transformation on O in the vertical direction, and finally get the encrypted complex matrix to get the amplitude spectrum; S35. Randomly select a row and a corresponding column in the plaintext data, and select 8 rows and 8 corresponding columns in total. Obtain an optimal sequence consisting of 0 and 1 through the optimization algorithm; in this sequence, 0 corresponds to Logistic chaos, and 1 corresponds to the optimization algorithm. The compressed medical data information is encrypted multiple times according to the order of the optimal sequence; in the first encryption, the matrix P after DCT processing is used as input, and in each subsequent encryption, the amplitude spectrum is used as the input for the next encryption; the final ciphertext result is obtained.

5. The smart medical information encryption method according to claim 1, characterized in that: S4 is specifically: If the attribute of the encrypted medical data information exists, the information gain of the encrypted medical data information is calculated using the attribute, and the encrypted medical data information is classified according to the information gain; If the attribute of the encrypted medical data information is lost, the posterior probability is obtained, and the category to which the encrypted medical data information belongs is the category with the highest posterior probability.

6. The smart medical information encryption method according to claim 5, characterized in that: The information gain of the encrypted medical data information is calculated by using the attribute, and the encrypted medical data information is classified according to the information gain as follows: Calculate the expected total amount of information, the formula is: I(s1,s2,…,s i ,…,s m )=-∑p i log2(p i ) Among them, I(s1,s2,…,s i ,…,s m ) represents the total amount of expected information, s m represents the number of samples in the mth category, p i Indicates that any sample belongs to category C i The probability of C i Indicates the information category, i = 1, 2, ..., m, and its number is represented by m; C i The number of samples in a class is denoted by s i express, Taking attribute A as the standard, all encrypted medical data information is divided into v subsets (s1, s2, ..., s v ), calculate the amount of information E(A) required for the subset to complete the classification; Solve for the information gain value: Gain(A)=I(s1,s2,...,s i ,...,s m )-E(A) In the formula, Gain(A) represents the information gain value, Use information gain to classify encrypted medical data information.

7. A smart medical information encryption system, characterized in that: include: An acquisition module, used for acquiring original medical data information and dividing the original medical data information to obtain a plurality of information blocks; A compression module, used for dynamically compressing the original medical data information according to the information block to obtain compressed medical data information; An encryption module, used to encrypt the compressed medical data information by using an encryption algorithm based on fractional Fourier transform and dual chaotic system; The storage module is used to classify the encrypted medical data information and store the encrypted medical data information according to different categories of the encrypted medical data information.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the intelligent medical information encryption method as described in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the intelligent medical information encryption method as described in any one of claims 1-6.

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