CN113141359A - Password system for privacy protection of electronic medical images of Internet of things - Google Patents
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Abstract
The invention relates to a password system for protecting privacy of electronic medical images of the Internet of things. The invention mainly comprises the following steps that (1) a password system for protecting the privacy of the electronic medical image of the Internet of things is provided; (2) a Pseudo Random Number Generator (PRNG) algorithm based on a 2D-ICM and 2D-LASM chaotic system is provided; (3) a rapid medical image parallel encryption method is provided.
Description
Technical Field
The invention relates to the field of information security and privacy protection, in particular to a password system for protecting the privacy of an electronic medical image of the Internet of things.
Background
Privacy protection has become a primary requirement for modern applications such as social media, internet of things (IoT), and electronic medical systems. In the field of electronic medicine, many medical imaging devices are widely connected and used to facilitate the diagnosis and treatment process of doctors, such as Magnetic Resonance Imaging (MRI) for brain tumor diagnosis, lung Computed Tomography (CT) for lung detection, and endoscopes for detecting the stomach. These personal medical images should be kept secret to ensure that the privacy of the patient is not compromised. Medical images are generally characterized by a huge amount of data and have high requirements on safety. Conventional text data-based encryption schemes cannot be directly applied to electronic image data due to limitations in the characteristics of the image data itself. In addition, a satisfactory level of security is achieved in a fast, lightweight encryption manner, taking into account the constraints of real-time data acquisition. The invention provides a double-chaos system-based privacy protection password system for medical images of the Internet of things. The encryption system can protect the medical image of the patient from being damaged by the middleman, and the medical image is in a ciphertext form during transmission and storage, so that any medical information of the patient cannot be disclosed. Aiming at medical images with huge data volume, the password system adopts a parallel mode, and only little time is needed for encryption, so that the real-time processing requirement of medical data acquisition under a real scene is met. A bidirectional ciphertext feedback mechanism is introduced in the encryption process, and the high safety of the system is ensured by the generated avalanche effect. The password system can encrypt the gray medical image and the color medical image, the generated encrypted image does not reveal any information, and only allows an authorized user to decrypt, thereby effectively protecting the privacy of patients.
Disclosure of Invention
The invention aims to solve the safety problem in the transmission and the access of the electronic medical image. Therefore, the invention provides a password system for protecting the privacy of the electronic medical images of the Internet of things, which mainly comprises three contents:
1. a password system for protecting the privacy of the electronic medical image of the Internet of things is provided;
2. a Pseudo Random Number Generator (PRNG) algorithm based on a 2D-ICM and 2D-LASM chaotic system is provided;
3. a rapid medical image parallel encryption method is provided.
The specific contents are as follows:
1. a cryptosystem for privacy protection of thing networking electron medical image is proposed
In our cryptographic system framework (fig. 1), medical images of a patient are acquired by a medical visual sensing device, such as color gastroscopic images, grayscale CT images, MRI images, and the like. Each patient has a key belonging to the patient, and after the data acquisition end passes the authentication, the encryption key of the patient can be acquired from the hospital key management system. The medical image acquired by the sensing equipment is encrypted by using the encryption key and then transmitted to the cloud platform, and is stored in a ciphertext mode. When the medical image data of the patient needs to be checked, after the user logs in the client and passes the authentication, the authorized user can acquire the decryption key of the patient from the hospital key management system, and the ciphertext image stored in the cloud platform is decrypted, so that the medical data of the patient can be checked. By the method, the medical data of the patient can be stored in an encrypted manner on the cloud platform, so that the privacy information of the patient is well protected. The patient can check own data at the mobile terminal, and medical data of the patient can be accessed only after a hospital doctor, a remote specialist, a researcher and the like obtain authorization through authentication. In the present encryption system, a symmetric cryptographic mechanism is used, and thus the encryption key and the decryption key are the same. The basic key of the encryption algorithm, namely the initial condition of the chaotic system, is stored in the key management system, and the basic key of all patients is the same. The updating process of the key firstly carries out hash calculation on the ID of each patient, the obtained hash code is unique because the ID value of each patient is different, and the hash code and the basic key are used for carrying out correlation calculation to obtain an updated key, namely the true key for the encryption algorithm. And the updating part of the key is completed and stored at the key management system end, the data acquisition end or the client sends an authentication request, and the updated key is obtained after the authentication. The key used by each patient for data encryption is different, where the encryption key is the updated key. The benefit of using a different key for each patient is that the privacy of the medical care information for other patients remains secure, assuming that one patient's key is inadvertently compromised.
2. A Pseudo Random Number Generator (PRNG) algorithm based on a 2D-ICM and 2D-LASM chaotic system is provided
The 2D-ICM is a two-dimensional hyperchaotic system with complex chaotic behavior, and the mathematical expression thereof is as follows:
the system parameters a and b are real numbers, a ≠ 0, b ≠ 0, x, y ∈ [ -1, 1 ]. The 2D-ICM has two positive Lyapunov exponents, and is hyperchaotic in the whole parameter range, so that the track of the 2D-ICM is difficult to infer. The lyapunov index value of the 2D-ICM increases with increasing parameter, and as large a lyapunov index value as possible can be obtained by adjusting the parameter. The larger the Lyapunov exponent is, the more obvious the chaotic characteristic of the system is, and the higher the safety is when the system is used for a cryptosystem.
The 2D-LASM is a two-dimensional chaotic system having high sensitivity to an initial value. The 2D-LASM is derived from the Sin mapping and the Logistic mapping, and the mathematical expression is as follows:
the system parameters u, v, mu belongs to [0, 1], when mu belongs to [0.37, 0.38] < U [0.4, 0.42] < U [0.44, 0.93], the 2D-LASM has chaotic behavior, when mu belongs to [0.37, 0.38] < U [0.4, 0.42] < U [0.44, 0.93], the 2D-LASM has two positive Lyapunov indexes, and the system has hyperchaotic behavior.
We use these two-dimensional chaotic maps to generate a random sequence associated with the plaintext image. Although the sequence generated by the chaotic system has no period in theory, the precision of the computer is limited, and the periodic phenomenon can occur due to the rounding of the precision in practical implementation. In consideration of the problem of limited precision, the chaos sequences generated by the two chaos systems are subjected to some operations and randomly combined, so that each random sequence used for encryption is jointly generated by the 2D-ICM and the 2D-LASM, and the degradation problem caused by limited precision calculation is avoided. We discard the first 1000 of the generated sequence to eliminate the effect of the initial value on the generated sequence. In addition, the hash value of the patient ID is obtained through the SHA-512 hash algorithm and is used for updating the encryption key, and high security of medical image information is guaranteed. The specific steps of our designed PRNG algorithm are described as follows:
the method comprises the following steps: the SHA-512 algorithm is used to calculate the hash H of the patient ID, which is divided into 64 eight-bit blocks, denoted H ═ H1，h2，...，hi]Wherein i is 1, 2i∈[0，255]。
Step two: the following calculation is made from the hash value of the patient ID
Step three: for x in fixed key0，y0，u0，v0Update as follows
Step four: and respectively iterating the 2D-ICM chaotic system and the 2D-LASM chaotic system mn +1000 times by using the updated key, and discarding the first 1000 values of each sequence to obtain four random sequences x, y, u and v.
Step five: t is obtained by the following calculation1，T2，T3，
For T1，T2，T3Sorting from small to large to obtain T ═ Sort (T)1，T2，T3)。
Step six: and randomly recombining X, Y, U and V in the step four to obtain four random sequences X, Y, U and V.
3. Provides a rapid medical image parallel encryption method
Most medical image acquisition systems diagnose patients by capturing color or gray key images in real-time video images through a high-resolution vision sensor, so a rapid medical image encryption algorithm is provided, which can be used for color and gray images and ensures the privacy and confidentiality of the key medical images. A method for updating a key and feeding back a ciphertext is introduced, so that an attacker cannot know any information about medical data of a patient from a ciphertext image and cannot construct a cryptanalysis model to acquire required information.
The method comprises the following steps: according to a fixed key x provided by a key management system0，y0，u0，v0A, b, mu and the patient ID, the four random sequences X, Y, U, V are obtained by the PRNG algorithm of content two.
Step two: the medical images I are grouped according to the parallel arrangement in the encryption module. The medical image is converted into a one-dimensional vector Iv, which is common assuming that each group contains l pixel values
And (4) grouping. When l is set, N is guaranteed to be an integer.
Step three: change Iv into a matrix I of size l NNUsing K1To INPerforming row scrambling to obtain Ip in a scrambling mode
Ip(K1(i)，：)＝IN(i，：)，i＝1，2，…，N
Step four: using K2Performing block cipher text feedback forward diffusion on Ip to obtain Id1In a diffusion manner of
Step five: using K3To Id1Performing feedback back diffusion on the block cipher text to obtain Id2In a diffusion manner of
Step six: let Id2Is used for each packet ofgDenotes the use of K4The internal pixels of the N groups are scrambled in parallel to obtain a scrambled group IgpThe scrambling mode is expressed as
Igp(K4(i))＝Ig(i)，i＝1，2，…，l
Step seven: using K5To IgpPerforming parallel block cipher text feedback forward diffusion to obtain Igd1In a diffusion manner of
Step eight: using K6To Igd1Performing feedback back diffusion on the block cipher text to obtain Igd2In a diffusion manner of
Step nine: splicing each group finished by parallel diffusion into a one-dimensional vector C with the length of l x N in sequencev。
Step ten: c is to bevAnd converting the image into a ciphertext image C with the size of m x n, and storing the ciphertext image C in the cloud platform in a ciphertext mode.
Because a rapid encryption algorithm is needed when the medical sensor of the internet of things performs data acquisition and encryption transmission, a parallel mode is adopted to meet the real-time processing requirement of medical images in a real scene. Fig. 2 is a block diagram of parallel encryption, assuming that the algorithm is run on a multi-threaded computer, dividing the image into N packets according to the number of threads available on the computer, and then performing global scrambling and bi-directional diffusion on the main thread on the N packets of the entire image. Then, entering a parallel phase, each thread completes scrambling and bi-directional diffusion of the internal elements of each packet. And finally, transmitting each encrypted packet to a main thread, finishing the final merging operation by the main thread according to the packet sequence, and outputting the final password image. When running in a parallel model, our proposed encryption algorithm takes very little time. Our method may not significantly improve image encryption efficiency when there are fewer pixels to be encrypted, but is well suited for medical images of large data volumes, with significant advantages over traditional encryption algorithms.
After the authorized user of the client passes the authentication, the background can obtain the decryption key of the key management system, and four random sequences X, Y, U and V are generated through the PRNG algorithm. And the ciphertext data returned by the cloud platform is subjected to inverse operation of the encryption algorithm to obtain the decrypted medical data and visually display the decrypted medical data.
Drawings
FIG. 1 is a system framework diagram of the present invention
FIG. 2 is a parallel structure diagram of the present invention
Detailed Description
The invention provides a password system for protecting privacy of electronic medical images of the Internet of things, which mainly comprises the following five steps:
constructing a PRNG;
(II) generating a key stream;
(III) group scrambling;
(IV) packet diffusion;
(V) scrambling in parallel in the group;
(VI) parallel diffusion in the group;
the implementation platform is MATLAB R2020b and the operating system is win 10. The method comprises the following specific steps:
the first step is as follows: construction of PRNG
Calculating the hash value of the patient ID, and updating the encryption key on the basis key of the key management center. And iterating the 2D-ICM chaotic system and the 2D-LASM chaotic system, and recombining the generated four sequences to obtain four random sequences.
The second step is that: generating a keystream
Four random sequences are obtained by using a PRNG algorithm, and the random sequences are preprocessed to generate six key streams required in encryption.
The third step: packet scrambling
Grouping plaintext images in a main thread and then according to a key stream K1The plaintext block is scrambled.
The fourth step: packet flooding
Using keystream K in main thread2Forward ciphertext feedback diffusion is carried out on plaintext blocks, and then the key stream K is used3And performing reverse ciphertext feedback diffusion.
The fifth step: intra-group parallel scrambling
In each thread, according to the key stream K4The pixels within a group are scrambled and the keystream used within each group is different.
Parallel diffusion in group (VI)
In each thread, a keystream K is used5Forward ciphertext feedback diffusion is carried out on the pixels of each group, and then the key stream K is used6And performing reverse ciphertext feedback diffusion.
Claims (4)
1. A cryptosystem for privacy protection of electronic medical images of the Internet of things is characterized in that:
(1) a password system for protecting the privacy of the electronic medical image of the Internet of things is provided;
(2) a Pseudo Random Number Generator (PRNG) algorithm based on a 2D-ICM and 2D-LASM chaotic system is provided;
(3) a rapid medical image parallel encryption method is provided.
2. The password system for privacy protection of electronic medical images of the internet of things according to claim 1, wherein: the medical image of the patient is acquired through the medical visual sensing equipment, after the data acquisition end passes the authentication, the encryption key of the patient can be acquired from the hospital key management system, the medical image is encrypted by using the encryption key and then transmitted to the cloud platform, and the medical image is stored in a ciphertext mode. When the medical image data of the patient needs to be checked, after the user logs in the client and passes the authentication, the authorized user can acquire the decryption key of the patient from the hospital key management system, and the ciphertext image stored in the cloud platform is decrypted, so that the medical data of the patient can be checked. By the method, the medical data of the patient can be stored in an encrypted manner on the cloud platform, so that the privacy information of the patient is well protected. In encryption systems, a symmetric cryptographic mechanism is used, the base key of all patients being the same. The true key for the encryption algorithm needs to be calculated by correlating the hash code of the patient ID with the basic key, so that the actual key used for data encryption is different for each patient, and the medical privacy information of other patients is still safe in case that the key of one patient is leaked carelessly.
3. The Pseudo Random Number Generator (PRNG) algorithm based on a 2D-ICM and 2D-LASM chaotic system according to claim 1. The method is characterized in that: the 2D-ICM and 2D-LASM chaotic systems are adopted to generate random sequences, although the sequences generated by the chaotic systems have no period theoretically, the accuracy of a computer is limited, and a periodic phenomenon can occur due to accuracy rounding in actual implementation. In consideration of the problem of limited precision, the chaotic sequences generated by the two chaotic systems are subjected to certain operations and randomly combined, so that each random sequence used for encryption is jointly generated by the 2D-ICM and the 2D-LASM, and the degradation problem caused by the limited precision calculation is avoided. The first 1000 of the generated sequence are discarded to eliminate the effect of the initial value on the generated sequence. The Hash value of the patient ID is obtained through the SHA-512 Hash algorithm and is used for updating the encryption key, and high safety of medical image information is guaranteed.
4. The rapid parallel encryption method for medical images according to claim 1, characterized in that: the encryption algorithm adopts a parallel mode to meet the real-time processing requirement of the medical image in a real scene. Assuming the algorithm is run on a multi-threaded computer, the image is divided into N packets according to the number of threads available on the computer, and then the N packets of the entire image are subjected to overall scrambling and bi-spreading on the main thread. Entering a parallel phase, each thread completes scrambling and bi-directional diffusion of each packet's internal elements. And finally, transmitting each encrypted packet to a main thread, finishing the final merging operation by the main thread according to the packet sequence, and outputting the final password image. When running in a parallel model, our proposed encryption algorithm takes very little time. Our method may not significantly improve image encryption efficiency when there are fewer pixels to be encrypted, but is well suited for medical images of large data volumes, with significant advantages over traditional encryption algorithms. By adopting the bidirectional ciphertext feedback method, the generated avalanche effect prevents an attacker from knowing any information about the medical data of the patient from the ciphertext image and constructing a cryptanalysis model to acquire required information.
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