CN117807620B - Dynamic encryption storage method for information - Google Patents
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Abstract
The invention relates to the technical field of data encryption, in particular to an information dynamic encryption storage method. The method comprises the steps of obtaining cloud computing information data and a cloud computing reference key; acquiring a dynamic feature matrix according to the dynamic change of the data; obtaining a topological feature matrix according to the topological structure of the cloud computing network, and further obtaining key parameters; obtaining a reference key matrix, and dividing to obtain a block matrix; acquiring an initial block matrix according to the dynamic characteristics of data, and scanning to acquire a random scanning path sequence; carrying out quantum walking at a first position in the sequence to obtain a probability distribution matrix, and further obtaining a quantum matrix; obtaining a quantum transformation key, thereby obtaining encrypted data; the encrypted data is stored and the quantum transformation key is updated. According to the method, the unique dynamic key is generated by combining the dynamic characteristics of the cloud computing information data and utilizing the quantum entanglement principle, so that the cloud computing information data is not easy to break down and is suitable for the cloud computing information data which dynamically changes.
Description
Technical Field
The invention relates to the technical field of data encryption, in particular to an information dynamic encryption storage method.
Background
In the background of the wide application of cloud storage nowadays, data security is becoming a core problem of concern for users. Traditional encryption methods face increasingly complex challenges in cloud environments, especially with significant problems in key management and performance. Along with the continuous increase of user data on a cloud platform, the traditional static encryption mode obviously cannot meet the requirements of a dynamic data environment. For this reason, there is an urgent need for a more flexible and efficient dynamic encryption storage method to cope with evolving threats and data management challenges.
In the prior art, when the cloud computing information data is encrypted and stored by adopting a data encryption algorithm, the situation that the key content is totally updated by utilizing a traditional key generation algorithm occurs due to large data quantity and discrete distribution of the cloud computing information data, so that the cloud computing information data needs to be encrypted again, computing resources are seriously occupied, and the dynamic change of the cloud computing information data cannot be adapted.
Disclosure of Invention
In order to solve the technical problems that when a data encryption algorithm is adopted to encrypt and store cloud computing information, the data volume of the cloud computing information data is large, the distribution is discrete, the traditional key generation algorithm is utilized to update all keys and encrypt the cloud computing information data again, computing resources are seriously occupied, and the dynamic change of the cloud computing information cannot be adapted, the invention aims to provide an information dynamic encryption storage method, which adopts the following technical scheme:
A method for dynamically encrypting and storing information, the method comprising:
acquiring cloud computing information data and a cloud computing reference key which need to be stored in an encrypted mode;
acquiring a dynamic feature matrix of the cloud computing information data according to the storage duty ratio, the update time and the data type diversity of the cloud computing information data; obtaining a topological feature matrix of the cloud computing network according to the topological structure features of the cloud computing network; obtaining key parameters of the cloud computing reference key according to the dynamic feature matrix of the cloud computing information data and a topological feature matrix of a cloud computing network;
Transcoding and arranging the cloud computing reference key to obtain a reference key matrix; dividing the reference key matrix to obtain all block matrixes of the reference key matrix; acquiring initial block matrixes in all block matrixes according to dynamic characteristics of cloud computing information data; starting from the initial block matrix, scanning all the block matrixes to obtain a random scanning path sequence of all the block matrixes; quantum walking is carried out at a first position in the random scanning path sequence, and a probability distribution matrix of the reference key matrix is obtained; obtaining a quantum matrix according to the probability distribution matrix and the key parameter; expanding and recombining the quantum matrix to obtain a quantum transformation key;
Encrypting the cloud computing information data according to the quantum transformation key to obtain encrypted data;
And storing the encrypted data.
Further, the method for acquiring the dynamic feature matrix of the cloud computing information data comprises the following steps:
The dynamic feature matrix is obtained according to a dynamic feature matrix calculation formula, wherein the dynamic feature matrix calculation formula is as follows:
; in the/> Representing a dynamic feature matrix of cloud computing information data; /(I)Representing a storage space required by cloud computing information data; /(I)Representing the storage capacity of the data storage area; /(I)Indicating the occurrence of the data storage area/>Probability of the seed data type; /(I)Representing total update time in the cloud computing information data history update record; /(I)Representing the update times of the cloud computing information data in the history update record; /(I)A storage duty ratio representing a storage capacity of the cloud computing information data occupying the data storage area; /(I)Data type diversity representing cloud computing information data; /(I)Representing average update time of cloud computing information data in a history update record; /(I)A rational number indicating that the preset value is not 0.
Further, the method for obtaining the topological feature matrix comprises the following steps:
the topological feature matrix is obtained according to a topological feature matrix calculation formula, and the method for obtaining the topological feature matrix calculation formula comprises the following steps:
; in the/> A topology feature matrix representing a cloud computing network topology; /(I)Representing a total number of nodes in the cloud computing network topology; /(I)Representing an average path length of the cloud computing network topology; representing the degree of a cloud computing network topology; /(I) And representing the number of nodes contained in the maximum connected component in the cloud computing network topology.
Further, the method for acquiring the maximum connected component includes:
In a cloud computing network topological structure, a center node is taken as a center point to be expanded outwards, and a shortest path between the center node and each other node is obtained; traversing the shortest paths to obtain the longest radiation paths among the shortest paths;
and selecting the connected component with the largest intersection with the longest radiation path in the cloud computing network topology structure as the largest connected component in the cloud computing network topology structure.
Further, the method for acquiring the key parameter comprises the following steps:
And taking the product of the dynamic feature matrix of the cloud computing information data and the topological feature matrix of the cloud computing network as a key parameter of a cloud computing reference key.
Further, the method for acquiring the initial block matrix comprises the following steps:
Taking the number of the block matrixes of each row after the block matrix division of the reference key matrix as the number of the row matrixes, and taking the number of the block matrixes of each column after the block matrix division of the reference key matrix as the number of the column matrixes;
the data type diversity of the cloud computing information data is rounded up, the number of the row matrixes is modulo, and the abscissa of the initial block matrix is obtained;
taking the product of the storage duty ratio of the cloud computing information data and the updating time down, and taking the modulus of the number of the column matrixes to obtain the ordinate of the initial block matrix;
forming a first position coordinate of the initial block matrix by the abscissa and the ordinate of the initial block matrix;
and taking the block matrix corresponding to the first position coordinate as an initial block matrix.
Further, the method for acquiring the random scanning path sequence comprises the following steps:
Starting from the initial block matrix, scanning all block matrixes of the reference key matrix by utilizing a rider tour algorithm to obtain the random scanning path sequence; the random scan path sequence includes position coordinates of the block matrix for each scan.
Further, the method for obtaining the probability distribution matrix comprises the following steps:
And starting from the initial block matrix by using an alternate quantum walking rule, performing quantum walking, and obtaining a probability distribution matrix of the reference key matrix.
Further, the method for obtaining the quantum matrix comprises the following steps:
Dividing the probability distribution matrix according to a block matrix division mode of the reference key matrix to obtain all sub-block matrixes in the probability distribution matrix;
obtaining each corresponding sub-block matrix of each position coordinate in the probability distribution matrix in the random scanning path sequence; taking the convolution between each corresponding sub-block matrix and the key parameter as a sub-block quantum matrix of each corresponding sub-block matrix;
and arranging all the sub-block quantum matrixes according to the position coordinates in the random scanning path sequence to obtain the quantum matrixes.
Further, the method for obtaining the quantum transformation key comprises the following steps:
And carrying out ASCII character conversion on all elements in the quantum matrix to obtain the quantum transformation key.
The invention has the following beneficial effects:
The method comprises the steps of obtaining cloud computing information data and a cloud computing reference key which need to be stored in an encrypted mode; because the cloud computing information data has dynamic characteristics, the dynamic characteristics of the cloud computing information data can be characterized by the storage duty ratio of the cloud computing information data, the update time of the cloud computing information data and the data type diversity of the cloud computing information data, the dynamic characteristic matrix of the cloud computing information data is required to be obtained according to the storage duty ratio, the update time and the data type diversity of the cloud computing information data; according to the topological structure characteristics of the cloud computing network, a topological feature matrix of the cloud computing network is obtained, and the structural information of the cloud computing network is reflected; in order to enable the subsequently obtained secret key to have the dynamic characteristics of the cloud computing information data and the topological properties of the cloud computing network at the same time, obtaining a secret key parameter of a cloud computing reference secret key according to the dynamic characteristic matrix of the cloud computing information data and the topological characteristic matrix of the cloud computing network; due to the randomness and inaccuracy principle of quantum computation, in order to improve the randomness of the secret key, a random scanning path sequence of all block matrixes is obtained; obtaining a probability distribution matrix of a reference key matrix; obtaining a quantum matrix according to the probability distribution matrix and the key parameter; encrypting the cloud computing information data according to the quantum transformation key to obtain encrypted data; the encrypted data is stored, and the dynamic key is updated according to the encrypted data. The method combines the dynamic characteristics of the cloud computing information data needing to be stored in an encrypted manner, and generates the unique dynamic key by utilizing the quantum entanglement principle, so that the cloud computing information data needing to be stored in an encrypted manner is less prone to being broken through, and is more suitable for the cloud computing information data which dynamically changes.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for dynamically encrypting and storing information according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description refers to the specific implementation, structure, characteristics and effects of a dynamic encryption storage method for information according to the invention, which is provided by the invention with reference to the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the dynamic encryption storage method for information provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a method for dynamically encrypting and storing information according to an embodiment of the present invention is shown, where the method includes:
And S1, acquiring cloud computing information data and a cloud computing reference key which need to be stored in an encrypted mode.
The embodiment of the invention provides an information dynamic encryption storage method, which is mainly aimed at dynamic encryption storage of cloud computing information data, and needs to acquire the cloud computing information data needing encryption storage. Since the encryption of the cloud computing information data requires key management, in order to obtain a dynamic key of the cloud computing information data adapting to dynamic changes, a cloud computing reference key issued by a cloud computing center needs to be acquired in advance.
Step S2: acquiring a dynamic feature matrix of the cloud computing information data according to the storage duty ratio, the update time and the data type diversity of the cloud computing information data; obtaining a topological feature matrix of the cloud computing network according to the topological structure features of the cloud computing network; and obtaining key parameters of the cloud computing reference key according to the dynamic feature matrix of the cloud computing information data and the topological feature matrix of the cloud computing network.
The cloud computing information data in the cloud computing environment needs to be updated and processed in real time, the cloud computing information data relates to various data types such as structured data, semi-structured data and unstructured data, and the storage proportion of the cloud computing information data may change continuously along with time, the situations reflect that the cloud computing information data has dynamic characteristics, the dynamic characteristics of the cloud computing information data can be represented by the storage proportion of the cloud computing information data, the update time of the cloud computing information data and the data type diversity of the cloud computing information data, and in order to facilitate subsequent convolution operation, a dynamic characteristic matrix of the cloud computing information data needs to be obtained.
Preferably, in one embodiment of the present invention, a method for acquiring a dynamic feature matrix of cloud computing information data includes:
acquiring a dynamic feature matrix according to a dynamic feature matrix calculation formula, wherein the dynamic feature matrix calculation formula is as follows:
In the method, in the process of the invention, Representing a dynamic feature matrix of cloud computing information data; /(I)Representing a storage space required by cloud computing information data; /(I)Representing the storage capacity of the data storage area; /(I)Indicating the occurrence of the data storage area/>Probability of the seed data type; /(I)Representing total update time in the cloud computing information data history update record; /(I)Representing the update times of the cloud computing information data in the history update record; /(I)A storage duty ratio representing a storage capacity of the cloud computing information data occupying the data storage area; data type diversity representing cloud computing information data; /(I) Representing average update time of cloud computing information data in a history update record; /(I)A rational number indicating that the preset value is not 0.
In the dynamic feature matrix calculation formula, the storage space and the storage capacity of a data storage area required by cloud computing information data, and the total update time and the update times in the historical update record of the cloud computing information data can be referred to in an update log of a cloud computing service provider; and the data storage area is presented with the firstThe probability of the seed data type can be consulted through a large database of the cloud computing service provider; in order to make the connection between the storage duty ratio, the average update time and the data type diversity of the cloud computing information data more compact, the self-correlation of the storage duty ratio, the average update time and the data type diversity of the cloud computing information data needs to be introduced, so that the dynamic characteristics of the cloud computing information data are expressed in the form of a main diagonal symmetry matrix.
In one embodiment of the present invention,In other embodiments of the invention,/>, with the value of 1The value of (2) can be set by the practitioner by himself, and is not limited herein.
It should be noted that, in other embodiments of the present invention,、/>And/>The positions of the elements can be adjusted, and the adjusted matrix form is only required to meet the requirement of main diagonal symmetry, and is not limited herein.
In actual situations, the cloud computing system can log in to a cloud service management console according to an account number provided by a cloud computing service provider, network services can be managed in the cloud service management console, a cloud computing network capable of obtaining cloud computing information data in the cloud computing network can be obtained, and connection relations between different components and nodes in the cloud computing network, namely the topology structure of the cloud computing network, can be obtained. Since all nodes in the cloud computing network can be known according to the topology structure of the cloud computing network, and secure communication is needed between the nodes, and the topology structure of the cloud computing network needs to be known for the subsequent acquisition of the dynamic key, in the embodiment of the invention, the topology feature matrix of the cloud computing network is obtained according to the topology structure features of the cloud computing network.
Preferably, in one embodiment of the present invention, the method for obtaining a topology feature matrix includes:
The method for acquiring the topological feature matrix according to the topological feature matrix calculation formula comprises the following steps:
In the method, in the process of the invention, A topology feature matrix representing a cloud computing network topology; /(I)Representing a total number of nodes in the cloud computing network topology; /(I)Representing an average path length of the cloud computing network topology; /(I)Representing the degree of a cloud computing network topology; /(I)And representing the number of nodes contained in the maximum connected component in the cloud computing network topology.
In the topological feature matrix calculation formula, the maximum connected component in the cloud computing network topological structure represents the subgraph with the maximum number of nodes in the cloud computing network topological structure, the overall reliability and stability of the cloud computing network can be known through the maximum connected component in the cloud computing network topological structure, and when a secret key is designed, access control can be carried out according to the communication mode in the maximum connected component, so that the security of the secret key is improved; the degree of the cloud computing network topology represents the number of edges of each node connected with other nodes, the degree of the cloud computing network topology can reflect the load condition of each node, and an attacker may be more prone to supplying the nodes with high connectivity, and the degree of the cloud computing network topology can help to improve the security of the cloud computing network; the average path length of the cloud computing network topology structure can be obtained by averaging all path lengths among all nodes, the average path length can reflect the size of the cloud computing network topology structure, and the longer the average path length is, the larger the cloud computing network topology structure is, and the higher the cloud computing network security is.
Preferably, in one embodiment of the present invention, the method for acquiring the maximum connected component includes:
In a cloud computing network topological structure, taking a central node as a central point to expand outwards, and obtaining the shortest path between the central node and each other node; it is known in the art that other nodes may be included in the shortest path between two nodes; traversing the shortest paths to obtain the longest radiation paths among the shortest paths; the longest radiation path from the central node to other nodes can reflect the maximum radiation range of the central node as far as possible, and the connected component with the longest radiation path intersection is considered as the connected component with larger area and closest to the maximum radiation range of the central node, so that the connected component with the longest radiation path intersection in the cloud computing network topology structure is selected as the maximum connected component in the cloud computing network topology structure.
In one embodiment of the invention, the shortest path between a central node and other nodes in the network topology is calculated by using the Bellman-Ford algorithm. Wherein, the calculation formula of the longest radiation path is as follows:
In the method, in the process of the invention, Representing a Bellman-Ford algorithm; /(I)Representing a central node within a cloud computing network topology; representing the/>, except for a central node, within a cloud computing network topology A plurality of nodes; /(I)Representing the/>, except for a central node, within a cloud computing network topologyA plurality of nodes; /(I)Representing a total number of nodes within the cloud computing network topology; Representing the maximum function.
Preferably, in one embodiment of the present invention, the method for acquiring the key parameter includes:
In order to make the subsequent encryption mode be dynamic encryption, the dynamic change characteristic of the cloud computing information data and the invariance of the original cloud computing network topology structure are combined, so that the product between the dynamic characteristic matrix of the cloud computing information data and the topology characteristic matrix of the cloud computing network is used as a key parameter of a cloud computing reference key. In one embodiment of the invention, the key parameter calculation formula is as follows:
In the method, in the process of the invention, Representing a key parameter; /(I)Representing a dynamic feature matrix of cloud computing information data; /(I)Representing a topological feature matrix of the cloud computing network.
Up to this point, the key parameters of the cloud computing reference key are obtained.
Step S3: transcoding and arranging the cloud computing reference keys to obtain a reference key matrix; dividing the reference key matrix to obtain all block matrixes of the reference key matrix; acquiring initial block matrixes in all block matrixes according to dynamic characteristics of cloud computing information data; starting from the initial block matrix, scanning all the block matrixes to obtain a random scanning path sequence of all the block matrixes; quantum walking is carried out at a first position in the random scanning path sequence, and a probability distribution matrix of a reference key matrix is obtained; obtaining a quantum matrix according to the probability distribution matrix and the key parameter; and expanding and recombining the quantum matrix to obtain the quantum transformation key.
The transformation relation between each row and each column of the matrix obtained after the completion of the convolution operation adopted in the traditional key obtaining method is obvious, has certain regularity, and can easily obtain the original cloud computing information data content through rule analysis and cracking, and the quantum computation has randomness and inaccuracy principle, so that in order to improve the randomness of the key, the random scanning path sequence of all the block matrixes is obtained in the embodiment of the invention; obtaining a probability distribution matrix of a reference key matrix; and obtaining a quantum matrix according to the probability distribution matrix and the key parameter.
In one embodiment of the invention, the issued 128-bit cloud computing reference key is acquired from the cloud computing center, and binary transcoding operation is carried out on the 128-bit cloud computing reference key to obtain a 32×32 reference key matrix for facilitating subsequent analysis. In the subsequent analysis, the content of the reference key matrix was referred to, and the form of the reference key matrix was 32×32. Other forms of reference key matrices may be used in other embodiments of the invention, and are not limited in this regard.
In one embodiment of the invention, the reference key matrix is equally divided into 64 block matrices, each block matrix having a size of 4 x 4. It should be noted that, in other embodiments of the present invention, other types of block matrices may be divided, and only each block matrix is needed, which is not limited herein.
The position of the initial block matrix is related to the dynamic characteristics of the cloud computing information data, and different initial block matrices exist for the cloud computing information data with different dynamic characteristics, so that different random scanning path sequences are obtained, and the uniqueness of the secret key can be ensured.
Preferably, in one embodiment of the present invention, the method for acquiring an initial block matrix includes:
Taking the number of the block matrixes of each row after the block matrix division of the reference key matrix as the number of the row matrixes, and taking the number of the block matrixes of each column after the block matrix division of the reference key matrix as the number of the column matrixes; the data type diversity of the cloud computing information data is rounded up, the number of the row matrixes is modulo, and the abscissa of the initial block matrix is obtained; taking the product of the storage duty ratio of the cloud computing information data and the updating time down, and taking the modulus of the number of the column matrixes to obtain the ordinate of the initial block matrix; forming a first position coordinate of the initial block matrix by the abscissa and the ordinate of the initial block matrix; taking the block matrix corresponding to the first position coordinate as an initial block matrix; after the cloud computing information data is updated, a new initial block matrix can be found by utilizing the dynamic characteristics of the updated cloud computing information data, and then a new rider tour route is obtained, so that a new random scanning path sequence is obtained, and the uniqueness of the secret key can be ensured. In one embodiment of the present invention, the first position coordinate calculation formula is as follows:
In the method, in the process of the invention, A first position coordinate representing an initial block matrix; /(I)Indicating the occurrence of the data storage area/>Probability of the seed data type; /(I)Representing a storage space required by cloud computing information data; /(I)Representing the storage capacity of the data storage area; /(I)A storage duty ratio representing a storage capacity of the cloud computing information data occupying the data storage area; /(I)Data type diversity representing cloud computing information data; /(I)Representing average update time of cloud computing information data in a history update record; /(I)Representing a modulo function; /(I)Representing an upward rounding function; /(I)Representing a downward rounding function.
In the first position coordinate calculation formula, since the dynamic characteristics of the cloud computing information data are updated after each update, at this timeAnd/>The cloud computing information data can be changed, namely different first position coordinates can be generated when the cloud computing information data are updated each time, the first position coordinates are different, the initial block matrix of the basic key matrix is different after the cloud computing information data are updated, and at the moment, the cruising routes of the knight are different, so that different random scanning path sequences are obtained, and the uniqueness of the key is ensured; since the reference key matrix is in the form of 32×32 and each block matrix has a size of 4×4, the number of block matrices per row and column of the reference key matrix is 8, so will/>And/>Taking the mould of 8 respectively; to avoid the occurrence of a value of 0 on the abscissa in the first position coordinates, thus yielding an invalid first position coordinate, will/>And/>Each added with a value of 1.
Preferably, in one embodiment of the present invention, the method for acquiring the random scan path sequence includes:
because the rider tour algorithm has unique dynamic disorder characteristics, based on the path convolution operation of the rider tour algorithm, the jump path is unique and irregular, and the line-row related items caused by convolution under the normal convolution rule can be effectively avoided, so that all block matrixes of the reference key matrix are scanned by adopting the rider tour algorithm, and all block matrixes of the reference key matrix are scanned by utilizing the rider tour algorithm from the initial block matrix to obtain a random scanning path sequence; the random scan path sequence contains the position coordinates of the block matrix for each scan. In one embodiment of the present invention, a specific step of acquiring a random scan path sequence by using a rider tour algorithm is provided, including the steps of:
Starting from an initial matrix block with a position coordinate A, performing traversing recursion scanning on the block matrix according to the behavior rule of horses in chess, trying each possible movement, and then continuing recursion scanning the next position; meanwhile, in the recursive process, the validity of each step of scanning needs to be checked to ensure that the boundary of the block matrix is not exceeded and the scanned new block matrix is not accessed, and once the next step of scanning is not performed and all block scanning is not completed, backtracking needs to be performed to try other possible moving methods until a scanning path for completing all block scanning is found, and the position coordinates of the block matrix scanned each time in the scanning path are used as each element of a random scanning path sequence.
In order to improve the randomness of the key, a corresponding quantum matrix of the reference key matrix needs to be obtained, and a probability distribution matrix of the reference key matrix is obtained first. Preferably, in one embodiment of the present invention, the method for obtaining a probability distribution matrix includes:
And starting from the initial block matrix by using an alternate quantum walking rule, performing quantum walking, and obtaining a probability distribution matrix of the reference key matrix.
It should be noted that, the alternate quantum walking rule and quantum walking are all technical means well known to those skilled in the art, and are not described herein.
Preferably, in one embodiment of the present invention, the method for obtaining a quantum matrix includes:
Dividing the probability distribution matrix according to a block matrix division mode of the reference key matrix to obtain all sub-block matrixes in the probability distribution matrix; obtaining each corresponding sub-block matrix of each position coordinate in the probability distribution matrix in the random scanning path sequence; taking the convolution between each corresponding sub-block matrix and the key parameter as a sub-block quantum matrix of each corresponding sub-block matrix; arranging all sub-block quantum matrixes according to position coordinates in a random scanning path sequence to obtain a quantum matrix; since the quantum matrix is obtained by arranging the position coordinates in a random scanning path sequence, the quantum matrix is a 32×32 matrix here. In one embodiment of the present invention, the calculation formula of the sub-block quantum matrix is as follows:
In the method, in the process of the invention, Represents the/>, of each sub-block matrix in the probability distribution matrixA sub-block quantum matrix; /(I)Representing a key parameter; /(I)Representing the/>, within a random scan path sequencePosition coordinates; /(I)Representing the/>, within a random scan path sequenceA corresponding sub-block matrix of the position coordinates in the probability distribution matrix; /(I)Representing the convolved symbols.
In a calculation formula of the quantum matrix, each sub-block matrix in the probability distribution matrix is convolved by utilizing the key parameter, so that the sub-block quantum matrix combines the dynamic characteristics of the key parameter, and the finally obtained quantum matrix has stronger randomness and non-analyzability.
After the quantum matrix is obtained, the quantum matrix needs to be unfolded and recombined, and finally the quantum transformation key is obtained. Preferably, in one embodiment of the present invention, the method for obtaining the quantum transformation key includes:
And carrying out ASCII character conversion on all elements in the quantum matrix to obtain the quantum transformation key. In one embodiment of the present invention, the quantum matrix is numbered from the first element in the first row, and at this time, the quantum transformation key calculation formula is as follows:
In the method, in the process of the invention, Representing a quantum transformation key; /(I)Representing a character conversion function; /(I)Representing the/>, of each row of elements within the quantum matrixA sequence number of the individual element; /(I)Representing the/>, of each row of elements within the quantum matrixData values of the individual elements.
In the quantum transformation key calculation formula, each 8-bit element in the quantum matrix is used as a data set, and corresponding characters of each data set are calculated, so that a quantum transformation key is finally obtained, and the quantum transformation key has 128 bits in total.
To this end, a quantum transformation key is obtained.
Step S4: and encrypting the cloud computing information data according to the quantum transformation key to obtain encrypted data.
In one embodiment of the invention, the cloud computing information data is encrypted by using an AES encryption algorithm by using a quantum transformation key to obtain encrypted data. The following provides a specific step of encrypting cloud computing information data by using an AES encryption algorithm by using a quantum transformation key, comprising the following steps:
key expansion: an extended key table is first generated from the quantum transformation key. This process involves using a key scheduling algorithm to extend the initial key to a series of round keys for use in encryption of subsequent rounds.
Initial round key encryption: the plaintext and the initial round key are subjected to a bitwise exclusive or (XOR) operation. This operation introduces the effect of the key, making the combination of plaintext and the key more complex.
Multiple rounds of encryption: the following steps are repeatedly performed:
a) Byte substitution transform: each byte of plaintext is replaced by a predefined value, replaced by an S-box.
B) Line shift conversion: the left shift operation is cycled for each row to increase the confusion.
C) Column confusion transformation: the confusion of the algorithm is enhanced by performing linear transformation on each column.
D) Round key addition: and performing bit-wise exclusive OR operation on the round key of the current round and the transformed data.
Final wheel: the last round has no column confusion transformation operation and only contains byte substitution, row shifting and round key addition operations.
Outputting ciphertext: after multiple rounds of encryption, the final ciphertext, i.e., encrypted data, is obtained.
It should be noted that, in other embodiments of the present invention, data encryption algorithms such as DES and 3DES may be further used to encrypt the cloud computing information data, where the data encryption algorithms are well known to those skilled in the art, and are not limited and described herein.
So far, the encrypted data corresponding to the quantum transformation key is obtained.
Step S5: the encrypted data is stored.
In one embodiment of the invention, after the encrypted data is obtained, the encrypted data is stored in a database corresponding to the cloud computing network, and a quantum change key is distributed to related personnel through access setting of the database. When the encrypted data in the database changes, namely the cloud computing information data changes, the key parameters also change correspondingly, the quantum transformation key is updated accordingly, and the data security is ensured through the uniqueness of the quantum transformation key.
Thus, the storage of the encrypted data and the updating of the dynamic key are completed.
In summary, the invention acquires cloud computing information data and a cloud computing reference key which need to be stored in an encrypted manner; because the cloud computing information data has dynamic characteristics, the dynamic characteristics of the cloud computing information data can be characterized by the storage duty ratio of the cloud computing information data, the update time of the cloud computing information data and the data type diversity of the cloud computing information data, the dynamic characteristic matrix of the cloud computing information data is required to be obtained according to the storage duty ratio, the update time and the data type diversity of the cloud computing information data; according to the topological structure characteristics of the cloud computing network, a topological feature matrix of the cloud computing network is obtained, and the structural information of the cloud computing network is reflected; in order to enable the subsequently obtained secret key to have the dynamic characteristics of the cloud computing information data and the topological properties of the cloud computing network at the same time, obtaining a secret key parameter of a cloud computing reference secret key according to the dynamic characteristic matrix of the cloud computing information data and the topological characteristic matrix of the cloud computing network; due to the randomness and inaccuracy principle of quantum computation, in order to improve the randomness of the secret key, a random scanning path sequence of all block matrixes is obtained; obtaining a probability distribution matrix of a reference key matrix; obtaining a quantum matrix according to the probability distribution matrix and the key parameter; encrypting the cloud computing information data according to the quantum transformation key to obtain encrypted data; the encrypted data is stored, and the dynamic key is updated according to the encrypted data. The method combines the dynamic characteristics of the cloud computing information data needing to be stored in an encrypted manner, and generates the unique dynamic key by utilizing the quantum entanglement principle, so that the cloud computing information data needing to be stored in an encrypted manner is less prone to being broken through, and is more suitable for the cloud computing information data which dynamically changes.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (9)
1. A method for dynamically encrypting and storing information, the method comprising:
acquiring cloud computing information data and a cloud computing reference key which need to be stored in an encrypted mode;
acquiring a dynamic feature matrix of the cloud computing information data according to the storage duty ratio, the update time and the data type diversity of the cloud computing information data; obtaining a topological feature matrix of the cloud computing network according to the topological structure features of the cloud computing network; obtaining key parameters of the cloud computing reference key according to the dynamic feature matrix of the cloud computing information data and a topological feature matrix of a cloud computing network;
Transcoding and arranging the cloud computing reference key to obtain a reference key matrix; dividing the reference key matrix to obtain all block matrixes of the reference key matrix; acquiring initial block matrixes in all block matrixes according to dynamic characteristics of cloud computing information data; starting from the initial block matrix, scanning all the block matrixes to obtain a random scanning path sequence of all the block matrixes; quantum walking is carried out at a first position in the random scanning path sequence, and a probability distribution matrix of the reference key matrix is obtained; obtaining a quantum matrix according to the probability distribution matrix and the key parameter; expanding and recombining the quantum matrix to obtain a quantum transformation key;
Encrypting the cloud computing information data according to the quantum transformation key to obtain encrypted data;
Storing the encrypted data;
the method for acquiring the dynamic feature matrix of the cloud computing information data comprises the following steps:
The dynamic feature matrix is obtained according to a dynamic feature matrix calculation formula, wherein the dynamic feature matrix calculation formula is as follows:
; in the/> Representing a dynamic feature matrix of cloud computing information data; /(I)Representing a storage space required by cloud computing information data; /(I)Representing the storage capacity of the data storage area; /(I)Indicating the occurrence of the data storage area/>Probability of the seed data type; /(I)Representing total update time in the cloud computing information data history update record; /(I)Representing the update times of the cloud computing information data in the history update record; /(I)A storage duty ratio representing a storage capacity of the cloud computing information data occupying the data storage area; /(I)Data type diversity representing cloud computing information data; /(I)Representing average update time of cloud computing information data in a history update record; /(I)A rational number indicating that the preset value is not 0.
2. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the topological feature matrix comprises the following steps:
the topological feature matrix is obtained according to a topological feature matrix calculation formula, and the method for obtaining the topological feature matrix calculation formula comprises the following steps:
; in the/> A topology feature matrix representing a cloud computing network topology; /(I)Representing a total number of nodes in the cloud computing network topology; /(I)Representing an average path length of the cloud computing network topology; /(I)Representing the degree of a cloud computing network topology; /(I)And representing the number of nodes contained in the maximum connected component in the cloud computing network topology.
3. The method for dynamically encrypting and storing information according to claim 2, wherein the method for acquiring the maximum connected component comprises the steps of:
In a cloud computing network topological structure, a center node is taken as a center point to be expanded outwards, and a shortest path between the center node and each other node is obtained; traversing the shortest paths to obtain the longest radiation paths among the shortest paths;
and selecting the connected component with the largest intersection with the longest radiation path in the cloud computing network topology structure as the largest connected component in the cloud computing network topology structure.
4. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the key parameter comprises the steps of:
And taking the product of the dynamic feature matrix of the cloud computing information data and the topological feature matrix of the cloud computing network as a key parameter of a cloud computing reference key.
5. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the initial block matrix comprises the steps of:
Taking the number of the block matrixes of each row after the block matrix division of the reference key matrix as the number of the row matrixes, and taking the number of the block matrixes of each column after the block matrix division of the reference key matrix as the number of the column matrixes;
the data type diversity of the cloud computing information data is rounded up, the number of the row matrixes is modulo, and the abscissa of the initial block matrix is obtained;
taking the product of the storage duty ratio of the cloud computing information data and the updating time down, and taking the modulus of the number of the column matrixes to obtain the ordinate of the initial block matrix;
forming a first position coordinate of the initial block matrix by the abscissa and the ordinate of the initial block matrix;
and taking the block matrix corresponding to the first position coordinate as an initial block matrix.
6. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the random scan path sequence comprises the steps of:
Starting from the initial block matrix, scanning all block matrixes of the reference key matrix by utilizing a rider tour algorithm to obtain the random scanning path sequence; the random scan path sequence includes position coordinates of the block matrix for each scan.
7. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the probability distribution matrix comprises the steps of:
And starting from the initial block matrix by using an alternate quantum walking rule, performing quantum walking, and obtaining a probability distribution matrix of the reference key matrix.
8. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the quantum matrix comprises the steps of:
Dividing the probability distribution matrix according to a block matrix division mode of the reference key matrix to obtain all sub-block matrixes in the probability distribution matrix;
obtaining each corresponding sub-block matrix of each position coordinate in the probability distribution matrix in the random scanning path sequence; taking the convolution between each corresponding sub-block matrix and the key parameter as a sub-block quantum matrix of each corresponding sub-block matrix;
and arranging all the sub-block quantum matrixes according to the position coordinates in the random scanning path sequence to obtain the quantum matrixes.
9. The method for dynamically encrypting and storing information according to claim 1, wherein the method for acquiring the quantum transformation key comprises the steps of:
And carrying out ASCII character conversion on all elements in the quantum matrix to obtain the quantum transformation key.
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