CN113901159A - A Local Encryption and Decryption Method for Vector Data Network Transmission Based on Multilevel Spatial Index - Google Patents
A Local Encryption and Decryption Method for Vector Data Network Transmission Based on Multilevel Spatial Index Download PDFInfo
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Abstract
The embodiment of the disclosure provides a vector data network transmission local encryption and decryption method based on multi-level spatial index, which belongs to the technical field of data processing, and specifically comprises the following steps: acquiring element positions and attribute information of the vector geographic data according to the types of the vector geographic data, constructing an R-tree index by using a minimum circumscribed rectangle, and generating an element set; generating an initial parameter value, and calculating a bifurcation parameter and a key character string; calculating parameter values, encrypting a cosine transform result of the point coordinate set and chaotically and randomly scrambling an encryption result; according to the query instruction, local area searching is carried out in the R-tree index, and the searched leaf node element set is defined as a target set; and converting the secret key character string into a numerical value, calculating a parameter value, performing chaotic random inverse scrambling, and substituting the cosine inverse transform of an inverse scrambled result into a decryption formula to obtain a decryption result. By the scheme, the transmission efficiency, the security and the adaptability of the vector data in the network transmission process are improved.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of data processing, in particular to a vector data network transmission local encryption and decryption method based on multistage spatial indexes.
Background
At present, space vector geographic data serving as a core data type in the field of geographic information mapping of modern times has a wide application range in production and life, and how to safely store and transmit the vector geographic data becomes a problem to be solved urgently in the field of geographic information mapping. Most of the existing vector geographic data encryption technologies only consider the security of overall encryption, and often have the defects of large data transmission quantity, lack of flexibility, insufficient utilization of the spatial position relation and the multi-level spatial index structure of entities in vector data and incapability of local information encryption. After the whole encryption, the user needs to receive the whole data and perform the whole decryption to obtain the required local spatial information, which causes a large amount of unnecessary data transmission and encryption and decryption calculation burdens, resulting in low whole transmission efficiency.
Therefore, a safe, efficient and strong-adaptability vector data network transmission local encryption and decryption method based on multi-level spatial index is needed.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide a vector data network transmission local encryption and decryption method based on multi-level spatial index, which at least partially solves the problems of poor security, transmission efficiency, and adaptability in the prior art.
The embodiment of the disclosure provides a vector data network transmission local encryption and decryption method based on multistage spatial indexes, which comprises the following steps:
acquiring element positions and attribute information of vector geographic data according to the types of the vector geographic data, constructing an R-tree index of the vector geographic data by using a minimum circumscribed rectangle, and generating an element set by using all leaf nodes of the R-tree index;
generating an initial parameter value according to the outline coordinate of the minimum circumscribed rectangle of each leaf node, and calculating a bifurcation parameter and a key character string according to the initial parameter value;
converting the secret key character string into a numerical value, calculating a parameter value of a Logi st i cs chaotic function, substituting a cosine transform result of a point coordinate set of the element set into an encryption formula for encryption, and performing chaotic random scrambling on an encryption result;
according to the received query instruction, local area searching is carried out in the R-tree index, and the searched leaf node element set is defined as a target set;
and after converting the secret key character string corresponding to each leaf node in the target set into a numerical value, calculating a parameter value of the Logi st i cs chaotic function, performing chaotic random reverse scrambling on the encrypted result, and substituting the cosine reverse transformation of the reverse scrambled result into a decryption formula to obtain a decryption result.
According to a specific implementation manner of the embodiment of the present disclosure, the vector geographic data includes a point element, a line element, and a surface element, and the step of obtaining the element position and attribute information of the vector geographic data according to the type of the vector geographic data, constructing an R tree index of the vector geographic data by using a minimum circumscribed rectangle, and generating an element set by using all leaf nodes of the R tree index includes:
acquiring attribute information and coordinate data of each point element, and acquiring an upper left corner coordinate and a lower right corner coordinate of a minimum circumscribed rectangle corresponding to each line element and each surface element;
traversing all the point elements, the line elements and the surface elements to obtain a space coordinate set corresponding to the vector geographic data, wherein the space coordinate set comprises a point coordinate set corresponding to all the point elements and a minimum circumscribed rectangle coordinate set corresponding to the line elements and the surface elements;
constructing a hash table to respectively store the single element coordinate and the attribute value of each element;
initializing and constructing an R-tree structure and setting the maximum value of the node capacity of the R-tree structure;
inputting the space coordinate set into the R-tree structure, constructing the R-tree index, inserting entries and recording the number of leaf nodes;
searching corresponding elements in the hash table according to the entries in the leaf nodes;
and traversing all the leaf nodes to generate the element set.
According to a specific implementation manner of the embodiment of the present disclosure, the step of generating an initial parameter value according to the outline coordinate of the minimum circumscribed rectangle of each leaf node, and calculating a forking parameter and a key character string using the initial parameter value includes:
calculating the length and height of each leaf node according to the contour coordinate of the minimum bounding rectangle of the leaf node;
calculating an initial parameter value of each leaf node according to the length and the height;
and calculating the bifurcation parameter and the key character string according to the initial parameter value.
According to a specific implementation manner of the embodiment of the present disclosure, the step of calculating a parameter value of a logistic chaotic function after converting the key character string into a numerical value, substituting a cosine transform result of a point coordinate set of the element set into an encryption formula for encryption, and performing chaotic random scrambling on an encryption result includes:
in the sequence of each leaf node, obtaining the ASCII code of the corresponding secret key character string, converting the secret key character string into a binary numerical value, and then converting the binary numerical value into a decimal numerical value;
calculating an initial state value and iteration times of the Logitics chaotic function according to the decimal value;
calculating an updated state value of the Logitics chaotic function according to the bifurcation parameter, the initial state value and the iteration times;
performing iterative computation on the point coordinate set according to the updated state value, the bifurcation parameter and the iteration times to obtain a first transformation parameter set;
respectively carrying out discrete cosine transform operation on two columns in the first transform parameter set to obtain a calculation result sequence;
respectively substituting the integer part and the decimal part in the calculation result sequence into the encryption formula for encryption, and recombining the encrypted integer part and the encrypted decimal part to obtain the encryption result;
and generating random scrambling coefficients with corresponding lengths by using logical chaotic mapping, performing chaotic scrambling on the encryption result, and symmetrically encrypting and uniformly storing other attributes of the leaf nodes.
According to a specific implementation manner of the embodiment of the present disclosure, the step of performing local area search in the R x tree index according to the received query instruction, and defining the searched leaf node element set as a target set includes:
setting the area range corresponding to the query instruction as a rectangle, and generating a coordinate sequence according to the area range;
searching the coordinate sequence for the intersection region of different rectangles through the R-tree index;
and taking the leaf nodes in the intersection area as a set, traversing the corresponding space coordinates, inserting marks as header information of the divided and inserted attributes, storing the header information as the target set through serialization operation, and calculating the hash value of the target set.
According to a specific implementation manner of the embodiment of the present disclosure, the step of calculating a parameter value of the logistic chaotic function after converting a secret key character string corresponding to each leaf node in the target set into a numerical value, performing chaotic random inverse scrambling on the encrypted result, and substituting an inverse cosine transform of the inverse scrambled result into a decryption formula to obtain a decrypted result includes:
segmenting the target set according to the marks to obtain a coordinate sequence set to be decrypted and header information;
generating a random scrambling coefficient with the same length as the coordinate sequence set to be decrypted by using logical chaotic mapping to perform reverse chaotic scrambling to obtain a coordinate set of a point to be decrypted;
acquiring ASCII (American standard code for information interchange) codes of secret key character strings corresponding to each sequence in the coordinate sequence set to be decrypted, converting the secret key character strings into binary values, and converting the binary values into decimal values;
calculating a bifurcation parameter, a first state value and iteration times of the Logitics chaotic function according to a decimal value corresponding to the coordinate sequence set to be decrypted;
calculating a second state value of the Logitics chaotic function according to the bifurcation parameter, the first state value and the iteration times corresponding to the coordinate sequence set to be decrypted;
performing iterative computation on the coordinate set of the point to be decrypted according to a second state value, a bifurcation parameter and iteration times corresponding to the coordinate sequence set to be decrypted to obtain a second transformation parameter set;
performing inverse discrete cosine transform operation on the two columns in the second transform parameter set respectively to obtain a decryption result sequence;
and respectively substituting the integer part and the decimal part in the decryption result sequence into the decryption formula for decryption, recombining the decrypted integer part and the decrypted decimal part, and decrypting the attribute on the corresponding leaf node to obtain the decryption result.
The scheme for local encryption and decryption of vector data network transmission based on multi-level spatial index in the embodiment of the disclosure comprises the following steps: acquiring element positions and attribute information of vector geographic data according to the types of the vector geographic data, constructing an R-tree index of the vector geographic data by using a minimum circumscribed rectangle, and generating an element set by using all leaf nodes of the R-tree index; generating an initial parameter value according to the outline coordinate of the minimum circumscribed rectangle of each leaf node, and calculating a bifurcation parameter and a key character string according to the initial parameter value; converting the secret key character string into a numerical value, calculating a parameter value of a Logitics chaotic function, substituting a cosine transform result of a point coordinate set of the element set into an encryption formula for encryption, and performing chaotic random scrambling on an encryption result; according to the received query instruction, local area searching is carried out in the R-tree index, and the searched leaf node element set is defined as a target set; and converting a secret key character string corresponding to each leaf node in the target set into a numerical value, calculating a parameter value of the Logitics chaotic function, performing chaotic random reverse scrambling on the encrypted result, and substituting the cosine reverse transformation of the reverse scrambled result into a decryption formula to obtain a decryption result.
The beneficial effects of the embodiment of the disclosure are: by the scheme, the geographic space vector data encryption method of the multilevel spatial index technology is constructed, the spatial position relation of entities in the vector data and the multilevel spatial index structure are fully utilized, local information encryption and decryption are carried out, and the transmission efficiency, the safety and the adaptability of the vector data in the network transmission process are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a local encryption and decryption method for vector data network transmission based on multi-level spatial indexes according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of road network data provided in an embodiment of the present disclosure;
fig. 3 is a schematic diagram illustrating a construction result of an R-tree index according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram of an overall encryption result provided by the embodiment of the present disclosure;
fig. 5 is a schematic diagram of an index area search result provided in an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a partial decryption result according to an embodiment of the disclosure.
Detailed Description
The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
The embodiments of the present disclosure are described below with specific examples, and other advantages and effects of the present disclosure will be readily apparent to those skilled in the art from the disclosure in the specification. It is to be understood that the described embodiments are merely illustrative of some, and not restrictive, of the embodiments of the disclosure. The disclosure may be embodied or carried out in various other specific embodiments, and various modifications and changes may be made in the details within the description without departing from the spirit of the disclosure. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present disclosure, and the drawings only show the components related to the present disclosure rather than the number, shape and size of the components in actual implementation, and the type, amount and ratio of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
At present, space vector geographic data serving as a core data type in the field of geographic information mapping of modern times has a wide application range in production and life, and how to safely store and transmit the vector geographic data becomes a problem to be solved urgently in the field of geographic information mapping. Most of the existing vector geographic data encryption technologies only consider the security of overall encryption, and often have the defects of large data transmission quantity, lack of flexibility, insufficient utilization of the spatial position relation and the multi-level spatial index structure of entities in vector data and incapability of local information encryption. After the whole encryption, the user needs to receive the whole data and perform the whole decryption to obtain the required local spatial information, which causes a large amount of unnecessary data transmission and encryption and decryption calculation burdens, resulting in low whole transmission efficiency.
The embodiment of the disclosure provides a vector data network transmission local encryption and decryption method based on multi-level spatial index, and the method can be applied to the vector data transmission process of spatial data processing or geographic information security scene.
Referring to fig. 1, a schematic flow chart of a vector data network transmission local encryption and decryption method based on multi-level spatial index according to an embodiment of the present disclosure is shown. As shown in fig. 1, the method mainly comprises the following steps:
s101, acquiring element positions and attribute information of vector geographic data according to the types of the vector geographic data, constructing an R-tree index of the vector geographic data by using a minimum circumscribed rectangle, and generating an element set by using all leaf nodes of the R-tree index;
in specific implementation, considering that the vector geographic data generally includes multiple types of data, such as point data, line data, plane data, and the like, for example, the element position and attribute information may be obtained according to different types of point data, then an R tree index of the vector geographic data is constructed by a minimum circumscribed rectangle of the line data and the plane data, and an element set corresponding to the vector geographic data is generated by all leaf nodes of the R tree index. Of course, other spatial indexing methods, such as a multi-level grid spatial index, a quadtree spatial index, an R-tree index, etc., may be used to generate the element set corresponding to the vector geographic data.
S102, generating an initial parameter value according to the outline coordinate of the minimum circumscribed rectangle of each leaf node, and calculating a bifurcation parameter and a key character string according to the initial parameter value;
in specific implementation, after the element set corresponding to the R tree index is obtained, an initial parameter value may be generated according to the outline coordinate of the minimum circumscribed rectangle of each leaf node, and a bifurcation parameter and a key character string are calculated according to the initial parameter value, so as to facilitate a subsequent data decryption process.
S103, converting the secret key character string into a numerical value, calculating a parameter value of a Logitics chaotic function, substituting a cosine transform result of a point coordinate set of the element set into an encryption formula for encryption, and performing chaotic random scrambling on an encryption result;
in specific implementation, the spatial position relationship of an entity in vector geographic data and a multi-level spatial index structure can be utilized to convert the secret key character string into a numerical value, then a parameter value of a Logitics chaotic function is calculated, a cosine transformation result of a point coordinate set of the element set is substituted into an encryption formula to be encrypted, the encryption result is subjected to chaotic random scrambling, and each leaf node is respectively encrypted.
S104, searching a local region in the R-tree index according to the received query instruction, and defining the searched leaf node element set as a target set;
considering that all the vector geographic data are encrypted, and in the actual use process, the query instruction may only need to query partial vector geographic data, and after receiving the query instruction, a local region search may be performed in the R-tree index according to the query instruction, and the searched leaf node element set is defined as a target set.
S105, converting a secret key character string corresponding to each leaf node in the target set into a numerical value, calculating a parameter value of the Logitics chaotic function, performing chaotic random inverse scrambling on the encrypted result, and substituting the inverse cosine transform of the inverse scrambled result into a decryption formula to obtain a decryption result.
After the target set is obtained, a secret key character string corresponding to each leaf node in the target set can be converted into a numerical value, then a parameter value of the Logitics chaotic function is calculated, chaotic random reverse scrambling is carried out on the encryption result, cosine reverse transformation of the reverse scrambling result is substituted into a decryption formula, and the decryption result is obtained by carrying out reverse decryption on the encrypted data.
In the vector data network transmission local encryption and decryption method based on the multilevel spatial index, by constructing a geographic spatial vector data encryption method based on the multilevel spatial index technology, the spatial position relationship of entities in the vector data and the multilevel spatial index structure are fully utilized to encrypt and decrypt local information, so that the transmission efficiency, the security and the adaptability of the vector data in the network transmission process are improved.
On the basis of the foregoing embodiment, the vector geographic data includes a point element, a line element, and a surface element, and the step S101 acquires element positions and attribute information according to types of the vector geographic data, constructs an R tree index of the vector geographic data with a minimum circumscribed rectangle, and generates an element set with all leaf nodes of the R tree index, including:
acquiring attribute information and coordinate data of each point element, and acquiring an upper left corner coordinate and a lower right corner coordinate of a minimum circumscribed rectangle corresponding to each line element and each surface element;
traversing all the point elements, the line elements and the surface elements to obtain a space coordinate set corresponding to the vector geographic data, wherein the space coordinate set comprises a point coordinate set corresponding to all the point elements and a minimum circumscribed rectangle coordinate set corresponding to the line elements and the surface elements;
constructing a hash table to respectively store the single element coordinate and the attribute value of each element;
initializing and constructing an R-tree structure and setting the maximum value of the node capacity of the R-tree structure;
inputting the space coordinate set into the R-tree structure, constructing the R-tree index, inserting entries and recording the number of leaf nodes;
searching corresponding elements in the hash table according to the entries in the leaf nodes;
and traversing all the leaf nodes to generate the element set.
For example, the embodiment of the present invention is described by using geospatial vector geography line data of a Shapefile of a road network of a certain city in China, the vector data is as shown in fig. 2, the minimum circumscribed rectangle of each line element is obtained, and coordinates of a lower left corner and an upper right corner of the minimum circumscribed rectangle are recorded as (x) coordinatesmin，ymin) And (x)max，ymax) And traversing all the elements to obtain a space position coordinate set of the vector geographic data, and obtaining a coordinate set of the minimum circumscribed rectangle of each element. And constructing a hash table FeatureMap to store the single element coordinate and the attribute Value of each vector element, wherein Key is the coordinate position, and Value is the SimpleFeatureAttribute of each element.
Then, the R-tree structure is initially constructed, and the maximum node capacity of the R-tree structure is set to be 20. Inputting the space position set of vector geographic elements into an R-tree structure, constructing an R-tree index, inserting entries by expanding a minimum cost principle, and recording the number of entries or sub-nodes in a node as Nk when N is the numberkFor > 20, the nodes need to be split, the splitting principle follows the minimum bounding rectangle.
After the R-tree index of the completed vector geographic data is constructed, the corresponding element object is looked up in FeatureMap according to the entry in the leaf node. Traversing all leaf nodes thereof, and constructing an index set FeatureIndex of all elements, wherein the sequence of each leaf node is expressed as a nodeiAnd constructing an R-tree index of a proper amount of geographic data by using all the element objects including the leaf node in the sequence, wherein the result is shown in fig. 3.
Further, in step S102, generating an initial parameter value according to the contour coordinates of the minimum bounding rectangle of each leaf node, and calculating a forking parameter and a key string according to the initial parameter value, includes:
calculating the length and height of each leaf node according to the contour coordinate of the minimum bounding rectangle of the leaf node;
calculating an initial parameter value of each leaf node according to the length and the height;
and calculating the bifurcation parameter and the key character string according to the initial parameter value.
In specific implementation, the minimum external rectangular shape R of each leaf node i is usediOf (2), i.e. RiLower left corner coordinate (x)min，ymin)iWith coordinates (x) in the upper right cornermax，ymax)iAnd calculating RiLength ofiHeight and height ti。
Now with R0For example, Rectangle [ x ]min＝110.2313198，ymin＝19.7305877，xmax＝110.2552547，ymax＝19.753232]And calculating to obtain:
Length0＝xmax0-xmin0＝0.0239349
Heigh t0＝ymax0-ymin0＝0.0226443
calculating the initial parameter value para of the leaf node i0：
para0＝SUM(Length0，Heigh t0)*210＝47.6971008
According to para0Calculating a bifurcation parameter mu of a node0：
μ0＝(para0mod 0.430055)+3.569945＝3.9609958
Let Key2Computing the key string E of a node from para0 ═ encryptTest0：
E0＝SM3([para0/2]+Num(R0))2*Key2)
＝5789e08b08267472621bb126edb09b80e053768129f86052fbe93036f350508b。
On the basis of the foregoing embodiment, in step S103, converting the key character string into a numerical value, calculating a parameter value of a logistic chaotic function, substituting a cosine transform result of a point coordinate set of the element set into an encryption formula to encrypt, and performing chaotic random scrambling on an encryption result, including:
in the sequence of each leaf node, obtaining the ASCII code of the corresponding secret key character string, converting the secret key character string into a binary numerical value, and then converting the binary numerical value into a decimal numerical value;
calculating an initial state value and iteration times of the Logitics chaotic function according to the decimal value;
calculating an updated state value of the Logitics chaotic function according to the bifurcation parameter, the initial state value and the iteration times;
performing iterative computation on the point coordinate set according to the updated state value, the bifurcation parameter and the iteration times to obtain a first transformation parameter set;
respectively carrying out discrete cosine transform operation on two columns in the first transform parameter set to obtain a calculation result sequence;
respectively substituting the integer part and the decimal part in the calculation result sequence into the encryption formula for encryption, and recombining the encrypted integer part and the encrypted decimal part to obtain the encryption result;
and generating random scrambling coefficients with corresponding lengths by using logical chaotic mapping, performing chaotic scrambling on the encryption result, and symmetrically encrypting and uniformly storing other attributes of the leaf nodes.
For example, in the sequence of each leaf node i, a key string E is obtained0The character string is converted into a binary value, and then the binary value is converted into a decimal value BigI0. Next, calculating an initial value of the Iogenetics chaotic function, wherein the required parameters comprise the bifurcation parameter muiThe initial state value x0The number of iterations n, wherein the random number μ is generated in the second part0＝3.9609958，x0And n is calculated by the formula:
n＝(BigIi mod 214)+500＝14934
calculating a chaotic mapping formula for the three values to obtain an updated state value x iterated for n timesn＝0.7994300412699675；
The length of the point coordinate set is denoted as L-71, and then mu is added0，xnAnd L is taken as an initial value of the logic chaotic mapping and is substituted into a formula to carry out iterative computation, and each iterative result is recorded to obtain the first transformation parameter set I0；
For the point coordinate set Px，yRespectively carrying out discrete cosine transform on two rows of coordinate values to obtain a calculation result sequence dctP of the discrete cosine transformx，y. For dctPx，ySubstituting the sequence into the encryption formula for encryption calculation, and recombining the obtained integer part result and the decimal part:
dctPi＝Inti+Deci
and generating a chaotic random scrambling coefficient with a corresponding length by using the logical chaotic mapping to perform chaotic scrambling. Replacing the initial coordinate points with all coordinate points, and making other attributes of the initial points symmetrical through SM4Processed in an encrypted manner, the key being E0The last 16 bytes "e 0537b8129f86052fbe93036f350508 b" of the data are saved as the original data format or saved in a database;
since the leaf nodes are not affected by each other, all the leaf nodes can be encrypted and calculated by adopting a parallel calculation method, and the key parameter of each leaf node is stored, and the encryption result is shown in fig. 4.
On the basis of the foregoing embodiment, in step S104, performing local area search in the R-tree index according to the received query instruction, and defining the searched leaf node element set as a target set, includes:
setting the area range corresponding to the query instruction as a rectangle, and generating a coordinate sequence according to the area range;
searching the coordinate sequence for the intersection region of different rectangles through the R-tree index;
and taking the leaf nodes in the intersection area as a set, traversing the corresponding space coordinates, inserting marks as header information of the divided and inserted attributes, storing the header information as the target set through serialization operation, and calculating the hash value of the target set.
When the local vector data query is carried out in the area selected by the user, the secondary query needs to be used as the query instruction, the area range S to be queried is obtained according to the query instruction, the range S is assumed to be rectangular, the lower left corner coordinates (110.30666, 20.04324) and the upper right corner coordinates (110.35430, 20.08294), and the range coordinate value of the S is generated into a coordinate sequence [110.30666, 20.04324, 110.35430, 20.08294] to be transmitted to the service end of the electronic equipment through the network for processing.
Then, the region range retrieval can be carried out on the coordinate sequence through the R-tree index, and the core method is that the rectangles are judged to be intersected, and a first rectangle is set: (x1, y1), (x2, y2), second rectangle: (x3, y3), (x4, y4), the two rectangles intersect when the following formula is satisfied:
max(x1，x3)＜＝min(x2，x4)&&max(y1，y3)＜＝min(y2，y4)
and then, taking the leaf nodes with overlapped areas as a set, traversing vector geographic space objects contained in the set to obtain a query result, storing the query result into a sequence DeFeture as shown in figure 5, inserting a mark as a partition, and finally inserting header information of the attribute. The sequence is saved as the target set by a serialization method, and the hash value SM3(F) of the sequence is calculated and can be transmitted back to the user through the network.
Further, in step S105, converting a key character string corresponding to each leaf node in the target set into a numerical value, calculating a parameter value of the logistic chaotic function, performing chaotic random inverse scrambling on the encryption result, and substituting the inverse cosine transform of the inverse scrambled result into a decryption formula to obtain a decryption result, where the method includes:
segmenting the target set according to the marks to obtain a coordinate sequence set to be decrypted and header information;
generating a random scrambling coefficient with the same length as the coordinate sequence set to be decrypted by using logical chaotic mapping to perform reverse chaotic scrambling to obtain a coordinate set of a point to be decrypted;
acquiring ASCII (American standard code for information interchange) codes of secret key character strings corresponding to each sequence in the coordinate sequence set to be decrypted, converting the secret key character strings into binary values, and converting the binary values into decimal values;
calculating a bifurcation parameter, a first state value and iteration times of the Logitics chaotic function according to a decimal value corresponding to the coordinate sequence set to be decrypted;
calculating a second state value of the Logitics chaotic function according to the bifurcation parameter, the first state value and the iteration times corresponding to the coordinate sequence set to be decrypted;
performing iterative computation on the coordinate set of the point to be decrypted according to a second state value, a bifurcation parameter and iteration times corresponding to the coordinate sequence set to be decrypted to obtain a second transformation parameter set;
performing inverse discrete cosine transform operation on the two columns in the second transform parameter set respectively to obtain a decryption result sequence;
and respectively substituting the integer part and the decimal part in the decryption result sequence into the decryption formula for decryption, recombining the decrypted integer part and the decrypted decimal part, and decrypting the attribute on the corresponding leaf node to obtain the decryption result.
For example, after an encrypted target set is obtained, the target set is segmented by a mark to obtain the coordinate sequence set to be decrypted and header information. Generating chaotic random scrambling coefficients with corresponding lengths by using logical chaotic mapping, and performing reverse chaotic scrambling to obtain a coordinate set P of a point to be decryptedx，y；
In each sequence i, a key string E is obtainedjThe character string is converted into a binary value, and then the binary value is converted into a decimal value BigIi. Next, calculating a first state value of the logistic chaotic function, wherein the required parameters comprise a bifurcation parameter muiInitial state value x0Number of iterations n, where μiRandom number, x, generated in the second part0And n is calculated by the formula:
x0＝(BigIi mod 1020)/1020
n＝(BigIimod 214)+500
calculating a chaotic mapping formula for the three values to obtain a second state value x iterated for n timesn：
xn+1＝μixn(1-xn)
The length of the set of coordinate points is recorded as L, and then mu is recordediTaking xn and L as initial values of the logical chaotic mapping to be substituted into a formula for iterative computation, and recording each iteration result to obtain the second transformation parameter set Ii；
Set of coordinate points Px，yPerforming inverse discrete cosine transform on two rows of coordinate values respectively to obtain a calculation result sequence idctP of the inverse discrete cosine transformx，y. For idctPx，yThe sequence is substituted into a formula to carry out encryption calculation, and the obtained integer part result and the decimal are usedPartial recombination:
idctPi＝Inti+Deci
replacing the initial coordinate points with all coordinate points, and processing the attribute of the initial points in an SM4 symmetric decryption mode, wherein the key is EjThe last 16 bytes "e 0537b8129f86052fbe93036f350508 b", the result is written into the original data format file;
traversing all leaf nodes in the target set, and repeating the above steps until all the nodes are decrypted, so as to obtain the decryption result of the vector geographic data as shown in fig. 6.
The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (6)
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