CN108804933B - Method for carrying out scale conversion on big data in information hiding technology - Google Patents
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Abstract
The invention belongs to the technical field of information processing, and discloses a method for carrying out scale conversion on big data in an information hiding technology. Analyzing the influence of the large number system conversion operation on the correlation complexity between the arbitrary system sequence and the vector character digit, obtaining a complete segmentation sequence arranged according to the bit weight by estimating the memory space, obtaining a new system characteristic sequence by utilizing the iterative quotient and the new system numerical value based on a segmentation vertical division algorithm, and effectively performing the large number arbitrary system conversion. The invention solves the problem of vector character bit overflow, breaks the limit of built-in conversion, overcomes the limit of conversion system value and realizes the universality of conversion.
Description
Technical Field
The invention belongs to the technical field of information processing, and relates to a method for carrying out scale conversion on big data in an information hiding technology.
Background
The information hiding technology based on information security is to hide information in an original carrier through a specific method so as to hide the 'existence fact' of the information, and is mainly applied to confidential communication of bank systems, military information departments and the like. Currently, a commonly used information steganography algorithm based on an Expansion Modulation Direction (EMD) needs to convert original secret information into other system sequences required by a method before secret information is embedded, and a steganography algorithm based on diamond coding needs to embed secret information of an arbitrary system into a pixel. Therefore, the realization of the correct and quick conversion of the data system is a precondition guarantee for the implementation of the information steganography method. In the information age of big data nowadays, secret information is different from steganographic carriers and can be as large as PB, EB, ZB, even YB and BB. The currently involved method of binary conversion is classical long division, which can only divide and complement the converted binary value by the whole data (as shown in fig. 1). Due to the limitation of the range of the data value range, the method is only suitable for the situation of few original data bits and cannot meet the requirement of a large data structure based on the information hiding technology, and therefore, a correct and rapid binary conversion method for large data needs to be established.
Most of the binary conversion methods have the problem of limitation of conversion binary, and due to the characteristics of high speed (speed of data generation and use), high variation (range of data types and sources) and high-scale data volume of large data, and the complexity of arbitrary binary conversion between large numbers is included in the correlation among potential variables, the problem that the computational complexity is in nonlinear superposition is brought about, so how to reduce the complexity of arbitrary binary conversion between large numbers needs to be solved urgently.
Disclosure of Invention
The invention aims to provide a segmented vertical long division method for large data scale conversion, which is used for solving the problem of character bit number overflow of large data scale conversion in the prior art.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a segmented vertical long division method for large data system conversion is used for analyzing the influence of large data system conversion operation on the correlation complexity between any system sequence and vector character digit, obtaining a complete segmented sequence arranged according to the bit weight by estimating a memory space, obtaining a new system characteristic sequence by utilizing an iterative quotient and a new system numerical value based on a segmented vertical long division algorithm, and effectively performing large data system conversion.
The invention is characterized in that:
comprising a large number series Xi,j,k: x is an original system sequence (X represents an original system value); i denotes the iteration index (i)>0, I belongs to I, and I is the total iteration number); j denotes a segment number index (j)>0, J ∈ J, J being the total number of segments); k denotes a per-segment sequence number index (k)>0, K ∈ K, K is the total number of bits per segment of the sequence). Y isiRepresenting a new sequence of large numbers (y representing a new value) is the sequence that keeps the last remainder of each iteration dynamically. And the parameters L, S involved in the large-number arbitrary system conversionj、Qi、Rk. Wherein, L represents the total length of the original system sequence, the data length K of each segment and the segmentation number J, which are obtained according to the correlation complexity between the original system sequence and the vector character digit, when the original data can not be completely segmented, the data length t of the last tail segment satisfies t ≦ K. Sj(J ═ 1, …, J) is the quotient sequence for each segment; qi＝[Si,1,…,Si,J]Representing the quotient sequence of each iteration and continuing to operate as a dividend; remainder R corresponding to quotient and last bit weight of last segmenti,j-1Is a pair of related values, when Ri,j-1·xk+Xi,j·x0When y is more than or equal to y, quotient SjHas a value; when the calculated quotient is 0, the operation is ended, the remainder is reserved in a dynamic reverse order, and a new system sequence Y is obtainedi。
The specific technical scheme is as follows:
(1) initial data pre-processing
Generating uniformly distributed pseudo-random integer sequences X by using a random sequence generating function, setting a binary value y to be converted according to requirements, and generating a corresponding characteristic segment sequence set by adopting a self-adaptive vector character bit segmentation method based on the length of an original binary sequence, wherein the bit number K of each segment of the sequence is fixed, and the data length t of the last tail segment satisfies that t is less than or equal to K;
(2) obtaining cyclic iteration data through analog division;
the original data sequence obtained in the step (1) is intercepted according to segment rolling to obtain a corresponding segment characteristic sequence, and a quotient sequence S of each segment is calculated by applying a segmentation bitwise division algorithmj(J is 1, …, J) and the remainder on the corresponding weight, when recording the remainder R corresponding to the last weight of each segmenti,j-1(ii) a R is to bei,j-1Transmitting to the next section of data, using bit weight and new system value y to connect sections and sections to ensure the integrality and correctness when the next section of data operation is carried out, and using formula Ri,j-1·xK+Xi,j·x0-Sj·y＝Ri,jObtaining quotient SjAnd remainder Ri,j；
(3) Dynamically storing iterative operation results
While iteratingStoring the quotient sequence of each segment into the quotient sequence Q of each iteration in a dynamic vector connection modei＝[Si,1,…,Si,J](J represents the total number of segments of the current iteration), constructing a new complete quotient sequence set as a dividend of the next iteration, and processing the dividend in the step (2) which is the same as the original data to obtain the quotient and the remainder of each iteration;
(4) outputting the binary conversion result
The last digit remainder R of the last segment of each iterationi,JDynamically stored in Y sequence until Qi＝[Si,1,…,Si,J]When the value is 0, the conversion is finished, the result is stored, and the remainder in the Y sequence is output in the reverse order, namely the result is obtained; otherwise, the quotient is continuously divided by the binary value y, and the operations of the steps (2) to (4) are repeated.
The invention has the following beneficial effects:
(1) the conversion method of the invention is firstly special for large number system conversion. The current binary conversion method is classical long division, the method can only carry out division and complementation on the conversion binary value by the whole data (as shown in figure 1), and the overflow problem of 'character digit' can occur under the limitation of the range of the data value, so the method is only suitable for the condition of less original data digit. The invention arranges the large number original data according to the sequence of the segments, decomposes the large number division problem which can not be realized by character digit overflow into simple segmented vertical operation by utilizing the segmentation idea, and solves the problem of vector character digit overflow.
(2) The segmented vertical long division method provided by the invention fully utilizes the storage space, adopts a segmented storage mechanism to carry out iterative operation on the original data, reduces the space complexity caused by the superposition operation of large numbers, realizes the arbitrary system conversion of the large numbers, breaks the limit of the built-in conversion, overcomes the limit of the conversion system value, and realizes the universality of the conversion.
Drawings
FIG. 1 is a diagram illustrating the binary conversion of integers with fewer bits of original data.
FIG. 2 is a flow chart of a method for converting a decimal system according to the present invention.
FIG. 3 is a block diagram of the present invention based on the method of converting a large number system.
Detailed Description
The invention provides a big data system conversion method used in information hiding technology, which is implemented on the basis of information hiding technologies such as multidirectional coding technology-modified steganography algorithm, diamond coding-based steganography algorithm and the like, and comprises the following steps, wherein the implementation flow chart of the method is shown in figure 2:
(1) preprocessing initial data;
the method comprises the steps of randomly generating uniformly distributed pseudo-random original data sequences X by utilizing the requirement of large number system conversion, preprocessing the generated random large number sequences, namely obtaining corresponding characteristic segment sequence sets by utilizing the length of X and adopting a self-adaptive vector character string segmentation method. In addition, a new binary value y is defined.
Thus, the original data sequence X, the length L, the total number of segments J and the total number of bits K of each segment can be obtained.
(2) Obtaining cyclic iteration data through analog division;
knowing that the original data of the first iterative operation is X, carrying out K-bit sequential interception on the X, traversing the original binary sequence by segments through an analog division algorithm, and obtaining each segment of quotient sequence Sj(J-1, …, J) and Ri,j(the remainder corresponding to the last bit weight of the ith iteration and the jth segment) and adding Ri,jAnd transmitting the data to the next section of data as a basis for calculating a second section of quotient sequence, and repeating division operation according to sections by using the remainder and new system numerical values x and y in sequence to obtain the quotient sequence of each section and the remainder of the final bit weight.
The formula for the quotient and remainder can be described as:
Ri,j·xK+Xi,j+1·x0-Sj+1·y＝Ri,j+1
(3) obtaining an iterative operation result;
the quotient sequence Q of each iteration is obtained by connecting the dynamic vectors of each quotient sequencei＝[Si,1,…,Si,J]Performing analog division operation as raw data, and storing the last digit remainder of the iteration while dynamically storingRJ(indicating the jth segment, kth bit remainder in the current iteration).
(4) Outputting a system conversion result;
according to the nature of the vertical long division, the end of the operation is indicated when the quotient is 0, i.e. when QiWhen the value is 0, the operation ends. Dynamically storing the remainder corresponding to the last bit weight of the dividend of each iteration into Y when Q is equal toiThe remainder obtained by outputting in reverse order when equal to 0, i.e. Y is equal to [ R ]I,J,RI-1,J,…,R2,J,R1,J](I represents the number of iterations, J represents the total number of segments in the current iteration, and K represents the last bit index of each segment in each iteration).
Example (see fig. 3) of performing binary conversion on more than one hundred bits of data under conversion of binary secret information based on modified multidirectional coding technique into (2n +1) binary sequence (n represents the number of pixels participating in the coding technique, and n is 12 in this example), which is also applicable to embedding one B-ary sequence secret information into a pixel pair in a diamond coding-based steganography algorithm (B is 2 v)2+2v +1, v denotes a pixel change amount, in this case v ═ 3). The method is only applied to the hundred-bit binary sequence, and the effect of the method can be fully explained, but the invention provides a general framework, and besides the example, the method can be applied to any binary conversion of other large data with any length.
An example procedure is as follows:
(1) generating an original sequence X (X is 2, length L is 101, total segment number J is 11, each segment sequence bit number K is 10, and the last segment bit number t is 1, and the user can specify the test length), and obtaining the following result through a random sequence generation function: (X represents the original system sequence, y represents the new system value)
X＝101010111000101110001011100010100001110110100000000110001001000111000100011101010100110110000111110；
y＝25；
And carrying out segmentation interception operation on the original data X of the first iteration according to the condition that K is 10, and obtaining a quotient sequence of each segment according to a segment sequence: s1,1＝[0 0 0 00 11 01 1]，…S1,10＝[1 1 1 0 0 1 1 0 1 0]，S1,11＝[1]And remainder sequence: r1,1＝[1 2 5 10 21 17 10 21 18 11]，…，R1,10＝[20 15 5 10 20 16 8 17 10 21]，R1,11＝[17](ii) a Integration of the quotient sequence to yield Q1＝[S1，S2，…，S9，S10，S11]The integrated quotient sequence Q1As a new dividend, i.e. the original data of the second iteration;
to Q1The pre-0 removal processing is carried out, then the next iteration data is intercepted in a rolling way according to sections, and the obtained next iteration data is respectively [1101101110 ] according to the section sequence]，[0100111110]，[0101110011]，[1110000010]，[0001010010]，[0110100101]，[0010011111]，[0001001110]，[0111111100]，[110101](ii) a Repeating the above process until QIThe conversion is finished when the value is 0, the remainder is obtained, the reverse order is stored in the sequence Y, and Y is obtained when the value is R79,1,R78,1,…,R2,10,R1,11]. The final result is expressed as:
(101010111000101110001011100010100001110110100000000110001001000111000100011101010100110110000111110)2＝(7 11 19 22 13 14 23 23 0 18 9 1 12 16 320 19 23 18 15 15 17)25
examples illustrate that: in the current binary conversion method, the binary character vector is required to be less than 53 bits to ensure that the binary conversion algorithm data does not overflow, if the binary character vector exceeds 53 bits, the binary conversion algorithm data exceeds a built-in type storage range, namely, the binary conversion cannot be performed when the number of the binary vector character bits exceeds 53 bits, so that the embodiment of fig. 2 cannot be realized for the prior art, but the binary conversion can be successfully performed by the invention.
Claims (1)
1. A system conversion method of big data used in information hiding technology is applied to a steganography algorithm based on diamond coding to embed secret information into a pixel pair, and is characterized by comprising the following steps:
(1) initial data pre-processing
Generating uniformly distributed pseudo-random integer sequences X by using a random sequence generating function, defining a new system value y, and generating a corresponding characteristic segment sequence set by adopting a self-adaptive vector character bit segmentation method based on the length of an original system sequence, wherein the bit number K of each segment of the sequence is fixed, and the data length t of the last tail segment meets the condition that t is less than or equal to K;
(2) obtaining cyclic iteration data through analog division;
the original data sequence obtained in the step (1) is intercepted according to segment rolling to obtain a corresponding segment characteristic sequence, and a quotient sequence S of each segment is calculated by applying a segmentation bitwise division algorithmjAnd the remainder on the corresponding bit weight, wherein J is 1, …, J, when the remainder R corresponding to the last bit weight of each segment is recordedi,j-1(ii) a R is to bei,j-1Transmitting to the next section of data, using bit weight and new system value y to connect sections and sections to ensure the integrality and correctness when the next section of data operation is carried out, and using formula Ri,j-1·xK+Xi,j·x0-Sj·y＝Ri,jObtaining a quotient sequence SjThe remainder R corresponding to the ith iteration and the jth section of the last bit weighti,j；
(3) Dynamically storing iterative operation results
Storing the quotient sequence of each segment into the quotient sequence Q of each iteration in a dynamic vector connection mode while performing iterative operationi＝[Si,1,…,Si,J](J represents the total number of segments of the current iteration), constructing a new complete quotient sequence set as a dividend of the next iteration, and processing the dividend in the step (2) which is the same as the original data to obtain the quotient and the remainder of each iteration;
(4) outputting the binary conversion result
The last digit remainder R of the last segment of each iterationi,JDynamically stored in Y sequence until Qi＝[Si,1,…,Si,J]When the value is 0, the conversion is finished, the result is stored, and the remainder in the Y sequence is output in the reverse order, namely the result is obtained; otherwise, the quotient is continuously divided by the binary value y, and the operations of the steps (2) to (4) are repeated.
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