CN107358072B - Vector map digital fingerprint copyright protection method based on I code and CFF code - Google Patents
Vector map digital fingerprint copyright protection method based on I code and CFF code Download PDFInfo
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- CN107358072B CN107358072B CN201710582789.XA CN201710582789A CN107358072B CN 107358072 B CN107358072 B CN 107358072B CN 201710582789 A CN201710582789 A CN 201710582789A CN 107358072 B CN107358072 B CN 107358072B
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/10—Protecting distributed programs or content, e.g. vending or licensing of copyrighted material ; Digital rights management [DRM]
- G06F21/16—Program or content traceability, e.g. by watermarking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/56—Information retrieval; Database structures therefor; File system structures therefor of still image data having vectorial format
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Abstract
Aiming at the problem that piracy tracking is difficult after vector map data are distributed, a vector map data digital fingerprint method based on I codes and CFF codes is provided. Firstly, carrying out block coding by utilizing an I code and a CFF code to establish a fingerprint library, wherein the area code adopts the I code, and the user code adopts the CFF code; and then embedding the fingerprint into a DFT phase coefficient of the vector map data in a quantization mode, and finally obtaining the fingerprint-containing vector map data for distribution. The proposed fingerprint coding scheme not only can effectively resist common collusion attacks, can correctly trace at least one traitor, but also has shorter code length under the condition of larger user capacity; the blind detection of the fingerprint information is realized, and the robustness to various fingerprint attacks is strong. The scheme can provide effective copyright protection for the vector map data and is suitable for distribution of the vector map data.
Description
Technical Field
The invention belongs to the technical field of cartography and geographic information science, and relates to a vector map data digital fingerprint method based on I codes and CFF codes.
Background
The vector map data is used as an important strategic resource of the country and a core content for supporting the development of the geographic information surveying and mapping industry, and the safety of the vector map data is important. The current vector map data is mainly stored in a digital form, which facilitates data copying and distribution and makes illegal piracy of data extremely easy. Currently, reliable technologies are urgently needed to ensure the safety of vector map data.
For vector map data after distribution, two problems of copyright ownership determination and traitor tracing of the data are generally involved. Digital watermarking technology, which is a leading technology developed in recent years in the field of information security, achieves copyright protection by embedding copyright identification information related to a data owner into data, and solves the problem of data copyright ownership determination to some extent, but does not have the traitor tracing problem. Digital fingerprinting technology, which is the main direction of future copyright protection, embeds unique purchaser-related information (fingerprints) in each piece of distributed data, and tracks traitors by extracting data fingerprints and fingerprint information in fingerprint libraries. The digital fingerprint is more consistent with a data distribution scene in reality due to the principle of the digital fingerprint, and is widely applied to the field of copyright protection of multimedia data such as images, audios and videos, but is rarely researched in the field of copyright protection of vector map data.
Disclosure of Invention
Aiming at the situation, the invention provides a vector map data digital fingerprint method based on I code and CFF code, which comprises the steps of firstly utilizing the I code and the CFF code to carry out block coding to establish a fingerprint library, wherein the area code adopts I coding, and the user code adopts CFF coding; and then embedding the fingerprint into a DFT phase coefficient of the vector map data in a quantization mode, and finally obtaining the fingerprint-containing vector map data for distribution. The method can effectively resist common collusion attack, can correctly trace at least one traitor, and has shorter code length under the condition of larger user capacity; the blind detection of the fingerprint information is realized, and the robustness to various fingerprint attacks is strong.
The I code gamma (n, d) is obtained by the compensation of an orthonormal matrix, the parameter n represents the user capacity, d represents the Hamming distance, and the minimum Hamming distance of the code is 2 d. At willcAnWhen the user "and" colludes, the position of 0 in the resulting fingerprint is unique, and the traitor is correctly traced according to the position of 0. When any two users perform or collusion, any one colluding user cannot be correctly tracked. In order to make the I code resist AND collusion and OR collusion attack at the same time, the elements with the lower triangle of 1 in the I code are required to be inverted.
CFF coding is a system (X, F) with N elements, N granules, denoted r-CFF (N, N)). The only condition that the element pairs which are already present in a certain CFF granule, and not in the remaining granules, are satisfied between any r granules belonging to F and any other granule B belonging to F. And (5) inverting the incidence matrix M of the r-CFF according to bits to obtain the CFF code resisting the collusion of r users.
The method comprises the following steps: fingerprint coding construction, fingerprint embedding, extraction and tracking.
The fingerprint coding structure is to perform block coding on an I code and a CFF code, and comprises the following steps: first, a set is selectedVAnd the number of collusion attack resistant peoplerStructure ofBoolean matrix with elements of 1B(ii) a Then, constructing an Nxn CFF code word matrix and an Nxn I code word matrix; finally, the I and CFF codes are extended by 10 and 01 for 1 and 0 to better resist the averaging attack.
Fingerprint embedding refers to embedding fingerprint information into original vector map data to obtain vector map data containing fingerprints. The method comprises the following steps: firstly, reading vector space data, extracting all coordinate points of a graphic object, and constructing a complex sequence; secondly, performing DFT conversion on the sequence, and calculating to obtain a phase coefficient | and an amplitude coefficient; then, scrambling the fingerprint to be embedded by applying a Logistic chaotic algorithm to increase the security of the fingerprint; then, fingerprint information is embedded into the phase coefficient by applying a QIM method; and finally, performing DFT inverse transformation on the phase coefficient of the coordinate point pair embedded with the watermark to obtain the map data containing the fingerprint vector.
The extraction process of the watermark is the inverse of the embedding process. Firstly, reading data to be detected, extracting all coordinate points of a graphic object, and constructing a complex sequence; secondly, performing DFT conversion on the sequence, and calculating to obtain a phase coefficient; then, extracting the value of the fingerprint sequence in the scrambling state by a QIM method; then, performing Logistic reverse scrambling on the extracted sequence; and finally, determining fingerprint information by adopting a voting principle on the fingerprint sequence subjected to Logistic reverse scrambling to obtain a final fingerprint sequence.
The fingerprint tracing is to calculate the hamming distance between the extracted fingerprint sequence and the fingerprints in the fingerprint library, and determine the user corresponding to the fingerprint in the library with the smallest hamming distance with the suspicious fingerprint sequence as an illegal user, thereby tracing traitors.
Drawings
FIG. 1I code gamma (5,1)
FIG. 2 is a diagram of anti-AND collusion and OR collusion I code
FIG. 3 is a diagram of r-CFF encoding
FIG. 4 is a block coding schematic
FIG. 5 is ICFF fingerprint encoding
FIG. 6(a) is the raw data
FIG. 6(b) is a diagram of a fingerprint-containing vector map data
FIG. 7 is a user fingerprint
FIG. 8(a) shows data of a and b user collusions
FIG. 8(b) shows data of c and d user collusions
FIG. 8(c) shows data of e and f user collusion
TABLE 1 ability to resist single user attacks
Table 2 shows a scheme for resisting 2-user attack
TABLE 3 ability to resist attack by 2 users
。
Detailed Description
In order to explain technical contents, structural features, objects to be achieved, and effects to be achieved of the present invention in detail, the following detailed description is given with reference to the embodiments.
The implementation steps of the invention can be summarized into three parts: fingerprint library construction, fingerprint information embedding and fingerprint information extraction and traitor tracing, the implementation steps are further described below.
The fingerprint database is constructed by block coding of an I code and a CFF code, and the specific implementation steps are as follows:
(1) selecting a set V and a collusion attack resistant number r, and constructing a Boolean matrix B with n multiplied by n elements of 1;
(2) an N × N CFF codeword matrix is constructed. Taking the set V = {1,2,3,4,5,6,7,8,9,10,11,12} as an example, a 2-CFF (12,16) codeword matrix can be constructed, and the specific steps are as follows:
(a) constructing a Boolean matrix B with n multiplied by n elements of 1;
(b) in the sets { (1, ⋯, r +1), (r +2, ⋯,2r +2), ⋯, (n-r, ⋯, n) } and { (1, n ⁄ (r +1) +1, ⋯, (r × n) ⁄ (r +1) +1), (2, n ⁄ (r + C)
1) A union of +2, ⋯, (r × n) ⁄ (r +1) +2), ⋯, (n ⁄ (r +1),2n ⁄ (r +1), ⋯, n) } as a CFF basis set G, values of corresponding pairs of elements in B are modified, and G constructed with V as an element set is (1,2,3), (4,5,6), (7,8,9), (10,11,12), (1,5,9), (2,6,10), (3,7,11), (4,8, 12);
(c) taking G as an initial value, carrying out 3-order full arrangement on 12 elements in V, traversing all the block groups, judging whether a corresponding value in an element pair B of a certain block group is 0, and if 0 indicates that the element pair appears, discarding the block group; if the value is 1, this block is retained, and the CFF blocks generated with G above are (1,2,3), (2,4,9), (3,4,10), (4,5,6), (1,4,7), (2,5,7), (3,5,8), (4,8,12), (1,5,9), (2,6,10), (3,6,9), (7,8,9), (1,6,8), (2,8,11), (3,7,11), (10,11, 12);
(d) constructing an N multiplied by N incidence matrix M by the CFF block, wherein each row in the M corresponds to one CFF block, the corresponding position value of the block element is 1, and the rest positions are 0;
(e) inverting M according to bits to obtain a code word matrix C which is r-CFF;
(f) expanding C to improve the fingerprint collusion attack resistance, wherein the expansion mode is that 1 and 0 are respectively replaced by 10 and 01 to finally obtain r-CFF codes;
(3) constructing an NxN I code word matrix, which comprises the following specific steps:
(g) generating an N multiplied by N matrix with diagonal elements of 0 and the rest elements of 1, wherein N is the number of r-CFF groups;
(h) negating elements with the lower triangle being 1;
(i) carrying out code word expansion on the I code to resist average collusion attack, wherein the expansion modes are 10 and 01 to replace 1 and 0 respectively;
(4) and taking the I code as a region code, taking the CFF code as a user code, carrying out block coding, establishing a final fingerprint library, and then storing the fingerprint library for use when embedding.
The fingerprint embedding is to select a fingerprint to be constructed before and embed the fingerprint into a DFT phase coefficient of vector map data, and comprises the following specific implementation steps:
(5) reading vector map data, appliedConstructing a complex sequence from the coordinate points；
(6) To pairPerforming DFT conversion to calculate the phase coefficientA t Sum of amplitude coefficients；
(7) Scrambling the fingerprint to be embedded by applying a Logistic chaotic algorithm to increase the fingerprint security, wherein an initial value of Logistic transformation is used as a key for extracting fingerprint information;
(8) embedding fingerprint information into the phase coefficient by using a QIM method, wherein the quantization embedding process is shown as the following formula:
wherein Q is a quantization value, ICFF is a fingerprint sequence,the method comprises the steps of obtaining a DFT phase coefficient sequence containing a fingerprint;
(9) toPerforming DFT inverse transformation to obtain map data containing fingerprint vector。
The fingerprint extraction and traitor tracing comprises the steps of extracting fingerprints, comparing the extracted fingerprints with the fingerprints in a fingerprint library, calculating the Hamming distances of the extracted fingerprints and the fingerprints in the fingerprint library, and judging the user of the fingerprint in the fingerprint library with the minimum Hamming distance to be a traitor;
(10) reading vector map data to be tested, application typeConstructing a complex sequence from the coordinate points；
(11) To pairPerforming DFT conversion to obtain phase coefficientA t ’ |；
(12) Extracting the value of ICFF by a QIM method, wherein Q is a quantized value when the fingerprint is embedded;
(13) performing Logistic reverse scrambling on the extracted sequence;
(14) determining fingerprint information of the fingerprint sequence subjected to Logistic reverse scrambling by adopting a voting principle to obtain a final fingerprint sequence;
(15) calculating the Hamming distance between the extracted fingerprint sequence and the fingerprint in the fingerprint library, and judging the user corresponding to the fingerprint in the library with the smallest Hamming distance with the suspicious fingerprint sequence as an illegal user, thereby tracing traitors. The hamming distance calculation formula is as follows:
wherein the content of the first and second substances,，⨁ denotes the modulo-2 addition, D (x, y) denotes two fingerprint sequences in phaseThe sum of the number of different codewords at the same position.
Claims (1)
1. The vector map data digital fingerprint method based on the I code and the CFF is characterized by comprising the following steps of:
the method comprises the following steps: carrying out block coding on the I code and the CFF code to construct a fingerprint database, and specifically comprising the following steps:
(1) selecting a set V and a collusion attack resistant number r, and constructing a Boolean matrix B with n multiplied by n elements of 1;
(2) the method comprises the following steps of constructing an Nxn CFF code word matrix:
(a) generating a Boolean matrix B with n multiplied by n elements of 1;
(b) modifying the values of the corresponding element pairs in B with the union of the sets { (1, …, r +1), (r +2, …,2r +2), …, (n-r, …, n) } and { (1, n/(r +1) +1, …, (r × n)/(r +1) +1), (2, n/(r +1) +2, …, (r × n)/(r +1) +2), …, (n/(r +1),2n/(r +1), …, n) } as the CFF basis set G;
(c) taking G as an initial value, carrying out 3-order full arrangement on n elements in V, traversing all the block groups, judging whether the corresponding value of an element pair B of a certain block group is 0, and if 0 indicates that the element pair appears, discarding the block group; if the value is 1, the element pair does not appear, and the block group is reserved;
(d) constructing an N multiplied by N incidence matrix M by the CFF block, wherein each row in the M corresponds to one CFF block, the corresponding position value of the block element is 1, and the rest positions are 0;
(e) inverting M according to bits to obtain a code word matrix C which is r-CFF;
(f) expanding C to improve the fingerprint collusion attack resistance, wherein the expansion mode is that 1 and 0 are respectively replaced by 10 and 01 to finally obtain r-CFF codes;
(3) constructing an NxN I code word matrix, which comprises the following specific steps:
(g) generating an N multiplied by N matrix with diagonal elements of 0 and the rest elements of 1, wherein N is the number of r-CFF groups;
(h) negating elements with the lower triangle being 1;
(i) carrying out code word expansion on the I code to resist average collusion attack, wherein the expansion modes are 10 and 01 to replace 1 and 0 respectively;
(4) taking the code I as a region code, taking the CFF code as a user code, carrying out block coding, establishing a final fingerprint library, and then storing the fingerprint library;
step two: the fingerprint embedding process is as follows:
(5) reading vector map data, and constructing a complex sequence from the coordinate points by applying the formula (1);
ak＝xk+iyk(k＝1,2,...,N) (1)
in the formula, xk,ykRespectively representing the values of the vertex coordinates X, Y, N representing the number of vertices, i representing the imaginary part of the complex number, akRepresenting the constructed complex number;
(6) performing DFT conversion on the complex sequence, and calculating to obtain a phase coefficient and an amplitude coefficient;
(7) scrambling the fingerprint to be embedded by applying a Logistic chaotic algorithm to increase the fingerprint security, wherein an initial value of Logistic transformation is used as a key for extracting fingerprint information;
(8) embedding fingerprint information into phase coefficients by applying a Quantization Index Modulation (QIM) method, and quantizing the embedded fingerprint by using equation (2):
q is the quantization step size, | AtL represents the phase coefficient, i represents the bit order of the fingerprint to be embedded, MOD is the mathematical modulo operation, | A'tL represents the phase coefficient after embedding the fingerprint;
(9) performing DFT inverse transformation on the fingerprint-containing phase sequence to obtain fingerprint-containing vector map data;
step three: fingerprint extraction and traitor tracing
(10) Reading vector map data to be detected, and generating a complex sequence according to the formula (1);
(11) performing DFT conversion on the complex sequence to obtain a phase coefficient;
(12) extracting the value of ICFF by a QIM method, wherein Q is a quantized value when the fingerprint is embedded;
(13) performing Logistic reverse scrambling on the extracted sequence;
(14) determining fingerprint information of the fingerprint sequence subjected to Logistic reverse scrambling by adopting a voting principle to obtain a final fingerprint sequence;
(15) calculating the Hamming distance between the extracted fingerprint sequence and the fingerprint in the fingerprint library, judging the user corresponding to the fingerprint in the library with the minimum Hamming distance with the suspicious fingerprint sequence as an illegal user, tracking the traitor, and calculating the Hamming distance by using the formula (3):
n represents the length of the fingerprint, FiIs the original fingerprint, Fi' is the fingerprint extracted from the data under test,denotes calculation of a hamming distance, D being the calculated hamming distance.
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| CN110223213B (en) * | 2019-06-14 | 2022-10-04 | 兰州交通大学 | Vector space data digital fingerprint method for GD-PBIBD coding |
| CN110958232B (en) * | 2019-11-22 | 2022-12-06 | 南京邮电大学 | Collusion-resistant power data fingerprint coding method based on CFF code and RS code |
| CN113326485B (en) * | 2021-05-07 | 2022-09-09 | 南京邮电大学 | Nearest neighbor collusion resistant digital fingerprint generation method based on dynamic network representation learning |
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