CN103152608A - Method for realizing digital fingerprint encrypted video multicast transmission - Google Patents

Abstract

The invention discloses a method for realizing digital fingerprint encrypted video multicast transmission. The method comprises digital fingerprint encrypted transmission and digital fingerprint encrypted receiving. The digital fingerprint encrypted transmission comprises the following steps of: performing moving picture experts group-2 (MPEG-2) standard compression on carrier information source data of images and videos; processing image-based or video-based digital fingerprint data to finally form digital fingerprint data; deciding the energy magnitudes of digital fingerprint embedding and the relation of the energy magnitudes according to the probability of different branches of a tree structure to mutually generate collusion attack; processing by code division multiple access/time division multiple address (CDMA/TDMA) combined quadrature modulation to form blended data; enabling the blended data to form an encrypted data stream; and finally transmitting through a channel. The digital fingerprint encrypted receiving comprises the following steps of: deciphering and compressing according to a secret key K<m>, K<(i)>; recovering the information source data of the images and the videos; meanwhile, performing demodulation and processing on the information source data of the images and the videos, detecting the collusion attack generated among all levels of the tree structure by correlation functions to finally obtain the digital fingerprint data. The method for realizing the digital fingerprint encrypted video multicast transmission has the advantages that the safety is high; the communication cost is reduced; and meanwhile, the right and the validity of a system to track lawbreakers are enhanced.

Description

Realize the method for the Video Multicast transmission that digital finger-print is encrypted

Technical field

The present invention relates to the technical field of information security, is the technology of the method for the Video Multicast transmission that realizes that digital finger-print is encrypted specifically.

Background technology

The digital finger-print video is the process of the fingerprint Digital Signal Processing of different identification that the given Video service signal of user is embedded, and utilizes the different meaning bits that occur to identify between the user.This sign normally realizes by the robust digital watermark telescopiny also referred to as fingerprint load pay-load.In digital copyright management DRM text, the main purpose of fingerprint embedding and encryption is that the protection video content is not subjected to single or collusion attack is disturbed.Wherein, the collusion attack of digital video is the sixty-four dollar question that its application faces, and therefore, the anti-collusion attack ability of digital video is its important technology index that can use.

Present Digital Fingerprinting Technology reaches far away the practical stage, and this is because people have ignored the research of watermark fail safe.Digital finger-print belongs to the digital watermarking research category.For a long time, the robustness of watermark is more paid close attention in the research of digital watermarking, i.e. how research resists the attack of some non-malice, as additive noise, filtration, lossy compression method and resist geometric attacks etc., and has ignored the research of watermark fail safe.Wait application for fingerprint recognition and copy control, the fail safe of watermark is a very important problem, and wherein, collusion attack is that digital finger-print is the most effectively attacked.In collusion attack, a plurality of conspirators generate a new copy with a plurality of copy collusion of the same works that they have, in new copy, finger print information is removed or weakens, thereby, digital finger-print not only requires to resist general signal and processes attack and single copy-attack, and can also resist collusion attack.

The technology that realizes of present digital finger-print is mainly quadrature fingerprint, correlation fingerprint, also can be divided into continuous fingerprint and discrete fingerprint and anti-collusion code ACC digital finger-print.

(1) shortcoming of quadrature fingerprint is: the fingerprint application few for the user is more effective, but along with increasing of user, the complexity of fingerprint detection and tracing algorithm significantly increases, and the significantly minimizing in collusion of the energy of fingerprint, and this makes detector fingerprint can't be detected.

(2) correlation fingerprint shortcoming is: introduce correlation in design, even the duplicate of digital content is subjected to collusion attack, in fingerprint, the energy of relevant portion can significantly not reduce yet.The correlation fingerprint mainly is comprised of the coding fingerprint, and the C-safety code that is wherein proposed by Boneh and Shaw the earliest proposes double-deck code construction method and resists attack to the conspirator of determined number.This finger-print codes scheme is further improved by Yacobi, and he combines the embeding layer of a direct spreading sequence and the coding layer of C-safety code, has improved number of users.But the major defect of this method is a) when synchronous distortion, to be difficult to extract effective digital finger-print.B) anti-collusion attack person's limited amount.

(3) people such as Wade Trappe has proposed a kind of anti-collusion yard ACC in conjunction with the theory of Combination Design and district's group coding (as BIBD etc.), its major defect is: finger-print codes and embedding are combined, although improved the ability of the anti-collusion attack of fingerprint, greatly increased the instructions for use of transmission bandwidth.Therefore, system realizes that cost is higher.

Summary of the invention

The purpose of this invention is to provide a kind of safe, can effectively reduce the method that realizes the Video Multicast transmission that digital finger-print is encrypted of communications cost, solve the impact of transmission bandwidth and system opposing collusion attack factor, reduce the computing cost of transmitting terminal, strengthen simultaneously the illegal person's of system tracks right and validity thereof.

The present invention is achieved through the following technical solutions.

A kind of method that realizes the Video Multicast transmission that digital finger-print is encrypted is characterized in that: the method that the described Video Multicast of realizing that digital finger-print is encrypted transmits comprises that digital finger-print encrypted transmission and digital finger-print encryption receive.

Described digital finger-print encrypted transmission comprises the following step:

1) the carrier information source data of image and video through the Moving Picture Experts Group-2 compression, form MPEG-2 master data S _l

2) digital fingerprint data of image or video

Utilize the many wavelet transformation trees of DGHM to process, form a kind of many wavelet tree;

3) according to the importance ranking of digital finger-print, the different pieces of information of digital finger-print image characteristic point is become the fingerprint vector base of different-energy according to the different decomposition of many wavelet tree " father-child node " relation

And formation digital fingerprint data

4) energy size and the relation thereof of the probability decision digital finger-print embedding of collusion attack occur mutually according to the different branches of tree structure;

5) in compression domain, according to key K ^m, K ⁽ⁱ⁾By CDMA/TDMA quadrature modulation matrix, the digital finger-print modulation is embedded into S _lIn, form the blended data that comprises carrier master data and digital finger-print

Wherein, K ^mBe PKI, K ⁽ⁱ⁾Be user u ⁽ⁱ⁾Private key;

6) data of multicast and clean culture is encrypted respectively the data flow that forms transmission, passes through at last transmission;

Described digital finger-print is encrypted to receive and is comprised the following steps:

1) according to key K ^m, K ⁽ⁱ⁾The compression bit flow data V of deciphering multicast and clean culture, wherein V may suffer collusion attack, also may not have;

2) carry out MPEG-2 and decompress, Recovery image and video source data simultaneously, are carried out demodulation according to CDMA/TDMA combination orthogonal matrix;

3) image and video data are carried out DGHM and decompose, and same spatial location at different levels and the different frequency sub-bands coefficient on direction are divided into same group and consist of a kind of symmetrical junction paper mulberry with " father-child node " relation;

4) sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

5) detect with normalizated correlation coefficient, coefficient correlation is defined as follows:

$\mathrm{\&eta;}=\frac{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{(i_1,...,i_l)}\&CenterDot;Y^{(i_1,...,i_l)}}{\sqrt{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{{(i_1,...,i_l)}^2}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{Y}^{{(i_1,...,i_l)}^2}}}--------\left(1\right)$

If η＞T (detection threshold of setting), digital fingerprint data detects, and wherein T is the detection threshold of setting, and η illustrates Y more near 1 ⁽ⁱ⁾More be approximately equal to original fingerprint data

6) according to statistics, relevance function detector tree generation collusion attack at different levels obtain digital fingerprint data at last.

Described step 4) with step 6) in collusion attack comprise the following steps:

If SC is for detecting and point out the index of collusion attack probability of happening, the suspicious copied content that definition collusion attack function produces is

K is the conspirator, and g (.) is the collusion function, for the 1≤l that sets≤L level, detects the collusion process as follows from V:

A) the fingerprint tree first order detects: detector is set up digital finger-print Y and each the D1 fingerprint that extracts in the first order

Statistic correlation:

$T^{i_1}=\frac{<Y,a^{i_1}>}{\left|\right|a^{i_1}\left|\right|},i_1=\mathrm{1,2},...,D_1-----\left(2\right)$

Wherein, || a|| is the Euclid norm of a, and the zone that first order detection collusion is distorted is

H1 is that thresholding is estimated in first order prediction;

B) fingerprint tree the 2nd≤l≤L level detects: the estimation region of known (l-1) level collusion attack is GR (l-1), for any [i ₁..., i _l-1] ∈ GR (l-1), the result of the 2nd≤l≤L level detection statistics is:

$T^{i_1,...,i_{l-1},i_l}=\frac{<Y,a^{i_1,i_2,...,i_{l-1},i_l}>}{\left|\right|a^{i_1,i_2,...,i_{l-1},i_l}\left|\right|},i=\mathrm{1,2},...,D_l-------\left(3\right)$

Detect and point to the zone that collusion occurs $\mathrm{GR}\left(l\right)=\left\{\right[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l]:[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1).{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}\&GreaterEqual;h_l\},$ h _lPrediction thresholding for l level fingerprint detection;

C) detector estimates that the index that output collusion occurs is set to

Described digital finger-print CDMA/TDMA combination orthogonal matrix carries out being provided with in demodulation the fingerprint drift compensation method, embed exactly digital fingerprint data in the motion vector of MPEG-2 video sequence reference frame, described fingerprint drift compensation method, comprised the digital finger-print secret information that in the reference frame, motion vector embeds, and can only be transferred to validated user by unicast tunnel, specifically comprise the following steps:

A) for the DCT coefficient of each MPEG-2 coding, if it does not modulate the embedding digital finger-print, carry out so Variable Length Code VLC operation, and pass through together K with motion vector, quantizing factor and side information ^mEncrypt, all users are given in multicast;

B) for the DCT coefficient of each MPEG-2 coding, if its modulation has embedded digital finger-print, so at first carry out inverse quantization Q ^-1, then to user u ⁽ⁱ⁾Modulation embeds corresponding digital fingerprint data and adds corresponding drift compensation signal data, forms like this to comprise drift-compensated digital finger-print coefficient, then quantizes Q and Variable Length Code VLC.

C) last, pass through key K ⁽ⁱ⁾Blended data is encrypted also clean culture to user i.

Described digital finger-print CDMA/TDMA hybrid modulation matrix P=P ^JointBe a upper triangular matrix:

Known { p _{L, l}} _{L=1 ..., L}And P ^JointThe time, we can seek N ₁, N ₂..., N _LSatisfy relation:

$P^{\mathrm{Joint}}{\left[\begin{array}{ccc}{N}_1& {\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">N</figure-callout>}}_2...& N_L\end{array}\right]}^T=N{\left[\begin{array}{ccc}{\mathrm{\&rho;}}_1& {\mathrm{\&rho;}}_2...& {\mathrm{\&rho;}}_L\end{array}\right]}^{T}s.t.\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{N}_l=N,0\&le;N_l\&le;N-----\left(12\right)$

P wherein _{L, L}＞ρ _L, p _{1, l}, p _{2, l}..., p _{L, l}Be respectively tree structure Data Modulation coefficients at different levels; ρ ₁, ρ ₂..., ρ _LThe probability that occurs collusion attack for tree structure nodes at different levels.

In the embedding of described CDMA/TDMA hybrid modulation fingerprint, known P ^Joint{ N _l} _{L=1 ..., L}, in 1≤l of fingerprint tree structure≤L level, for the fingerprint base

There is relation:

$a^{i_1,...,i_l}={a_l}^{i_1,...,i_l}\mathrm{\&Pi;}{a_{l+1}}^{i_1,...,i_l}...\mathrm{\&Pi;}{a}_L^{i_1,...,i_l}----\left(13\right)$

Here, Gaussian distributed And it is separate,

Length is Nk, and is embedded in Sk, symbol " ∏ " the expression series connection factor.

For the user

u ⁽ⁱ⁾The l part digital finger-print content that receives is

Here, digital finger-print

Concrete form be:

$W_i^{(i_1,...,i_l)}=\sqrt{{\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">p</figure-callout>}}_{1,l}}{a}_l^{i_1}+\sqrt{{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">p</figure-callout>}}_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{l,l}}{a}_l^{i_1,...,i_l}----\left(14\right)$

During collusion attack, suppose total K conspirator, SC is the detection index that points to the conspirator, and collusion attack person to divide L be each grouping

For 1≤l＜L, the known digital content

Assailant in SCl by

Produce l and partly conspire copied content, wherein, nl is the additive noise of being introduced by collusion attack person, supposes that the digital copies content that collusion obtains is V=V ₁Ω V ₂... Ω V _L

In the detection of described CDMA/TDMA hybrid modulation fingerprint, receiving the test side, known digital content by secret key decryption is V, and for 1≤l＜L, detecting step is as follows:

1) at first, detector is from V ₁Middle extraction Y ₁

2) first order of fingerprint tree detects: at the 1st grade, detector makes the fingerprint { Y of extraction _l} _{L=1 ..., L}With each D1 fingerprint base

Be correlated with and calculate ASSOCIATE STATISTICS:

$T^{i_1}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_k}^{i_1}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}}{\left|\right|{a_k}^{i_1}\left|\right|}^2},i_1=\mathrm{1,2},...,D_1----\left(15\right)$

Detector estimates that the first order collusion crime zone of output is:

$\mathrm{GR}\left(1\right)=\left\{\right[i_1]:{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}>h_1-----\left(16\right)$

Wherein, h ₁The thresholding that presets for tree structure first order fingerprint detection;

3) the 2nd≤l of fingerprint tree＜L level detects: the collusion zone of known detector output in the past is GR (l-1), for each [i ₁, i ₂..., i _l-1] ∈ GR (l-1), detector calculates ASSOCIATE STATISTICS:

${\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}\left|\right|{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}{\left|\right|}^2}},i_1=\mathrm{1,2},...,D_l--------\left(17\right)$

And point out that the collusion attack zone is: $\mathrm{GR}\left(l\right)=\left\{\right[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l]:[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1),{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}>h_l,$ Wherein, h _lThe thresholding that presets for tree structure l level fingerprint detection;

4) last, collusion attack person's index of detector output is:

In described digital finger-print encrypted transmission, the process that digital finger-print embedded and encrypted distribution is as follows:

A) according to the tree structure of digital finger-print, by formula $W_l^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}=\sqrt{{\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">p</figure-callout>}}_{1,l}}{a}_l^{i_1}+\sqrt{{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">p</figure-callout>}}_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{l,l}}{a}_l^{i_1,...,i_l}$ Generate user u ⁽ⁱ⁾Digital fingerprint data W ⁽ⁱ⁾

B) the MPEG-2 compression bit stream is divided into two parts: part 1 comprises motion vector, quantizing factor and other side information, and part 2 comprises DCT coefficient and VLD, the wherein variable normal decoding of VLD;

C) for the DCT coefficient that does not embed fingerprint, adopt the VLC coding.At first DCT coefficient for embedding fingerprint carries out inverse quantization, if it belongs to Sl, and grouping In the corresponding finger print data digital finger-print that adopts SS (spread spectrum) mode to embed be

Then, all DCT coefficients that comprise finger print data being carried out VLC forms the hybrid digital content that comprises digital finger-print and is

D) the DCT coefficient of non-embedded finger print data uses K ^mEncrypt and and motion vector, side information etc. together multicast to all users.For 1≤l＜L,

Use

Encrypt also multicast to grouping user

Digital content

Use private key K ⁽ⁱ⁾Encrypt also clean culture to user u ⁽ⁱ⁾

During described digital finger-print was encrypted and received, the process that digital finger-print embedded and encrypted distribution was as follows:

A) according to key K ^m, K ⁽ⁱ⁾The digital content data of deciphering multicast and clean culture

Wherein, V may suffer collusion attack, also may not have;

B) carry out the MPEG-2 decompression: at first the data of deciphering being carried out contrary variable-length decoding (is VLC ^-1Decoding); Then carry out inverse quantization Q ^-1, obtain non-overlapped 8 * 8DCT piece of digital picture and video source data, and according to key

Obtain embedding the position of the DCT coefficient of digital finger-print, last, in conjunction with motion compensation and inverse discrete cosine transformation operation recovery MPG-2 sequence of video images;

D) the CDMA/TDMA combination orthogonal matrix according to formula (11) carries out demodulation to digital fingerprint data;

E) based on the symmetrical structure fingerprint tree of Fig. 6 " father-child node " relation, utilize mould 2 operations, the sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

F) carry out the similarity measurement of digital finger-print with normalizated correlation coefficient defined formula (1);

G) according to statistic correlation function formula (15)-(17), the contingent collusion attack situation of detector tree, and the last index that detects collusion attack of output.

The present invention compared with prior art has the following advantages.

The present invention is in considering that the Video Multicast transmission is used, the capability problems of digital finger-print opposing collusion attack; Follow the tracks of the ability judgement of distorting the disabled user based on digital finger-print; Effective transmission bandwidth and the encryption method of digital finger-print; In decoding end, the reconstructing video technical problem.In the present invention 1) utilize spread spectrum to embed digital finger-print in video flowing; In order to reduce communications cost, the video coefficients that all user's multicast transmission are not embedded; The authorized user clean culture is embedded the video coefficients of digital finger-print.

The present invention proposes based on tree structure fingerprint multicasting technology and the design of combination fingerprint and allocative decision.Compare with existing orthogonal spectrum expansion fingerprint and coding fingerprint technique, advantage of the present invention is:

1) communications cost and the anti-collusion performance of taking into account system transmission, according to the difference of number of users and sequence characteristic, saved the communications cost of 48%-84% based on tree structure fingerprint multicasting technology than orthogonal spectrum expansion unicast technique.

2) in order further to reduce transmission bandwidth, CDMA/TDMA combination fingerprint design and distribution technique based on tree structure have been proposed.It is compared with tree structure fingerprint multicasting technology, has saved the 3%-9% communications cost.Comparatively speaking quadrature fingerprint technique, tree structure fingerprint multicasting technology and CDMA/TDMA make up three kinds of technology such as fingerprint design and distribution technique, and when number of users is less (approximately 10-20 user), quadrature fingerprint technique unicast technique performance is best; When number of users is more (as several thousand users), tree structure combination fingerprint is designed with best bandwidth usage effect.Therefore, for the video sequence (as personage's scene) that embeds less fingerprint, tree structure fingerprint multicasting technology has better bandwidth efficiency.And for the video sequence (as complex environment) that embeds more fingerprint, under certain network and design conditions, the design of tree structure CDMA/TDMA combination fingerprint has minimum communications cost.

3) in order to improve the video quality of receiving terminal reconstruct, under the prerequisite that does not increase communications cost, compare tree structure fingerprint multicasting technology, the fingerprint drift compensation method that this patent proposes makes the picture quality PSNR of CDMA/TDMA combination fingerprint designing technique reconstruct on average improve 1-1.5dB.

In order to improve the video quality of receiving terminal reconstruct, under the prerequisite that does not increase communications cost, compare tree structure fingerprint multicasting technology, this patent has proposed a kind of digital finger-print drift compensation method, make the picture quality PSNR of CDMA/TDMA combination fingerprint modulation embedded technology reconstruct on average improve 1-1.5dB, namely improved the picture quality of recovering.

4) according to the not at the same level and different branches of tree structure, patent adopts digital finger-print the modulation mathematical method that embeds and the ability of resisting collusion attack of different-energy size.

Description of drawings

Fig. 1 is the digital finger-print encryption transmission system block diagram that the present invention realizes the method for the Video Multicast transmission that digital finger-print is encrypted;

Fig. 2 is the digital finger-print encryption receiving system block diagram that the present invention realizes the method that the Video Multicast of digital finger-print encryption transmits;

Fig. 3 is the sub-band coefficients graph of a relation that the present invention realizes the wavelet decomposition more than 4 grades of the method that the Video Multicast of digital finger-print encryption transmits;

Fig. 4 is the Triangle Tree division figure that the present invention realizes wavelet coefficient more than the method for the Video Multicast transmission that digital finger-print is encrypted, a wherein a) grouping of many wavelet tree on the one-dimensional space, b) grouping Triangle Tree;

Fig. 5 is that the present invention realizes wavelet tree subband more than the method for the Video Multicast transmission that digital finger-print is encrypted Each subtree of coefficient is distributed the fingerprint method schematic configuration diagram;

Fig. 6 is fingerprint allocative decision figure (L=3, the D based on tree structure that the present invention realizes the method for the Video Multicast transmission that digital finger-print is encrypted ₁=D ₂=2, D ₃=3);

Fig. 7 is the schematic diagram ([ρ that carrier signal is divided when fingerprint is set L=3 that the present invention realizes the method for the Video Multicast transmission that digital finger-print is encrypted ₁, ρ ₂, ρ ₃]=[1/4,1/4,1/2]);

Fig. 8 is the schematic diagram of mutual collusion attack in fingerprint tree system of the present invention's method of realizing the Video Multicast transmission that digital finger-print is encrypted;

Fig. 9 is the MPEG-2 transmission system schematic diagram based on the modulation of CDMA/TDMA combined digital fingerprint that the present invention realizes the method for the Video Multicast transmission that digital finger-print is encrypted, wherein a) server transmitting terminal digital finger-print embeds and assigning process, and b) implementation procedure is processed in the decoding of user's receiving terminal;

Figure 10 is that the present invention realizes that the digital finger-print of the method for the Video Multicast transmission that digital finger-print is encrypted is embedded into the block diagram of the drift compensation method of motion vector in reference frame.

Embodiment

Below in conjunction with accompanying drawing, the present invention is realized that the method for the Video Multicast transmission that digital finger-print is encrypted is described in further detail.

The present invention realizes the method for the Video Multicast transmission that digital finger-print is encrypted, and comprises that the encryption of digital finger-print encrypted transmission and digital finger-print receives.

Described digital finger-print encrypted transmission comprises the following step:

1) the carrier information source data of image and video through the Moving Picture Experts Group-2 compression, form MPEG-2 master data S _l

2) digital fingerprint data of image or video

Utilize the many wavelet transformation trees of DGHM to process, form a kind of many wavelet tree;

3) according to the importance ranking of digital finger-print, the different pieces of information of digital finger-print image characteristic point is become the fingerprint vector base of different-energy according to the different decomposition of many wavelet tree " father-child node " relation

And formation digital fingerprint data

4) energy size and the relation thereof of the probability decision digital finger-print embedding of collusion attack occur mutually according to the different branches of tree structure;

5) in compression domain, according to key K ^m, K ⁽ⁱ⁾By CDMA/TDMA quadrature modulation matrix, the digital finger-print modulation is embedded into S _lIn, form the blended data that comprises carrier master data and digital finger-print $X_l^{\left(i\right)}=S_l+W_l^{\left(i\right)};$

6) data of multicast and clean culture is encrypted respectively the data flow that forms transmission, passes through at last transmission;

Described digital finger-print is encrypted to receive and is comprised the following steps:

1) according to key K ^m, K ⁽ⁱ⁾The compression bit flow data V of deciphering multicast and clean culture, wherein V may suffer collusion attack, also may not have;

2) carry out MPEG-2 and decompress, Recovery image and video source data simultaneously, are carried out demodulation according to CDMA/TDMA combination orthogonal matrix;

3) image and video data are carried out DGHM and decompose, and same spatial location at different levels and the different frequency sub-bands coefficient on direction are divided into same group and consist of a kind of symmetrical junction paper mulberry with " father-child node " relation;

4) sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

5) be defined as follows with normalizated correlation coefficient:

$\mathrm{\&eta;}=\frac{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}\&CenterDot;Y^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}}{\sqrt{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}^2}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{Y}^{{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}^2}}}--------\left(1\right)$

If η＞T (detection threshold of setting), digital fingerprint data detects, and wherein T is the detection threshold of setting, and η illustrates Y more near 1 ⁽ⁱ⁾More be approximately equal to original fingerprint data

6) according to statistics, relevance function detector tree generation collusion attack at different levels obtain digital fingerprint data at last.

The below describes in detail:

One. system survey with realize principle

Realize that as digital watermarking the copyrighted digital content protection is the powerful guarantee that information security is used with digital finger-print; wherein the transmission technology of Information hiding is the core technology that information security is used, and anti-collusion and incompressible attack are the Key Performance Indicators of Information hiding core technology.Especially under different transmission channel conditions, realizing that digital of digital video data is transferred to multiple users simultaneously reliably, and satisfy the requirement of cbr (constant bit rate) and low distortion, is the focal spot techniques of present multi-casting communication system research.According to the traditional theory of Shannon ' s, when given channel capacity, source and channel coding branch realizes.But under multi-user environment, this technology is difficult to reach the optimization encoding and decoding of information source and channel.Therefore, there is the resource optimization assignment problem in traditional multi-casting communication system.

This patent has proposed a kind of multicast transmission system that utilizes digital finger-print to be encrypted as digital watermarking for the safety issue of MPEG-2 transmission with application technology.The structure of whole system as shown in Fig. 1-2, in figure, symbol

The fingerprint vector data that presentation video or video data obtain after too much wavelet transformation;

Be respectively tree structure Data Modulation coefficients at different levels; K ^mBe PKI, K ⁽ⁱ⁾Be user u ⁽ⁱ⁾Private key; V expresses possibility and suffers the data content that receives after collusion attack; The digital fingerprint data of Y for extracting after decompressing.

(1) system principle and implementation procedure explanation:

Transmission ends realizes principle and basic step:

A) the carrier information source data of image and video through the Moving Picture Experts Group-2 compression, form MPEG-2 master data S _lB) digital fingerprint data of image or video

Utilize the many wavelet transformations trees of DGHM of people's propositions such as Kumsawat to process, form a kind of many wavelet tree.

C) according to the importance ranking of digital finger-print, the different pieces of information of digital finger-print image characteristic point is become the fingerprint vector base of different-energy according to the different decomposition of many wavelet tree " father-child node " relation

And formation digital fingerprint data

D) energy size and the relation thereof of the probability decision digital finger-print embedding of collusion attack occur mutually according to the different branches of tree structure.

E) in compression domain, according to key K ^m, K ⁽ⁱ⁾By CDMA/TDMA quadrature modulation matrix, the digital finger-print modulation is embedded into S _lIn, form the blended data that comprises carrier master data and digital finger-print $X_l^{\left(i\right)}=S_l+W_l^{\left(i\right)}.$

F) data of multicast and clean culture is encrypted respectively the data flow that forms transmission, passes through at last transmission.

Receiving terminal is realized principle and basic step:

A) according to key K ^m, K ⁽ⁱ⁾The compression bit flow data V of deciphering multicast and clean culture.Wherein, V may suffer collusion attack, also may not have.

B) carry out MPEG-2 and decompress, Recovery image and video source data.Simultaneously, carry out demodulation according to CDMA/TDMA combination orthogonal matrix.

C) image and video data are carried out DGHM and decompose, and same spatial location at different levels and the different frequency sub-bands coefficient on direction are divided into same group and consist of a kind of symmetrical junction paper mulberry with " father-child node " relation.

D) based on mould 2 operations, the sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

E) similarity measurement: be defined as follows with normalizated correlation coefficient:

$\mathrm{\&eta;}=\frac{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}\&CenterDot;Y^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}}{\sqrt{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}^2}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{Y}^{{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}^2}}}-------\left(1\right)$

If η＞T (detection threshold of setting), digital fingerprint data detects.Obviously, η is more near 1 explanation Y ⁽ⁱ⁾More be approximately equal to original fingerprint data

F) collusion attack situation contingent according to statistic correlation function check tree structure.Wherein, it is a characteristic part of the present invention that collusion attack detects, and is elaborated at this as follows.

Detection principle and the basic step of receiving terminal collusion attack:

If SC is for detecting and point out the index of collusion attack probability of happening, the suspicious copied content that definition collusion attack function produces is

K is the conspirator, and g (.) is the collusion function.For the 1≤l that sets≤L level, detect the collusion process as follows from V:

A) the fingerprint tree first order detects: detector is set up digital finger-print Y and each the D1 fingerprint that extracts in the first order Statistic correlation:

${\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}=\frac{<Y,a^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1}>}{\left|\right|a^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1}\left|\right|},i_1=\mathrm{1,2},...,D_1------\left(2\right)$

Wherein, || a|| is the Euclid norm of a.The zone that first order detection collusion is distorted is $\mathrm{GR}\left(1\right)=\left\{\right[i_1]:{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}>h_1\},$ H1 is that thresholding is estimated in first order prediction.

B) fingerprint tree the 2nd≤l≤L level detects: the estimation region of known (l-1) level collusion attack is GR (l-1).For any [i ₁..., i _l-1] ∈ GR (l-1), the result of the 2nd≤l≤L level detection statistics is:

${\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}=\frac{<Y,a^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,{\mathrm{<figure-callout\; id="2"\; label="i"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">i</figure-callout>}}_2,...,i_{l-1},i_l}>}{\left|\right|a^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,{\mathrm{<figure-callout\; id="2"\; label="i"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">i</figure-callout>}}_2,...,i_{l-1},i_l}\left|\right|},i=\mathrm{1,2},...,D_l------\left(3\right)$

Detect and point to the zone that collusion occurs $\mathrm{GR}\left(l\right)=\left\{\right[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l]:[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1).{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}\&GreaterEqual;h_l\},$ h _lPrediction thresholding for l level fingerprint detection.

C) detector estimates that the index that output collusion occurs is set to

(2) realization condition of system: compression standard is the video image under the MPEG-2 meaning; Transmission code rate is 1Mbps-50Mbps; Multicast users number: 1000-10000.

Two, system's each several part implementation procedure

(1) many wavelet decomposition of digital picture and digital video frame

When many wavelet decomposition of DGHM, under different yardsticks, the key property that its relevant wavelet sub-band coefficient has is that direction is identical with the position.When yardstick was determined, on the space, except high-frequency sub-band, each " father node " sub-band coefficients was relevant to all " child node " sub-band coefficients on the same direction of next stage.For the multistage subband of many small echos, when r=2 ties up, between " father-child node " sub-band coefficients of its wavelet decomposition more than 4 grades dependence as Fig. 3 a) as shown in,

Through after pre-filtering, original image or video frame images are divided into the 4 identical subimages of width size.Discrete many wavelet decomposition process and single wavelet decomposition process of two dimensional image are similar, but owing to there being a plurality of yardsticks (small echo) function to exist, and be corresponding with the number of sub images after single wavelet transformation of image, and the r number of sub images is arranged after many wavelet transformations.When wavelet decomposition more than the 1st layer, through after 2 small echo low-pass filtering and high-pass filtering, original image becomes 16 number of sub images, the b of its Relationship of Coefficients such as Fig. 3 respectively).When carrying out the 2nd layer of decomposition, similar single wavelet decomposition is just decomposed low frequency part further, and high frequency imaging partly remains unchanged.By that analogy.Decompose complete after, only having top 4 low-frequency images is low-frequency images completely, all contains the high frequency composition in all the other subimages.Under r dimension yardstick, the many wavelet transformations of L level can be r with picture breakdown ²(3L+1) number of sub images.After decomposing because many small echos are each, form more sub-band coefficients, may destroy Fig. 3 " father-child node " relation a), need to be to its position rearrangement reaction.Detailed process is to reset each 2 * 2 sub-block, makes 4 coefficients of same spatial location relation come together.

Other subband, we are divided into same group to the different frequency sub-bands coefficient on same spatial location and direction, and Fig. 4 illustrated on the one-dimensional space, and 16 coefficients in 4 coefficients of 1 coefficient in HL4 and HL3 and HL2 are divided in groups example.The sum of its grouping equals the sum of LH4, HL4 and HH4 sub-band coefficients, has 3 * 32 * 32=3072.

(2) the division condition of many wavelet tree structure of digital picture and digital video frame and digital finger-print thereof: according to different distributions and the different importance thereof of digital picture and digital video frame, the present invention has constructed the digital finger-print Information Hiding Techniques in a kind of many wavelet tree structure.

Many wavelet tree building method is as follows: after digital picture and digital video frame were decomposed through DGHM, we were divided into same group and consist of a subtree to the different frequency sub-bands coefficient on same spatial location and direction.According to the importance relation, each sub-band coefficients data of image and frame of video are become the fingerprint vector base of different-energy according to the different demarcation of many wavelet tree " father-child node " relation.Produce the digital finger-print information of varying strength on the different nodes of tree.Its structure on the one-dimensional space as shown in Figure 5, other the grouping coefficient similar.

The division condition of digital finger-print: in Fig. 5, the degree of depth of tree is L=4, and every one-level node has identical descendants's interstitial content D _l, l=1,2 ..., L, for each node in tree wherein except root node, i=[i ₁..., i _l], i _l=1,2 ..., D _l, the vector basis of unique digital fingerprint data

(YZ represents certain sub-band coefficients in many wavelet tree) satisfies Gaussian Profile

And separate.

(3) digital finger-print based on the anti-collusion attack of tree structure designs

Based on the digital finger-print structure of Fig. 5, Fig. 6 has illustrated a kind of symmetrical tree structure fingerprint design with anti-collusion attack that the present invention proposes.In the symmetrical tree structure, the degree of depth of each leaf node is L, (l-1, l=1,2 ..., L) level has identical child node Dl.

Interrelate with collusion attack, here hypothesis: grouping user U ^1,1In mutually the probability of collusion be all p ₃U ^1,1Each user of grouping and another grouping U ^1,2The probability that the user conspires mutually is p ₂, p ₂＜p ₃U ^1,1∪ U ^1,2In grouping, the probability of each user and other groups user collusion is p ₁, and p ₁＜p ₂＜p ₃The tree at different levels on, the finger print data base that it is unique

Tree node [i1 ..., i1] and (except root node) upper according to the Gaussian Profile rule Produce.Wherein l is the degree of depth of node, and i is certain user node, and { a} is separate for the fingerprint vector base simultaneously.For each user, all digital finger-prints from the leaf node to the root node are distributed to him, namely distribute to user u ⁽ⁱ⁾Digital finger-print content X ⁽ⁱ⁾In, the L of a total embedding fingerprint is

For example in Fig. 6, digital finger-print a ¹, a ^1,1And a ^1,1,1Be embedded into digital content X ⁽¹⁾In and distribute to user u ⁽¹⁾

(4) based on digital finger-print modulation technique and the allocative decision of tree structure

4.1 the CDMA of digital finger-print and TDMA modulation technique

Suppose that carrier information source data-signal S has N the DCT coefficient that may embed fingerprint, embedding so L fingerprint has two kinds of methods usually in S: based on CDMA with based on TDMA fingerprint modulation embedding grammar.

Modulate embedded technology based on the CDMA digital finger-print: in CDMA fingerprint modulation technique, the fingerprint base { energy that a} has identical length N and equates.Like this, user u ⁽ⁱ⁾Digital finger-print be the cumulative of tree structure fingerprint vector bases at different levels, its concrete form is:

$W^{\left(i\right)}=\sqrt{{\mathrm{\&rho;}}_1}{a}^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1}+\sqrt{{\mathrm{\&rho;}}_2}{a}^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,i_2}+...+\sqrt{{\mathrm{\&rho;}}_L}{a}^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,{\mathrm{<figure-callout\; id="2"\; label="i"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">i</figure-callout>}}_2,...,i_L}-----\left(4\right)$

Wherein, { ρ _l, l=1,2 ..., the sizes values of the digital finger-print index of modulation that the collusion attack probability determines occurs in L} serve as reasons different tree branch mutually, and relation is arranged This explanation, { ρ _l, l=1,2 ..., L} controlled tree embedding digital finger-print not at the same level the energy size and regulating correlation between different user.Therefore, distribute to user u ⁽ⁱ⁾And the video content form that comprises digital finger-print be: X ⁽ⁱ⁾=S+W ⁽ⁱ⁾, wherein S is carrier signal.

Based on TDMA fingerprint modulation technique: in TDMA fingerprint modulation technique, signal S is divided into S ₁..., S _LDeng L different non-overlapped parts.Therefore, S _lIn can embed fingerprint the carrier signal number of coefficients be N _l=ρ _lN, and

In Fig. 7, in every 4s, all frames belonged to Sl in first second, and all frames belonged to S2 in second second, and last two seconds in S3.If the sequence of video images long enough, S _lIn can embed fingerprint the carrier signal number of coefficients be approximately N _l=p _lN。In based on TDMA fingerprint modulation technique, the fingerprint base of tree l level

Having length is N _lDigital finger-print content X ⁽ⁱ⁾Distribute to user u ⁽ⁱ⁾, the fingerprint base of l level

Be embedded into carrier signal S _lIn the l part.Therefore, the video content that comprises digital finger-print is:

4.2 digital finger-print CDMA and TDMA modulation matrix

Based on CDMA and the TDMA modulating performance of tree structure finger prints processing system, we mainly measure the fingerprint energy size that embeds different digital fingerprint content for relatively.Suppose that carrier signal S is divided into L non-overlapped part

N wherein _lBe S _lIn can embed the signal number of fingerprint.Simultaneously, we suppose for user u ⁽ⁱ⁾,

Be S _lThe digital finger-print of middle embedding.For CDMA and TDMA modulation, distribute to user u ⁽ⁱ⁾And the l part digital video content concrete form that comprises digital finger-print is:

$X_l^{\left(i\right)}=S_l+W_l^{\left(i\right)}-----\left(5\right)$

Definition E _{K, l}K level fingerprint base for tree

Be embedded in

In energy, and

For

Gross energy.Further we define, and the element of the capable l row of matrix P k is

The k level fingerprint base of expression tree

Be embedded in

In energy and the ratio of gross energy.Therefore, the concrete form of digital finger-print CDMA and TDMA modulation matrix is respectively formula (6) and formula (7):

And relation is arranged in based on the TDMA modulation technique:

P ^TDMA[N ₁N ₂N _L] ^T=N[ρ ₁ρ ₂ρ _L] ^T-------(8)

N can embed the sum of fingerprint base in the carrier signal coefficient.

The effective bandwidth of CDMA and TDMA modulation digital fingerprint is relatively: at first, in based on the TDMA modulation technique, when k＞l, p is arranged _{K, l}=0, therefore,

In only embedded fingerprint base content at the k≤l level of tree.Notice the fingerprint base

In grouping

In shared by all users, so fingerprint is Therefore, in the TDMA modulation technique, tree structure fingerprint distribution system is not only to the non-overlapped coefficient of all user's multicasts, and the coefficient of the embedding fingerprint shared of multicast grouping user.And in the CDMA modulation technique, when k＞l, p is arranged _{K, l}＞0, tree structure fingerprint distribution system is the non-overlapped coefficient of multicast only.Therefore, from bandwidth availability ratio, more effective based on the CDMA modulation technique based on TDMA modulation technique ratio.

The anti-collusion attack of CDMA and TDMA modulation digital fingerprint is relatively: in based on the TDMA modulation technique, when k ≠ l, p is arranged _{K, l}=0, l level fingerprint base

Only be embedded in the digital finger-print content

In the l part.So collusion attack person can distinguish the different piece of digital content after the embedding fingerprint not at the same level of tree.They can point out the structure of fingerprint tree and the position that the conspirator is setting.According to the information of collecting, they can use special attack pattern-mutual collusion attack, attack the TDMA modulation technique.Suppose that SC is the index setting of pointing to collusion attack, { X ⁽ⁱ⁾} _{I ∈ SC}Be the digital content that contains finger print data that receives.In mutual collusion attack, collusion attack person is divided into L grouping And exist at least 1≤l＜L to make l grouping SC _lWith (l+1) grouping SC _l+1Be in the different branches of fingerprint tree, relation is namely arranged Collusion copied content V comprises L non-overlapped part { V _l} _{L=1 ..., L}, at grouping SC _lThe conspirator by collusion function

Produce the l partial content in V.Fig. 8 has illustrated a kind of example that mutual collusion attack may occur and detect on the fingerprint tree structure.The index SC={1=[1 that in figure, the hypothesis collusion attack occurs, 1,1], 2=[1,1,2] and, 4=[1,2,1], 7=[2,1,1] (being that dash area in the drawings occurs collusion attack).The conspirator selects SC ₁={ 7}, SC ₂={ 4}, SC ₃={ 1,2}.

The collusion digital content that produces is:

${\mathrm{<figure-callout\; id="1"\; label="V"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">V</figure-callout>}}_1=X_1^{\left(7\right)}={\mathrm{<figure-callout\; id="1"\; label="S"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">S</figure-callout>}}_1+a^2,$

${\mathrm{<figure-callout\; id="2"\; label="V"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">V</figure-callout>}}_2=X_2^{\left(4\right)}={\mathrm{<figure-callout\; id="2"\; label="S"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">S</figure-callout>}}_2+a^{\mathrm{1,2}}$

${\mathrm{<figure-callout\; id="3"\; label="V"\; filenames="HSA00000863421000022.png,HSA00000863421000033.png"\; state="\{\{state\}\}">V</figure-callout>}}_3=(X_3^{\left(1\right)}+X_3^{\left(2\right)})/2={\mathrm{<figure-callout\; id="3"\; label="S"\; filenames="HSA00000863421000022.png,HSA00000863421000033.png"\; state="\{\{state\}\}">S</figure-callout>}}_3+(a^{\mathrm{1,1,1}}+a^{\mathrm{1,1,2}})/2------\left(8\right)$

During detection, in the first order of tree, although a ¹And a ²All be suspected of committing a crime, but detector only can detect a ², because a ¹Directly do not consist of any part of V.At this moment, detector output detections zone is GR (1)=[2].In the second level, detector attempts to detect whether [2,1] or [2,2] are the crime subregions, but because a ^2,1And a ^2,2Not in V, therefore, detector points out that they are not the crime subregions.Due to the special construction of fingerprint tree design and unique multistep treatment process thereof, the anti-collusion ability of CDMA fingerprint modulation technique is better than TDMA fingerprint modulation technique.

4.3 digital finger-print CDMA/TDMA hybrid modulation technology

The advantage of digital finger-print CDMA and TDMA modulation matrix technology in discussing in conjunction with 4.2, patent further proposes a kind of digital finger-print CDMA/TDMA hybrid modulation embedded technology.In the design of combination fingerprint and distribution system, at first digital content owner or copyright owner generate a digital finger-print tree according to Fig. 6.Then, use CDMA/TDMA hybrid modulation technology to embed finger print data, to have improved effective bandwidth.At last, content owner or copyright owner are by certain form distribute digital content.

Digital finger-print CDMA/TDMA hybrid modulation matrix

For the validity requirement that realizes resisting the robustness of collusion attack and satisfying transmission bandwidth, at this, a kind of CDMA/TDMA hybrid modulation technology is proposed, at this moment modulation matrix P=P ^JointIt is a upper triangular matrix.At CDMA/TDMA hybrid modulation matrix P ^JointIn, its structural condition is:

p _{K, l}=0,-----(9) when k＞l

0＜p _{K, l}≤ 1,------(10) when k≤l

Wherein, (9) formula has realized effective bandwidth, the robustness of (10) formula feasible system (robustness means the ability of opposing collusion attack).

According to the requirement of formula (9) and (10), for the digital finger-print tree, at the 1st grade, p _1,1=1.At 2≤l≤L level, known p _{L, l}, we seek { p _{K, l}} _K＜lSatisfy a kind of fingerprint energy distribution relation: E _{1, l}: E _{2, l}: ...: E _{L-1, l}=ρ ₁: ρ ₂: ...: ρ _l-1At this moment, when k＜l, exist to concern p _{K, l}=ρ _k(1-p _{L, l})/(ρ ₁+ ... + ρ _l-1), the final CDMA/TDMA hybrid modulation matrix form that forms is:

Known { p _{L, l}} _{L=1 ..., L}And P ^JointThe time, we can seek N ₁, N ₂..., N _LSatisfy relation:

$P^{\mathrm{Joint}}{\left[\begin{array}{ccc}{N}_1& {\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">N</figure-callout>}}_2...& N_L\end{array}\right]}^T=N{\left[\begin{array}{ccc}{\mathrm{\&rho;}}_1& {\mathrm{\&rho;}}_2...& {\mathrm{\&rho;}}_L\end{array}\right]}^{T}s.t.\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{N}_l=N,0\&le;N_l\&le;N---\left(12\right)$

From (11) as seen, work as p _{L, L}=ρ _LThe time, P ^JointIt is exactly CDMA fingerprint modulation technique.Thereby we only consider p _{L, L}＞ρ _LSituation.

The embedded technology of CDMA/TDMA hybrid modulation fingerprint

Known P ^Joint{ N _l} _{L=1 ..., L}, in 1≤l of fingerprint tree structure≤L level, for the fingerprint base

There is relation: $a^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l}={a_l}^{i_1,...,i_l}\mathrm{\&Pi;}{a_{l+1}}^{{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l}...\mathrm{\&Pi;}{a}_{\mathrm{<figure-callout\; id="1"\; label="L\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">L</figure-callout>}}^{i_{}}-----\left(13\right)$

Here,

Gaussian distributed

And it is separate,

Length is Nk, and is embedded in Sk, symbol " ∏ " the expression series connection factor.

For the user

u ⁽ⁱ⁾The l part digital finger-print content that receives is $X_l^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}=S_l+W_l^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}.$

Here, digital finger-print

Concrete form be:

$W_l^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}=\sqrt{{\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">p</figure-callout>}}_{1.l}}{a}_l^{i_1}+\sqrt{{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">p</figure-callout>}}_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{l,l}}{a}_l^{i_1,...,i_l}------\left(14\right)$

During collusion attack, suppose total K conspirator, SC is the detection index that points to the conspirator, and collusion attack person to divide L be each grouping

For 1≤l＜L, the known digital content

Assailant in SCl by

Produce l and partly conspire copied content, wherein, nl is the additive noise of being introduced by collusion attack person.Suppose that the digital copies content that collusion obtains is V=V1 Ω V2 ... Ω VL.

The detection of CDMA/TDMA hybrid modulation fingerprint realizes technology

Receiving the test side, known digital content by secret key decryption is V, and for 1≤l＜L, detecting step is as follows:

1) at first, detector extracts Yl from Vl.

2) first order of fingerprint tree detects: at the 1st grade, detector makes the fingerprint { Y of extraction _l} _{L=1 ..., L}With each D1 fingerprint base

Be correlated with and calculate ASSOCIATE STATISTICS:

${\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}{\left|\right|{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}\left|\right|}^2}},i_1=\mathrm{1,2},...,D_1-------\left(15\right)$

Detector estimates that the first order collusion crime zone of output is:

$\mathrm{GR}\left(1\right)=\left\{\right[i_1]:{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}>h_1------\left(16\right)$

Wherein, h ₁The thresholding that presets for tree structure first order fingerprint detection.

3) the 2nd≤l of fingerprint tree＜L level detects: the collusion zone of known detector output in the past is GR (l-1), for each [i ₁, i ₂..., i _l-1] ∈ GR (l-1), detector calculates ASSOCIATE STATISTICS:

${\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}{\left|\right|{a_{\mathrm{<figure-callout\; id="1"\; label="k\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">k</figure-callout>}}}^{i_{}}\left|\right|}^2}},i_1=\mathrm{1,2},...,D_l------\left(17\right)$

And point out that the collusion attack zone is: $\mathrm{GR}\left(l\right)=\left\{\right[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l]:[{\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1),{\mathrm{<figure-callout\; id="1"\; label="T\; i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">T</figure-callout>}}^{i_{}}>h_l.$ Wherein, h _lThe thresholding that presets for tree structure l level fingerprint detection.

4) last, collusion attack person's index of detector output is:

(5) MPEG-2 digital finger-print modulation technique and transmission thereof realize technology

Based on CDMA/TDMA hybrid modulation technology, Fig. 9 is illustrated as a kind of MPEG-2 video request program (VOD) multicast transmission and realizes technology.Suppose K ^mBe PKI,

Be grouping user

Key, K ⁽ⁱ⁾Be user u ⁽ⁱ⁾Private key.

Fig. 9 a) in the server transmitting terminal, it is as follows that digital finger-print embeds and encrypt the process of distributing:

A) according to the tree structure of digital finger-print, by formula $W_l^{({\mathrm{<figure-callout\; id="1"\; label="i"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">i</figure-callout>}}_1,...,i_l)}=\sqrt{{\mathrm{<figure-callout\; id="1"\; label="p"\; filenames="HSA00000863421000022.png,HSA00000863421000041.png"\; state="\{\{state\}\}">p</figure-callout>}}_{1,l}}{a}_l^{i_1}+\sqrt{{\mathrm{<figure-callout\; id="2"\; label="p"\; filenames="HSA00000863421000011.png,HSA00000863421000012.png"\; state="\{\{state\}\}">p</figure-callout>}}_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{l,l}}{a}_l^{i_1,...,i_l}$ Generate user u ⁽ⁱ⁾Digital fingerprint data W ⁽ⁱ⁾

B) the MPEG-2 compression bit stream is divided into two parts: part 1 comprises motion vector, quantizing factor and other side information; Part 2 comprises DCT coefficient and VLD (variable normal decoding).

C) for the DCT coefficient that does not embed fingerprint, adopt the VLC coding.At first DCT coefficient for embedding fingerprint carries out inverse quantization, if it belongs to Sl, and grouping

In the corresponding finger print data digital finger-print that adopts SS (spread spectrum) mode to embed be Then, all DCT coefficients that comprise finger print data being carried out VLC forms the hybrid digital content that comprises digital finger-print and is

D) the DCT coefficient of non-embedded finger print data uses K ^mEncrypt and and motion vector, side information etc. together multicast to all users.For 1≤l＜L,

Use

Encrypt also multicast to grouping user

Digital content

Use private key K ⁽ⁱ⁾Encrypt also clean culture to user u ⁽ⁱ⁾

B at Fig. 9) process that the server receiving terminal in, digital finger-print embedded and encrypted distribution is as follows:

A) according to key K ^m, K ⁽ⁱ⁾The digital content data of deciphering multicast and clean culture

Wherein, V may suffer collusion attack, also may not have.

B) carry out the MPEG-2 decompression: at first the data of deciphering being carried out contrary variable-length decoding (is VLC ^-1Decoding); Then carrying out inverse quantization (is Q ^-1); Obtain non-overlapped 8 * 8DCT piece of digital picture and video source data, and according to key

Obtain embedding the position of the DCT coefficient of digital finger-print.At last, in conjunction with motion compensation and inverse discrete cosine transformation (being IDCT) operation recovery MPG-2 sequence of video images.

D) the CDMA/TDMA combination orthogonal matrix according to formula (11) carries out demodulation to digital fingerprint data.

E) based on the symmetrical structure fingerprint tree of Fig. 6 " father-child node " relation, utilize mould 2 operations, the sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

F) carry out the similarity measurement of digital finger-print with normalizated correlation coefficient defined formula (1).

If coefficient of similarity η＞T (detection threshold of setting), digital fingerprint data detects.Obviously, η is more near 1 explanation Y ⁽ⁱ⁾More be approximately equal to original fingerprint data

G) according to statistic correlation function formula (15)-contingent collusion attack situation of (17) detector tree, and the last index that detects collusion attack of output.

Three. the drift compensation method of digital finger-print CDMA/TDMA hybrid modulation

When digital finger-print transmitted, the finger print data that former frame embeds may be diffused into next frame, and the digital finger-print between different frame accumulates and can affect the quality of the video frame images of receiving terminal reconstruct.Therefore, this patent is embedded into digital finger-print in the motion vector of reference frame, and is transferred to each user by unicast tunnel.Its implementation procedure as shown in figure 10.

The implementation procedure of drift compensation method is as follows: a) for the DCT coefficient of each MPEG-2 coding, if it does not modulate the embedding digital finger-print, carry out so Variable Length Code VLC operation, and pass through together K with motion vector, quantizing factor and side information ^mEncrypt, all users are given in multicast.

B) for the DCT coefficient of each MPEG-2 coding, if its modulation has embedded digital finger-print, so at first carry out inverse quantization Q ^-1, then to user u ⁽ⁱ⁾Modulation embeds corresponding digital fingerprint data and adds corresponding drift compensation signal data, forms like this to comprise drift-compensated digital finger-print coefficient.Then quantize Q and Variable Length Code VLC.

C) last, pass through key K ⁽ⁱ⁾Blended data is encrypted also clean culture to user i.

In a word, key point of the present invention is as follows:

(1) the tree structure digital finger-print embedding/etection theory model under the collusion attack condition.Scientific practice proves, general Mathematical Modeling will have important directive significance for appropriate design and the concrete algorithm of evaluation analysis.Tree structure system of fingerprints theoretical model under this patent research collusion condition, be from the information hiding system model generally to specifically, again to concrete relation.To the processing of desynchronizing, digital finger-print embed, each stage such as detection analyzes and researches after collusion, effectively describe the mapping space size that desynchronizes, copy the system's internal relation under the multi-constraint conditions such as copy quality and conspirator's quantity after visual quality, each stage execution speed, collusion after desynchronize copy visual quality, adding fingerprint, digital finger-print embeds the means based theoretical in order to find safely and effectively in application.

(2) according to the not at the same level and different branches of tree structure, adopt the modulation of different-energy the fingerprint mathematical method that embeds and the ability that detects collusion attack.Digital video generally exists with compressed format in storage and transmitting procedure, considers that in actual applications make up fingerprint with the DCT territory of compressed video by CDMA/TDMA modulates embedded technology and resist collusion attack and have important practical significance.Fingerprint embedding characteristic in compression domain is different from the orthogonal spectrum expansion embedding parameter.Take compression domain DCT territory CDMA/TDMA combination fingerprint modulation embedded technology effectively to utilize fingerprint energy not at the same level, different branches; selecting compression domain to embed coefficient and can guarantee that execution speed can guarantee again visual quality and the security performance that desynchronizes, is important key technology and the protection point of the anti-collusion attack in this patent Real Time Compression territory.

(3) in order to improve the video quality of receiving terminal reconstruct, under the prerequisite that does not increase communications cost, the fingerprint drift compensation method that the present invention proposes.

Claims (7)

1. method that realizes the Video Multicast transmission that digital finger-print is encrypted is characterized in that: the described method that realizes the Video Multicast transmission that digital finger-print is encrypted comprises that digital finger-print encrypted transmission and digital finger-print encrypt reception,

Described digital finger-print encrypted transmission comprises the following step:

1) the carrier information source data of image and video through the Moving Picture Experts Group-2 compression, form MPEG-2 master data S _l

2) digital fingerprint data of image or video

Utilize the many wavelet transformation trees of DGHM to process, form a kind of many wavelet tree;

3) according to the importance ranking of digital finger-print, the different pieces of information of digital finger-print image characteristic point is become the fingerprint vector base of different-energy according to the different decomposition of many wavelet tree " father-child node " relation And formation digital fingerprint data

4) energy size and the relation thereof of the probability decision digital finger-print embedding of collusion attack occur mutually according to the different branches of tree structure;

5) in compression domain, according to key K ^m, K ⁽ⁱ⁾By CDMA/TDMA quadrature modulation matrix, the digital finger-print modulation is embedded into S _lIn, form the blended data that comprises carrier master data and digital finger-print

Wherein, K ^mBe PKI, K ⁽ⁱ⁾Be user u ⁽ⁱ⁾Private key;

6) data of multicast and clean culture is encrypted respectively the data flow that forms transmission, passes through at last transmission;

Described digital finger-print is encrypted to receive and is comprised the following steps:

1) according to key K ^m, K ⁽ⁱ⁾The compression bit flow data V of deciphering multicast and clean culture, wherein V may suffer collusion attack, also may not have;

2) carry out MPEG-2 and decompress, Recovery image and video source data simultaneously, are carried out demodulation according to CDMA/TDMA combination orthogonal matrix;

3) image and video data are carried out DGHM and decompose, and same spatial location at different levels and the different frequency sub-bands coefficient on direction are divided into same group and consist of a kind of symmetrical junction paper mulberry with " father-child node " relation;

4) sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

5) detect with normalizated correlation coefficient, coefficient correlation is defined as follows:

$\mathrm{\&eta;}=\frac{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{W_l}^{(i_1,...,i_l)}\&CenterDot;Y^{(i_1,...,i_1)}}{\sqrt{\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}}{W_l}^{{(i_1,...,i_l)}^2}\&CenterDot;\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{Y}^{{(i_1,...,i_l)}^2}}--------\left(1\right)$

If η＞T (detection threshold of setting), digital fingerprint data detects, and wherein T is the detection threshold of setting, and η illustrates Y more near 1 ⁽ⁱ⁾More be approximately equal to original fingerprint data

6) according to statistics, relevance function detector tree generation collusion attack at different levels obtain digital fingerprint data at last.

2. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 1, is characterized in that described step 4) with step 6) in collusion attack comprise the following steps:

If SC is for detecting and point out the index of collusion attack probability of happening, the suspicious copied content that definition collusion attack function produces is

K is the conspirator, and g (.) is the collusion function, for the 1≤l that sets≤L level, detects the collusion process as follows from V:

A) the fingerprint tree first order detects: detector is set up digital finger-print Y and each the D1 fingerprint that extracts in the first order Statistic correlation:

$T^{i_1}=\frac{<Y,a^{i_1}>}{\left|\right|a^{i_1}\left|\right|},i_1=\mathrm{1,2},...,D_1-----\left(2\right)$

Wherein, || a|| is the Euclid norm of a, and the zone that first order detection collusion is distorted is

H1 is that thresholding is estimated in first order prediction;

B) fingerprint tree the 2nd≤l≤L level detects: the estimation region of known (l-1) level collusion attack is GR (l-1), for any [i ₁..., i _l-1] ∈ GR (l-1), the result of the 2nd≤l≤L level detection statistics is:

$T^{i_1,...,i_{l-1},i_l}=\frac{<Y,a^{i_1,i_2,...,i_{l-1},i_l}>}{\left|\right|a^{i_1,i_2,...,i_{l-1},i_l}\left|\right|},i=\mathrm{1,2},...,D_l-------\left(3\right)$

Detect and point to the zone that collusion occurs $\left(l\right)=\left\{\right[i_1,...,i_l]:[i_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1).T^{i_1,...,i_l}\&GreaterEqual;h_l\},$ h _lPrediction thresholding for l level fingerprint detection;

C) detector estimates that the index that output collusion occurs is set to

3. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 1, it is characterized in that: described digital finger-print CDMA/TDMA combination orthogonal matrix carries out being provided with in demodulation the fingerprint drift compensation method, embed exactly digital fingerprint data in the motion vector of MPEG-2 video sequence reference frame, described fingerprint drift compensation method, comprised the digital finger-print secret information that in the reference frame, motion vector embeds, and can only be transferred to validated user by unicast tunnel, specifically comprise the following steps:

A) for the DCT coefficient of each MPEG-2 coding, if it does not modulate the embedding digital finger-print, carry out so Variable Length Code VLC operation, and pass through together K with motion vector, quantizing factor and side information ^mEncrypt, all users are given in multicast;

B) for the DCT coefficient of each MPEG-2 coding, if its modulation has embedded digital finger-print, so at first carry out inverse quantization Q ^-1, then to user u ⁽ⁱ⁾Modulation embeds corresponding digital fingerprint data and adds corresponding drift compensation signal data, forms like this to comprise drift-compensated digital finger-print coefficient, then quantizes Q and Variable Length Code VLC.

C) last, pass through key K ⁽ⁱ⁾Blended data is encrypted also clean culture to user i.

4. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 1, is characterized in that described digital finger-print CDMA/TDMA hybrid modulation matrix P=P ^JointBe a upper triangular matrix:

Known { p _{L, l}} _{L=1 ..., L}And P ^JointThe time, we can seek N ₁, N ₂..., N _LSatisfy relation:

$P^{\mathrm{Joint}}{\left[\begin{array}{ccc}{N}_1& N_2...& N_L\end{array}\right]}^T=N{\left[\begin{array}{ccc}{\mathrm{\&rho;}}_1& {\mathrm{\&rho;}}_2...& {\mathrm{\&rho;}}_L\end{array}\right]}^{T}s.t.\underset{l=1}{\overset{L}{\mathrm{\&Sigma;}}}{N}_l=N,0\&le;N_l\&le;N-----\left(12\right)$

P wherein _{L, L}＞ρ _L, p _{1, l}, p _{2, l}..., p _{L, l}Be respectively tree structure Data Modulation coefficients at different levels; ρ ₁, ρ ₂..., ρ _LThe probability that occurs collusion attack for tree structure nodes at different levels.

5. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 4, is characterized in that in the embedding of described CDMA/TDMA hybrid modulation fingerprint known P ^Joint{ N _l} _{L=1 ..., L}, in 1≤l of fingerprint tree structure≤L level, for the fingerprint base

There is relation:

$a^{i_1,...,i_l}={a_l}^{i_1,...,i_l}\mathrm{\&Pi;}{a_{l+1}}^{i_1,...,i_l}...\mathrm{\&Pi;}{a}_L^{i_1,...,i_l}----\left(13\right)$

Here,

Gaussian distributed

And it is separate,

Length is Nk, and is embedded in Sk, symbol " ∏ " the expression series connection factor.

For the user

u ⁽ⁱ⁾The part 1 digital finger-print content that receives is Here, digital finger-print

Concrete form be:

$W_l^{(i_1,...,i_l)}=\sqrt{p_{1,l}}{a}_l^{i_1}+\sqrt{p_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{1,l}}{a}_l^{i_1,...,i_l}----\left(14\right)$

During collusion attack, suppose total K conspirator, SC is the detection index that points to the conspirator, and collusion attack person divide L for each minute carefully

For 1≤l＜L, the known digital content

At SC _lIn the assailant by

Produce part 1 collusion copied content, wherein, n _lBe the additive noise of being introduced by collusion attack person, suppose that the digital copies content that collusion obtains is V=V ₁Ω V ₂... Ω V _L

6. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 5, it is characterized in that in the detection of described CDMA/TDMA hybrid modulation fingerprint, receiving the test side, known digital content by secret key decryption is V, for 1≤l＜L, detecting step is as follows:

1) at first, detector is from V ₁Middle extraction Y ₁

2) first order of fingerprint tree detects: at the 1st grade, detector makes the fingerprint { Y of extraction _l} _{L=1 ..., L}With each D1 fingerprint base Be correlated with and calculate ASSOCIATE STATISTICS:

$T^{i_1}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_k}^{i_1}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}{\left|\right|{a_k}^{i_1}\left|\right|}^2}},i_1=\mathrm{1,2},...,D_1----\left(15\right)$

Detector estimates that the first order collusion crime zone of output is:

$\mathrm{GR}\left(1\right)=\left\{\right[i_1]:T^{i_1}>h_1-----\left(16\right)$

Wherein, h ₁The thresholding that presets for tree structure first order fingerprint detection;

3) the 2nd≤l of fingerprint tree＜L level detects: the collusion zone of known detector output in the past is GR (l-1), for each [i ₁, i ₂..., i _l-1] ∈ GR (l-1), detector calculates ASSOCIATE STATISTICS:

$T^{i_1,...,i_{l-1},i_l}=\frac{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}<Y_k,{a_k}^{i_1,...,i_{l-1},i_l}>}{\sqrt{\underset{k=1}{\overset{L}{\mathrm{\&Sigma;}}}{\left|\right|{a_k}^{i_1,...,i_{l-1},i_l}\left|\right|}^2}},i_1=\mathrm{1,2},...,D_l--------\left(17\right)$

And point out that the collusion attack zone is: $\mathrm{GR}\left(l\right)=\left\{\right[i_1,...,i_l]:[i_1,...,i_{l-1}]\&Element;\mathrm{GR}(l-1),T^{i_1,...,i_l}>h_l,$ Wherein, h _lThe thresholding that presets for the 1st grade of fingerprint detection of tree structure;

4) last, collusion attack person's index of detector output is:

7. the method that realizes the Video Multicast transmission that digital finger-print is encrypted according to claim 6, is characterized in that in described digital finger-print encrypted transmission, and the process that digital finger-print embedded and encrypted distribution is as follows:

A) according to the tree structure of digital finger-print, by formula $W_l^{(i_1,...,i_l)}=\sqrt{p_{1,l}}{a}_l^{i_1}+\sqrt{p_{2,l}}{a}_l^{i_1,i_2}+...+\sqrt{p_{l,l}}{a}_l^{i_1,...,i_l}$ Generate user u ⁽ⁱ⁾Digital fingerprint data W ⁽ⁱ⁾

B) the MPEG-2 compression bit stream is divided into two parts: part 1 comprises motion vector, quantizing factor and other side information, and part 2 comprises DCT coefficient and VLD, the wherein variable normal decoding of VLD;

C) for the DCT coefficient that does not embed fingerprint, adopt the VLC coding.At first DCT coefficient for embedding fingerprint carries out inverse quantization, if it belongs to S _l, grouping

In the corresponding finger print data digital finger-print that adopts SS (spread spectrum) mode to embed be

Then, all DCT coefficients that comprise finger print data being carried out VLC forms the hybrid digital content that comprises digital finger-print and is

D) the DCT coefficient of non-embedded finger print data uses K ^mEncrypt and and motion vector, side information etc. together multicast to all users.For 1≤l＜L,

Use

Encrypt also multicast to grouping user

Digital content

Use private key K ⁽ⁱ⁾Encrypt also clean culture to user u ⁽ⁱ⁾

During described digital finger-print was encrypted and received, the process that digital finger-print embedded and encrypted distribution was as follows:

A) according to key K ^m, K ⁽ⁱ⁾The digital content data of deciphering multicast and clean culture

Wherein, V may suffer collusion attack, also may not have;

B) carry out the MPEG-2 decompression: at first the data of deciphering being carried out contrary variable-length decoding (is VLC ^-1Decoding); Then carry out inverse quantization Q ^-1, obtain non-overlapped 8 * 8DCT piece of digital picture and video source data, and according to key

Obtain embedding the position of the DCT coefficient of digital finger-print, last, in conjunction with motion compensation and inverse discrete cosine transformation operation recovery MPG-2 sequence of video images;

D) the CDMA/TDMA combination orthogonal matrix according to formula (11) carries out demodulation to digital fingerprint data;

E) based on the symmetrical structure fingerprint tree of Fig. 6 " father-child node " relation, utilize mould 2 operations, the sub-band coefficients of every grade of tree structure is calculated odd even, extract the digital finger-print watermark data Y that embeds ⁽ⁱ⁾

F) carry out the similarity measurement of digital finger-print with normalizated correlation coefficient defined formula (1);

G) according to statistic correlation function formula (15)-(17), the contingent collusion attack situation of detector tree, and the last index that detects collusion attack of output.

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