KR100879230B1 - Combined Fingerprinting and Decoding Methods - Google Patents

Abstract

The present invention relates to a method of combined fingerprinting and decoding of 3D data. In the combined fingerprinting and decryption method according to the present invention, A) at the server side transmitting encrypted 3D data, A-1) in response to input of 3D data including geometric information and additional information, the geometric information is essential. As an Feature Feature (EF), the additional information is separated as a Non Essential Feature (NEF), and the Essential Feature is divided into at least two subcategories, Core Feature (CF). ") And a Basic Feature (" BF "), and generating a one-dimensionally arranged Polygon Object Set (" POS ") based on the geometric information belonging to the subcategory. A-2) two-dimensionally aligning each set of polygon objects (POS) belonging to the subcategory to generate a POS map, A-3) applying encryption from each row of the POS map. Sampling the data, A-4) The encryption algorithm performs encryption on the sampled data, wherein the core feature (CF) is encrypted by a symmetry encryption key (K _S ), and the basic feature (Basic Feature, "BF") is encrypted using a group encryption key (K _G ), and A-5) partially encrypted geometric information obtained in step A-4) and addition of step A-1). Combining the information with each other to generate a partially encrypted 3D data file stream, and transmitting it to a plurality of users, and B) at each user terminal, decrypting the received 3D data file stream and displaying it on the user screen. When performing decryption, the Core Feature (CF) is decrypted by a symmetry encryption key K _S , and the basic feature is a decryption key Ki unique to each user terminal. here Ki, belonging to K _R inferred from the group encryption key, is applied to K _R = {K1, K2, K3, ... Ki ..., Kn}) to perform decryption It is made to include. The combined fingerprinting and decryption method of 3D data according to the present invention not only enables effective encryption and reduction of transmission bandwidth of 3D data, but also integrates decryption process and fingerprinting, which is a joint of decryption process and fingerprinting. Enabled implementations.

Description

Combined Fingerprinting and Decoding Method {METHOD FOR JOINT FINGERPRINTING AND DECRYPTION}

1 is a diagram illustrating a conventional fingerprinting and decoding method.

2 is a block diagram illustrating a partial encryption method of 3D data according to the present invention.

3 is a block diagram illustrating a process of data alignment of 3D data and construction of a polygon object set of input 3D data according to the present invention.

4 is a diagram illustrating a construction process of a polygon object set according to the present invention in more detail.

5 is a block diagram illustrating a partial encryption process from a polygon object set.

6 is a schematic diagram illustrating a combined fingerprinting and decoding method of 3D data according to the present invention.

FIG. 7 is a diagram specifically illustrating a cognitive ability result according to the number of columns (l) in a two-dimensional aligned POS map.

The present invention relates to a combined fingerprinting and decoding method. More specifically, the present invention relates to a method of combining fingerprinting and decryption of 3D data in which transmission bandwidth is reduced, decryption, and fingerprinting are integrated through transmission of a single encrypted data to a plurality of users.

A representative example of a conventional fingerprinting and decoding method is shown in FIG. Referring to FIG. 1, when 3D original data is received at a server side transmitting 3D data, a plurality of copies of the 3D original data are generated, and a plurality of copies of the 3D data are generated and fingerprinted and encrypted. Has been sent. According to this method, since a plurality of copies of the 3D data corresponding to the number n of users must be generated and transmitted, the waste of bandwidth is very large. Furthermore, since the server side has to perform fingerprinting (F ₁ -F _n ) and encryption for each copy, the data load of the server increases.

Generally, 3D data is stored in a physical file for data exchange or data acquisition between heterogeneous systems. At this time, the 3D data is VR (Computer Reality), CAD (Computer Aided Design), RP ( It is classified into various data file formats such as Rapid Prototyping. Depending on the format, the 3D file contains various information. Among these information, polygon or geometric / phase information is a representative and essential data unit representing 3D geometric data. Specifically, in the case of 3D files having VR and RP formats, polygons are data units representing 3D geometric data, and in the case of 3D files having CAD format, geometric / phase information is data units representing 3D geometric data.

In the present invention, we propose a combined Fingerprinting and Decryption ("JFD") based on partial encryption on a 3D model based on polygon units. In the method proposed in the present invention, only encryption is performed at the server side, and the same data is transmitted to all users. At the user receiving terminal, fingerprinting and decryption are integrated. In other words, fingerprinting and decryption are integrated, whereby it is performed in one integrated process in the fingerprinting and decoding process, and unique 3D data (unique 3D data) is provided for each user.

According to a preferred embodiment of the present invention, A) at the server side for transmitting encrypted 3D data, A-1) in response to the input of the 3D data including the geometric information and the additional information, the geometric information is essential Feature, " EF ", separating the additional information as a Non Essential Feature (" NEF "), and separating the essential feature with at least two sub-categories, Core Feature ("CF"). Separating into a basic feature ("BF") and generating a one-dimensionally arranged polygon object set ("POS") based on the geometric information belonging to the subcategory, A- 2) generating a POS map by two-dimensionally aligning each set of polygon objects (POS) belonging to the subcategory, A-3) selecting data to be applied for encryption from each row of the POS map. Sampling step, A-4) encryption to know Through the algorithm, but performs the encryption for the sampled data, the core feature (Core Feature, "CF") is, encrypted by the symmetric encryption key (symmetry encryption key, K _S), the basic feature (Basic Feature, " BF ″) is encrypted using a group encryption key K _G , and A-5) partially encrypted geometric information obtained in step A-4) and additional information of step A-1). Are combined with each other to generate a partially encrypted 3D data file stream, and transmits the same to a plurality of users, and B) at each user terminal, decrypts the received 3D data file stream and displays it on the user screen. When performing the core feature (Core Feature, "CF") is decrypted by a symmetry encryption key (symmetry encryption key, K _S ), the basic feature is unique decryption key Ki (where, Ki is said Belongs to the group encryption key K _R inferred from, K _R = consists of {K1, K2, K3, ... Ki ..., Kn} Yes), the application made by including the step of performing the decoding, 3D A combined fingerprinting and decoding method of data is provided.

According to a more preferred embodiment of the present invention, there is provided a method for combined fingerprinting and decoding of 3D data, characterized in that when the essential features are classified into subcategories, they are classified by random sampling.

2 is a block diagram illustrating a partial encryption method of 3D data according to a more preferred embodiment of the present invention. As shown in FIG. 2, when 3D data including geometric information and additional information is input, the geometric information is an essential feature (“EF”), and the additional information is a non-essential feature. , "NEF"). The 3D data includes geometric information and additional information. In the case of 3D files having VR and RP formats, a unit for representing geometric information is a polygon. In the case of a 3D file having a CAD format, the geometry / phase information is a data unit representing 3D geometry data. When 3D files with VR and RP formats are input, geometric information is obtained from a polygon object, which becomes an Essential Feature ("EF"). Other additional information, such as brightness, texture, color, etc., are classified as Non Essential Feature ("NEF"). In the case of a 3D file having a CAD format, geometric / phase information is extracted, and tesselated to rearrange the polygons into polygons. Other additional information (brightness, texture, color) is classified as a Non Essential Feature ("NEF"). As a result, the geometric information is separated as an Essential Feature ("EF") and the side information is separated as a Non-Essential Feature ("NEF"). Geometry information is obtained as a polygon object. These polygon objects are defined as facets and consist of coordinate values Vertex and vertical vectors (Normal) on three dimensions. More specifically, when 3D data is input, mesh data is generated, and then data allocation of each polygon object is performed, and polygon object set is stored by storing these polygon object data. , "POS") is obtained. At this time, each polygon object is arranged one-dimensionally in the POS. FIG. 3 is a block diagram illustrating a process of arranging data of 3D data of an input 3D data and constructing a POS. FIG. 4 is a view illustrating a process of POS operation. It is explained in detail.

Essential features (EF) containing geometric information are divided into at least two subcategories. For example, an essential feature EF containing geometric information is separated as a core feature ("CF") and a basic feature ("BF"). At this time, the naming of the subcategory is for understanding, and the naming of these may be done arbitrarily. Among the geometric information belonging to the essential feature EF, the separation of the core feature ("CF") and the basic feature ("BF") is preferably performed by random sampling. For this purpose, a random sampling operation is performed. The two sub-categories, Core Feature ("CF") and Basic Feature ("BF"), obtained from the essential features (EF), are separate polygons through the data alignment of 3D data and the construction of POS. An object set POS is obtained.

5 is a block diagram illustrating a partial encryption process from a polygon object set. Referring to FIG. 5, a partial encryption process from a polygon object set will be described in detail. Through the above process, the polygon object set (POS), which is built on the core feature (CF) and the basic feature (BF), respectively, is subjected to data alignment. This results in a POS map in which the polygon objects are arranged two-dimensionally. At this time, each polygon object is defined by a row and a column. According to a preferred embodiment of the present invention, it could be confirmed that fingerprinting and their cognitive power are influenced by the data alignment method. The data to apply for encryption is sampled from each row of the POS map with a two-dimensional array. At this time, the sampling is preferably performed by random sampling. In other words, it is preferable that sampling of data to be applied for encryption is performed by a random sampling operation. Among the polygon objects constituting the polygon object set, encryption is performed only on randomly sampled data. In other words, only randomly sampled partial data for the POS map is applied to the encryption, resulting in encrypted data for them. Through this process, a partially encrypted polygon object set (POS) is obtained. The obtained partially encrypted polygon object set forms an encrypted 3D file stream together with the above-described additional information. The encrypted 3D file stream is transmitted to all users in the same way.

In this case, at least some of the plurality of classes belonging to the subcategory are encrypted by a symmetry encryption key (K _S ), and the remaining categories are encrypted by a group encryption key (K _G ). do. For example, when classified into two sub categories, Core Feature (CF) is encrypted by a symmetry encryption key (K _S ) and Basic Feature (BF). Is encrypted by a group encryption key (K _G ). As a result, geometric information separately encrypted by a symmetry encryption key (K _S ) and a group encryption key (K _G ) is combined with additional information to implement an encrypted 3D file stream.

At this time, each user is a symmetry encryption key (K _S ) and Ki (where Ki belongs to K _R inferred from the group encryption key, K _R = {K1, K2, K3, ... Ki ..., Kn}. Therefore, the normal decryption is performed on the core feature (CF), and the decryption is performed slightly different for each user. By this procedure, even if the same 3D data is provided to the user, a slightly different image for each user is displayed on the user screen. That is, 3D data unique to each user is provided to each user. This allows tracking of 3D data for each user. In addition, fingerprinting is integrated in the decoding process, which means that the decoding process and the fingerprinting are implemented in a joint form.

는 복호화되고, 핑거프린트된 3D 데이터를 의미한다. 구체적으로, 코어 피쳐(Core Feature, "CF")에 속하는 기하 정보는 대칭 암호화키(symmetry encryption key, K_S)에 의해 암호화되고, 베이식 피쳐(Basic Feature, "BF")에 속하는 기하정보는 그룹 암호화키(group encryption key, K_G)에 의해 암호화된다. 그 후, 암호화된 3D 데이 터 파일 스트림이 사용자에게 전송된다. 한편, 사용자 단말에서는, 코어 피쳐(Core Feature, "CF")에 대한 암호화키인 대칭 암호화키(symmetry encryption key, K_S)를 갖고 있다. 이에 반해, 그룹 암호화키(group encryption key, K_G)와 동일한 암호화키는 갖고 있지 아니하다. 반면에, 각 사용자는 그룹 암호화키로부터 유추된 키인 K_R(여기서, K_R = {K1, K2, K3, ... Ki ..., Kn}으로 구성되어 있음)에 속하는 하나의 키를 갖는다. 즉, 그룹 암호화키(group encryption key, K_G)와 약간 다른 키에 의해 복화화가 수행된다. 따라서, 각 사용자 별로 서로 다른 복호화가 수행되며, 이것은 사용자별로 고유한 3D 데이터를 생성한다. 결과적으로, 복호화를 통해 핑거프린팅된 3D 데이터가 사용자에게 제공되며, 이것은 핑거프린팅이 복호화와 통합되어 있음을 의미한다.6 is a schematic diagram illustrating a combined fingerprinting and decoding method of 3D data according to the present invention. In FIG. 6, X is 3D data, Y is encrypted 3D data,

Means decoded and fingerprinted 3D data. Specifically, the geometric information belonging to the Core Feature (CF) is encrypted by a symmetry encryption key K _S , and the geometric information belonging to the Basic Feature (BF) is a group. Encrypted by a group encryption key (K _G ). The encrypted 3D data file stream is then sent to the user. On the other hand, the user terminal has a symmetry encryption key (K _S ) which is an encryption key for the core feature ("CF"). On the other hand, it does not have the same encryption key as the group encryption key (K _G ). On the other hand, each user has one key that belongs to K _R , where the key is inferred from the group encryption key, where K _R = {K1, K2, K3, ... Ki ..., Kn}. . That is, the decryption is performed by a key slightly different from the group encryption key K _G. Therefore, different decoding is performed for each user, which generates unique 3D data for each user. As a result, 3D data fingerprinted through decryption is provided to the user, which means that fingerprinting is integrated with decryption.

FIG. 7 is a diagram specifically illustrating a cognitive ability result according to the number of columns (l) in a two-dimensional aligned POS map. In FIG. 7, (a) is the original 3D model, (b) is the number of columns (ℓ) is 100, (c) is the number of columns (ℓ) is 50, and (d) is the number of columns (ℓ) When 10, (e) shows an encrypted 3D image when the number of columns (l) is two. As shown in FIG. 7, as the number of columns l in the POS map is decreased, the cognitive power of the fingerprinted model is significantly reduced. In order to maintain a partial level of partial encryption, it is expected that the number of columns in the POS map should be kept below 10.

The combined fingerprinting and decryption method of 3D data according to the present invention enables effective encryption of 3D data, and can also reduce transmission bandwidth by providing the same 3D file stream to all users. In addition, the combined fingerprinting and decryption method of 3D data according to the present invention includes classifying essential features into two or more subcategories, and encrypting encryption keys using a symmetric encryption group and a group encryption key, thereby allowing the same 3D data to be used. 3D data can be tracked for each user and can be integrated in the fingerprinting and decoding process. This enables the implementation of a form in which the decoding process and the fingerprinting are jointed.

Claims (2)

A) At the server side transmitting encrypted 3D data, A-1) in response to input of 3D data including geometric information and additional information, the geometric information as an Essential Feature (EF), wherein Separate additional information as a non-essential feature ("NEF") and divide the essential feature into at least two sub categories, Core Feature ("CF") and Basic Feature ("BF"). ) And generating a one-dimensionally arranged Polygon Object Set ("POS") based on the geometric information belonging to the subcategory, A-2) Generating a POS map by two-dimensionally aligning a polygon object set (POS), A-3) sampling data to be applied for encryption from each row of the POS map, A-4) encryption algorithm Through the arm of the sampled data Perform encryption, wherein the Core Feature (CF) is encrypted by a symmetry encryption key (K _S ), and the Basic Feature (BF) is a group encryption key (group). encrypting using an encryption key, K _G ), and A-5) partially encrypted 3D data by combining the partially encrypted geometric information obtained in the above step A-4) with the additional information of the step A-1). Creating a file stream and transmitting it to a plurality of users, and B) In each user terminal, the received 3D data file stream is decrypted and displayed on a user screen. When performing decryption, the core feature (CF) is a symmetry encryption key, K _S ), wherein the basic feature is unique to each user terminal with a decryption key Ki (where Ki belongs to K _R inferred from the group encryption key, K _R = {K 1, K 2, K 3,. ..., Ki ..., Kn}. The method according to claim 1, wherein when the essential features are classified into subcategories, they are classified by random sampling.

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