CN117972652A

CN117972652A - Transaction method based on vector geographic data

Info

Publication number: CN117972652A
Application number: CN202311071877.5A
Authority: CN
Inventors: 任娜; 陈泽锋; 张�浩; 赵萍; 王丹; 杨峰; 王忠芳; 朱长青; 胡宇宸; 顾进杰; 汪贺延
Original assignee: PROVINCIAL GEOMATICS CENTRE OF JIANGSU; Nanjing Normal University
Current assignee: PROVINCIAL GEOMATICS CENTRE OF JIANGSU; Nanjing Normal University
Priority date: 2023-08-24
Filing date: 2023-08-24
Publication date: 2024-05-03

Abstract

The invention provides a transaction method based on vector geographic data, which comprises the steps of acquiring a transaction request of a buyer, triggering watermark generation and embedding sub-protocols based on the transaction request of the buyer, obtaining watermark information based on the protocols, embedding the watermark information into the vector geographic data to be transacted, and obtaining vector geographic numbers containing the watermark information; acquiring a transaction key, encrypting vector geographic data containing watermark information by a buyer based on the key, and decrypting the vector geographic data containing watermark information by a seller based on the key; if the seller, and/or the original owner of the data, discovers infringing data and/or the buyer denies his own infringement, an infringement tracking sub-and arbitration protocol is triggered, based on which the infringer identity is queried and/or the job of arbitrating the complete traceability and/or auxiliary arbitrators of all associated transactions. The method meets the trusted transaction and traceability requirements of the vector geographic data in a multistage transaction network scene.

Description

Transaction method based on vector geographic data

Technical Field

The invention relates to the technical field of digital watermarking, and particularly provides a transaction method based on vector geographic data.

Background

Vector geographic data is an important result of national surveying and mapping geographic infrastructure construction and geospatial scientific research, is widely used in a plurality of fields such as smart city, digital twinning, automatic driving and the like, and plays an important role in economic and social development. With the rapid development of internet technology, the distribution, transmission and transaction of vector geographic data become more convenient and faster, but the problems of data theft and illegal distribution piracy are also very easy to occur. Therefore, it is necessary to study copyrights that effectively protect vector geographic data.

The digital watermarking technology is an effective method for solving the problem of illegal piracy of geographic data, and can determine copyright attribution and trace infringement when piracy is generated by hiding specific information in a data carrier and tightly combining the specific information with carrier data. Robust watermarking algorithms for vector geographic data have achieved relatively great results for years, and researchers have proposed a series of algorithms with excellent performance. However, in the practical application process, the geographic data face a mutual trust problem in the process of transaction circulation. Malicious copyright parties can forge a honest purchaser of copyright information, and a dishonest purchaser can repudiate own infringement, which makes the digital watermarking technology difficult to be directly used as a solution of copyright protection. Therefore, based on the digital watermarking technology, the safe and fair transaction protocol is used as the supplement of the digital watermarking technology, which is the key for realizing copyright protection in the data transaction process.

At present, many research results about digital watermarking protocols exist, but most schemes in the current literature are designed based on the architecture of trusted third parties. Under this architecture, it is difficult for traditional third parties to provide sustainable efficient services for the transactional distribution of mass data. Meanwhile, the copyright protection strength depends on the credibility of a third party, and a dishonest third party can collude with any party of the transaction, frame the other party. In addition, most of the existing digital watermarking protocols are oriented to single unidirectional point-to-point transaction scenes, and the situation of multi-level transaction of vector geographic data in the transaction process is rarely considered, so that the complete traceability of the data in the process of multiple transaction flows is difficult to ensure.

The blockchain technology that has been popular in recent years provides a viable approach to solving the above problems, because of its decentralised, non-tamperable, traceable and programmable nature, trust relationships can be established between mutually untrusted transaction participants. Meets the requirements of the digital watermark protocol in the transaction process. The blockchain technology is introduced into the digital watermark protocol, so that risks caused by complex flow, high cost, information leakage and data centralized storage of the existing watermark protocol can be eliminated.

In summary, there are many achievements in copyright protection for vector geographic data, but there is still risk of collusion under the condition that a third party is not trusted and complete traceability of vector geographic data under a multi-level distribution network is not considered. For example, a vector map digital watermarking algorithm for improving DFT and QR codes and Blind DIGITAL WATERMARKING Algorithm against Projection Transformation for Vector Geographic Data mentioned in ZHOU Q, REN, ZHU C mentioned in Xi Xu and the like are poor in object attack resistance.

Accordingly, there is a need in the art for a new vector geographic data based transaction approach to address the above-described problems.

Disclosure of Invention

The present invention is proposed to overcome the above-mentioned drawbacks, and to solve or at least partially solve the problem of meeting the trusted transaction and traceability requirements of vector geographic data in a multi-level transaction network scenario.

The invention discloses a transaction method based on vector geographic data, which comprises the following steps:

Acquiring a transaction request of a buyer, triggering a watermark generation and embedding sub-protocol based on the transaction request of the buyer, generating unique private information based on the watermark generation and embedding sub-protocol, binding the private information with data information to be purchased by the buyer, and authenticating on a blockchain platform to obtain purchase information authentication;

Acquiring transaction information of a buyer and transaction information of a seller, and acquiring transaction information authentication based on the transaction information of the buyer, the transaction information of the seller and a blockchain platform;

Based on the transaction information authentication returned by the seller, watermark information is obtained, the watermark information is embedded into vector geographic data to be transacted, and vector geographic data containing the watermark information is obtained;

based on a return address of transaction information successfully returned by seller authentication and a blockchain platform, acquiring a transaction key, encrypting vector geographic data containing watermark information by a buyer based on the key, and decrypting the vector geographic data containing watermark information by the seller based on the key;

if the seller, and/or the original owner of the data, discovers infringing data and/or the buyer denies his own infringement, an infringement tracking sub-and arbitration protocol is triggered, based on which the infringer identity is queried and/or the work of arbitrating the complete traceability and/or auxiliary arbitrators of all associated transactions is performed.

In one technical scheme of the transaction method based on the vector geographic data, the transaction information authentication is obtained based on the transaction information of the buyer, the transaction information of the seller and the blockchain platform;

and respectively sending the transaction information of the buyer and the transaction information of the seller to a blockchain platform, and authenticating in the blockchain platform to obtain transaction information authentication.

In one technical scheme of the transaction method based on the vector geographic data, the obtaining watermark information based on the transaction information authentication returned by the seller includes:

Acquiring a return address of the transaction information authentication returned by the seller, and embedding the watermark information into vector geographic data to be transacted; and encoding based on the return address of the transaction information authentication returned by the seller to obtain watermark information.

In one technical scheme of the transaction method based on the vector geographic data, acquiring a transaction key based on a return address and a blockchain platform of transaction information successfully returned by seller authentication, encrypting the vector geographic data containing watermark information by a buyer based on the key, and decrypting the vector geographic data containing watermark information by the seller based on the key comprises:

Inquiring the blockchain platform based on the return address of the transaction information successfully returned by the seller authentication, acquiring random numbers generated by both transaction sides from the inquiring result to generate a secret key, encrypting vector geographic data containing watermark information based on the secret key, and transmitting the encrypted content to the buyer; and initiating inquiry to the blockchain based on the transaction information authentication address returned by the successful buyer authentication, taking out the secret key from the inquiry result, and decrypting based on the secret key to obtain vector geographic data containing watermark information.

In one technical solution of the transaction method based on vector geographic data, if the seller and/or the original owner of the data find infringement data and/or the buyer denies own infringement, triggering an infringement tracking sub-and an arbitration protocol, and querying the identity of the infringer and/or arbitrating the complete traceability and/or auxiliary arbitrators of all related transactions based on the infringement tracking sub-and the arbitration protocol includes:

if the seller discovers infringement data, triggering an infringement tracking sub and arbitration protocol, extracting a digital watermark of the pirated data by the seller, analyzing a transaction authentication address from the extracted watermark information, initiating inquiry to a blockchain platform to obtain authentication information of the transaction, and tracking the identity of the buyer by combining a data transaction record of the seller and pursuing responsibility for the buyer;

If the initial owner of the data finds infringement data, although the data transaction record of the initial owner of the data does not have the purchase information of the buyer, the initial owner of the data can recursively initiate transaction inquiry to the blockchain according to the inquired authentication information to obtain all pre-associated transactions of the current transaction, and the source of the data is proved;

If the buyer of the overtaking party denies the infringement behavior of the buyer, the infringement tracking sub and the arbitration protocol are triggered to initiate arbitration, the arbitrator arbitrates by verifying evidence submitted by the seller of the overtaking party or the original owner of the data, and the buyer cannot deny the arbitration result because the transaction information is authenticated on the blockchain;

In one technical scheme of the transaction method based on the vector geographic data, embedding the watermark information into the vector geographic data to be transacted to obtain the vector geographic data containing the watermark information comprises the following steps:

constructing a new Cartesian coordinate system based on the vector geographic data;

acquiring a coordinate set in the new Cartesian coordinate system;

acquiring embedded data based on coordinate values in a coordinate set and the watermark information;

And processing the embedded data to obtain vector geographic data containing watermark information.

In one technical scheme of the transaction method based on the vector geographic data, constructing a new Cartesian coordinate system based on the vector geographic data comprises:

extracting a point set constituting a vector geographic element based on the vector geographic data;

simplifying the vector geographic elements based on a DP algorithm to obtain a feature point set;

and constructing a minimum circumscribed rectangle according to the feature point set, constructing the minimum circumscribed rectangle based on the feature point set, and establishing a new Cartesian coordinate system.

In one technical scheme of the transaction method based on vector geographic data, the acquiring the coordinate set in the new cartesian coordinate system includes:

all vertices in the point set of the vector element are converted into a set of coordinates in a new cartesian coordinate system.

In one technical scheme of the transaction method based on vector geographic data, obtaining the embedded data based on the coordinate values in the coordinate set and the watermark information comprises:

carrying out maximum and minimum value normalization processing on the coordinate values in the coordinate set;

and establishing a watermark bit index, and embedding the watermark information into the coordinate set subjected to maximum and minimum value normalization processing to obtain embedded data.

In one technical scheme of the transaction method based on the vector geographic data, the processing of the embedded data to obtain the vector geographic data containing watermark information comprises the following steps:

Performing processing inverse normalization processing based on the embedded data to obtain relative coordinates; and converting the relative coordinates into original coordinates, and recombining the original coordinates into a coordinate set to obtain vector geographic data containing watermark information.

The technical scheme provided by the invention has at least one or more of the following beneficial effects: the invention introduces the blockchain platform to replace a trusted third party, constructs watermark generation and embedding sub-protocol, infringement tracking sub-and arbitration protocol based on blockchain authentication, and meets the trusted transaction and traceability requirements of vector geographic data in a multistage transaction network scene.

Furthermore, a traceable transaction record frame in the intelligent contract based on the blockchain design is used for transaction authentication service, so that chain storage and quick query of associated transaction information in the blockchain are realized.

Drawings

The present disclosure will become more readily understood with reference to the accompanying drawings. As will be readily appreciated by those skilled in the art: the drawings are for illustrative purposes only and are not intended to limit the scope of the present invention. Moreover, like numerals in the figures are used to designate like parts, wherein:

FIG. 1 is a flow chart illustrating the main steps of a transaction method based on vector geographic data according to one embodiment of the invention;

FIG. 2 is a schematic diagram of a quick traceability of an associated transaction according to one embodiment of the invention;

FIG. 3 is a schematic diagram of a transaction chain logic structure according to one embodiment of the invention;

FIG. 4 is a schematic diagram of watermark generation and embedding sub-protocol interactions, according to one embodiment of the invention;

FIG. 5 is a schematic diagram of infringement tracking and infringement tracking sub-and arbitration protocol interactions, in accordance with one embodiment of the invention;

fig. 6 is a schematic diagram of a watermark information generation flow according to an embodiment of the invention;

FIG. 7 is a simplified schematic diagram of a DP algorithm according to one embodiment of this invention;

FIG. 8 is a schematic diagram of a new Cartesian coordinate system construction according to an embodiment of the present invention;

FIG. 9 is a coordinate value transformation diagram according to one embodiment of the invention;

fig. 10 is a flowchart of a watermark extraction method according to one embodiment of the invention;

FIG. 11 is a schematic diagram of purchase information authentication according to one embodiment of the invention;

FIG. 12 is a transaction information authentication schematic according to one embodiment of the invention;

FIG. 13 is a watermark information generation and embedding flow diagram according to one embodiment of the invention;

FIG. 14 is a data transaction flow diagram according to one embodiment of the invention;

FIG. 15 is a data authentication information recursion query according to one embodiment of the present invention;

FIG. 16 is a schematic diagram of experimental data according to one embodiment of the invention;

FIG. 17 is a schematic diagram of watermark information generation in accordance with an embodiment of the invention;

FIG. 18 is a schematic diagram of a geometric attack according to one embodiment of the present invention;

FIG. 19 is a schematic view of an object attack according to one embodiment of the invention;

fig. 20 is a diagram of a robustness contrast experiment according to one embodiment of the invention.

Detailed Description

Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.

Some terms related to the present invention will be explained first.

Buyer (Buyer, B): a user purchasing data.

Seller (Seller, S): the owner of the data.

Digital certificate authority (CERTIFICATE AUTHORITY, CA): registering and issuing a digital certificate for the buyer and the seller participating in the transaction, and being used for identity authentication in the transaction process of the buyer and the seller.

Blockchain platform (BC): the decentralization platform is used for recording and authenticating data transaction and has copyright certification and traceability characteristics.

Cutting party (Judger, J): and when copyright disputes occur, the medium cubes participating in copyright arbitration.

Example 1

Referring to fig. 1, fig. 1 is a schematic flow chart of main steps of a transaction method based on vector geographic data according to an embodiment of the present invention. As shown in fig. 1, the transaction method based on vector geographic data in the embodiment of the invention mainly includes:

In this embodiment, the current information to be transacted is authenticated on the blockchain platform BC, and watermark information embedded in transaction data is used as the node address for transaction information authentication. Wherein the transaction authentication is completed by the parties involved in the transaction, and the information for authenticating the transaction comprises the private information of the buyer. As the blockchain platform has high public trust and once the node content is in the uplink and can not be tampered, the authentication result is used as watermark information, so that not only can the seller be prevented from forging the watermark information, but also the buyer can be prevented from repudiating the watermark information, thereby protecting the rights and interests of both parties of the transaction.

In this embodiment, the blocks in the blockchain network are arranged according to the time sequence of block generation to form the blockchain, so in the conventional blockchain transaction authentication application, the authentication information of the related transaction does not have connectivity, and when the vector geographic data-oriented multi-level transaction scenario is adopted, the query of the related transaction always needs to traverse the whole blockchain network to search, thereby consuming a great amount of resources. Therefore, an improvement is needed for the block chain structure, so that the related transaction can be quickly queried, and quick tracing is realized. As shown in fig. 2, in the data logic layer, an attribute field of a hash address of a pre-transaction node is added in a node of the associated transaction to realize a link between physically non-adjacent nodes, thereby realizing a quick link of the associated transaction information in the application layer.

Taking transaction 1- & gt transaction 2- & gt transaction 4 as an example in the related transaction, transaction 4 is the latest transaction, and transaction 1 is the initial transaction. The logical structure of the transaction certificates of the three transactions is shown in fig. 3, and the front transaction hash attribute of the transaction 4 and the front transaction hash attribute of the transaction 2 record the node hash addresses of the transaction 2 and the transaction 1 respectively, and the front transaction hash attribute of the transaction 1 is 0. When the corresponding intelligent contract inquires certain node information, the source can be traced rapidly through the address of the front transaction node recorded in the transaction certificate. The block structure is designed to realize quick tracing when the malicious data user infringes through linking the related transactions, and provide reliable evidence for the infringed. Compared with the traditional blockchain copyright protection application, the computing efficiency is greatly improved under the condition that the physical structure of the blockchain bottom layer is not greatly modified.

Furthermore, the error correction coding method (ErrorCorrectingCode) performs self-error correction coding on the digital watermark information before embedding the digital watermark information into carrier data, so that the watermark information is correctly decoded under the condition of incomplete extraction of the digital watermark. Defining the encoding operation as Encode (…) and the decoding operation as Decode (…), the self-error correction encoding and decoding for message m can be expressed as:

m＝Decode(Encode(m)) (3.2)

In this embodiment, the block chain platform BC implements the decentralised authentication and inquiry service, and the transaction information and the watermark information are bound and authenticated without relying on a trusted third party. The transaction information is stored in the blockchain node in a logical data structure formed by a transaction chain, wherein the node address of the last associated transaction is recorded, so that the quick tracing of the transaction is realized.

In one embodiment, obtaining transaction information authentication includes based on the buyer's transaction information, the seller's transaction information, a blockchain platform;

In one embodiment, based on the transaction information authentication returned by the seller, obtaining watermark information includes:

In this embodiment, as shown in fig. 6, the node address of the blockchain is used as watermark information to embed transaction data, and the node address returned by the blockchain is a hash value in a string format. The QR code is one of the most widely applied codes at present, and has the characteristics of large storage capacity, small occupied space and strong error correction capability. QR encoding is conducted on the Hash character string to serve as watermark information.

In one embodiment, based on the return address of the transaction information successfully returned by the seller authentication, the blockchain platform, the transaction key is obtained, the buyer encrypts the vector geographic data containing the watermark information based on the key, and the seller decrypts the vector geographic data containing the watermark information based on the key comprises:

In this embodiment, the transaction data is encrypted, the availability of the transaction data is destroyed, and if and only after the transaction information is successfully authenticated on the blockchain platform BC, the buyer can obtain the decryption key to recover the availability, so that the security of the transaction data is ensured. Meanwhile, the blockchain platform BC operates the corresponding intelligent contract to generate a random number so as to generate an encryption key, so that the seller is prevented from forging the encryption key, and the buyer rights and interests are ensured.

In one embodiment, if the seller, and/or the original owner of the data, discovers infringing data and/or the buyer denies his own infringement, then triggering an infringement tracking sub-and arbitration protocol based on which the operation of querying the identity of the infringer and/or arbitrating the complete traceability and/or auxiliary arbitrators of all associated transactions includes:

If the seller discovers infringement data, triggering an infringement tracking sub and arbitration protocol, extracting a digital watermark of the pirated data by the seller, analyzing a transaction authentication address from the extracted watermark information, initiating inquiry to a blockchain platform to obtain authentication information of the transaction, and tracking the identity of the buyer by combining a data transaction record of the seller and pursuing responsibility for the buyer; in this embodiment, after the seller discovers the suspected infringement data, the seller can autonomously call a digital watermark extraction algorithm to extract watermark information in the data, and then initiate a query to the blockchain platform BC according to the watermark information, thereby revealing the identity of the infringer.

If the buyer of the overtaking party denies the infringement action of the buyer, the infringement tracking sub and the arbitration protocol are triggered to initiate arbitration, and the arbitrator arbitrates by verifying evidence submitted by the seller of the overtaking party or the original owner of the data, because the transaction information is authenticated on the blockchain, the buyer cannot deny the arbitration result.

In this embodiment, the arbitrator J is allowed to query the blockchain platform BC by itself according to the evidence submitted by the seller S, and since the watermark information is already bound with the transaction information and recorded on the blockchain platform during the transaction, the arbitrator J can directly determine the consistency of the submitted evidence and the query result due to the non-tamperable characteristic thereof, thereby arbitrating the dispute.

As shown in fig. 5, the specific process after triggering the infringement tracking sub-and the arbitration protocol includes:

(1) After the seller S finds the data X ' suspected of infringing, a digital watermark extraction algorithm is invoked to extract watermark information W ', then self-correcting decoding is performed on the watermark information W ' to extract a blockchain node address h ' =decode (W ') storing transaction authentication information, and then a query is initiated to the blockchain BC according to h.

(2) The block chain platform BC queries in the block network according to the node address h' provided by the seller S to obtain the transaction information authenticated on the BC by the data and the node address of the pre-associated transaction. S can judge the infringement behavior of the buyer B through the information, and in addition, S can trace the source upwards through a transaction chain to pull all transactions, so that complete tracing of all data related transactions is realized.

(3) If the buyer B denies his own infringement, the seller S encapsulates the data X ' into m ₃ = { X ', W ', h ' } according to the traceability result in the infringement tracking sub-protocol, and submits the m ₃ = { X ', W ', h ' } as evidence to the arbitrator J.

(4) After receiving the evidence, the arbitrator J first runs a watermark detection algorithm to verify whether the watermark information extracted in X 'is consistent with W' submitted by the seller S. If the two types of data are consistent, the next arbitration is carried out, and if the two types of data are inconsistent, the judgment that B does not form infringement is carried out.

(5) The secondary cutting party J performs self-error correction decoding on the extracted watermark information W ', and verifies whether the decoding result is consistent with h' submitted by the seller S. If the two types of data are consistent, the next arbitration is carried out, and if the two types of data are inconsistent, the judgment that B does not form infringement is carried out.

(6) And the arbitrator J initiates a query to the blockchain platform BC according to h', so as to obtain current node transaction information res= { ID _S,ID_B,ID_X,h,W_S,W_B … }, in the transaction chain. And then judging the transaction information in the query result to arbitrate the current dispute, wherein the buyer cannot deny the arbitration result because the authentication information stored on the blockchain is authenticated by the buyers and sellers together.

In one embodiment, embedding the watermark information into the vector geographic data to be transacted to obtain the vector geographic data containing the watermark information includes:

acquiring a coordinate set in the new Cartesian coordinate system;

In one embodiment, constructing a new Cartesian coordinate system based on vector geographic data comprises:

In this embodiment, before the vector geographic elements are processed, vertices in the elements may be reasonably simplified, so as to simplify redundant data and reduce subsequent computation complexity. At the same time, compression attacks can be resisted. The vector element feature points are extracted by using a Douglas-Peucker (DP) algorithm so as to improve the stability of the subsequent watermark embedding operation. A complex polyline as shown in fig. 7 (a), and a process of simplifying extraction of feature points using a DP algorithm is shown in fig. 7 (b), fig. 7 (c), and fig. 7 (d).

And extracting the characteristic points from the vector elements by using a DP algorithm to obtain a characteristic point set. And calculating the minimum circumscribed rectangle of the point set by extracting the outermost convex hull of the characteristic point set. There are various methods for extracting the convex hull of the outermost layer of the point set, and in this embodiment, the convex hull is calculated by using a gram-Scan algorithm, and then the minimum circumscribed rectangle of the convex hull is calculated. After the minimum bounding rectangle of the feature point set is calculated, the left lower corner vertex p ₀＝(x₀,y₀ of the bounding rectangle can be known. And (3) taking p ₀ as an original point, taking the long side l of the rectangle as the positive direction of the X axis and the short side as the positive direction of the Y axis, and establishing a Cartesian coordinate system. The coordinate system construction diagram is shown in fig. 8.

In one embodiment, obtaining the set of coordinates in the new Cartesian coordinate system comprises:

In this embodiment, as shown in fig. 9, p ₀ is the origin of the new coordinate system, θ is the minimum angle θ required for the new coordinate system X axis to rotate to the old coordinate system X axis, and if the counterclockwise rotation is negative and the clockwise rotation is positive, θ∈ [ -90 °,90 ° ]. Each point p _i＝(x_i,y_i) in the point set is converted to a relative coordinate p' _i＝(x'_i,y'_i) by:

x'_i＝(x_i-x₀)*cosθ+(y_i-y₀)*sinθ (3.8)

y'_i＝-(x_i-x₀)*sinθ+(y_i-y₀)*cosθ (3.9)

in one embodiment, obtaining the embedded data based on the coordinate values in the coordinate set and the watermark information includes:

In one embodiment, processing the embedded data to obtain vector geographic data containing watermark information includes:

The specific process of watermark embedding of the vector geographic elements is as follows:

Step 1: the point set record= { p ₁,p₂,…,p_n } constituting the vector geographic element is extracted. And (3) operating a DP algorithm to simplify the vector geographic elements and obtain a feature point set. And constructing a minimum circumscribed rectangle according to the feature point set, and establishing a new Cartesian coordinate system based on the minimum circumscribed rectangle.

Step 2: the point set of the vector geographic elements, record= { p ₁,p₂,…,p_n } is converted into a coordinate set record '= { p' ₁,p'₂,…,p'_n } in a new coordinate system, and an X-axis coordinate set X '= { X' ₁,x'₂,…,x'_n } and a Y-axis coordinate set Y '= { Y' ₁,y'₂,…,y'_n } are obtained.

Step 3: maximum and minimum normalization is respectively carried out on coordinate values in the coordinate value sets X ' and Y ', and X "= { X" ₁,x"₂,…,x"_n } and Y ' = { Y "₁,y"₂,…,y"_n }:

Where X '_min、x'_max represents the minimum and maximum values, respectively, in coordinate set X' and Y '_min、y'_max represents the minimum and maximum values, respectively, in coordinate set Y'.

Step 4: establishing a watermark bit index, and embedding binary watermark information W= { W ₁,w₂,…,w_n } needing to be embedded with vector geographic data into k valid bits of X 'and Y':

In the watermark embedding process, in order to ensure the correct extraction of watermark information, the embedding operation of the maximum value and the minimum value of the coordinate value of the outer convex hull and the normalized coordinate is skipped.

Step 5: and carrying out inverse normalization processing on the embedded data:

Step 6: and converting the relative coordinates after watermark embedding into original coordinates, and recombining the original coordinates into a coordinate set to obtain the vector geographic elements containing watermark information.

The watermark extraction method is as shown in fig. 10, firstly extracting the coordinate set of the vector elements, then calculating the minimum circumscribed rectangle thereof, establishing a cartesian coordinate system based on the rectangle, and converting the coordinate values into relative coordinates. And normalizing the relative coordinates, and recovering watermark information from the normalized result according to the valid bit value and the watermark bit index.

As shown in fig. 4, the specific process after triggering the watermark generation and embedding sub-protocol includes: (1) The seller and the buyer each generate an asymmetric encryption public-private key pair, and then send the public keys to a digital certificate authority CA for submitting registrations, for which the CA issues digital certificates Cert (S), cert (B) and Cert (C), respectively. The buyer firstly initiates a transaction to the seller to propose purchase data X, and the two parties mutually send digital certificates to verify identities and transfer public keys;

(2) The buyer generates a piece of unique private information W _B, authenticates the information on a block chain platform BC, and the BC operates an intelligent contract to store the private information on the block chain and returns an authentication address h _B;

(3) The seller S generates a random number N _S, encapsulates the transaction information m ₁＝{h,ID_S,ID_B,ID_X,W_S,N_S, … and generates a digital signature (m ₁) therefor, where W _S is the copyright information of S. Simultaneously, buyer B generates a random number N _B, encapsulates transaction information m ₂＝{ID_S,ID_B,ID_X,W_B,h_B,N_B, … and generates a digital signature (m ₂) for it, wherein W _B is B's private information;

(4) The buyer and the seller respectively send m ₁ and m ₂ to the blockchain platform BC to request transaction information authentication, the BC firstly verifies the correctness and the integrity of the signature verification messages of m ₁ and m ₂, and then an intelligent contract is operated to verify whether the transaction information from the two parties is correct or not. If the verification is passed, the new node records all the information { m ₁∪m₂ } of the current transaction, and then returns an authentication success message containing the authentication information node address h. Otherwise, sending a message of authentication failure;

(5) After receiving the authentication success message, the seller verifies the authentication result according to the returned node address h. Then, the received block chain link point address h is subjected to self-error correction coding to obtain watermark information W=Encode (h), and a watermark embedding algorithm is operated to embed W into transaction data to obtain And generates a one-time key for encrypting data based on the two random numbers, and then encrypts the transaction data X using the key to obtain En (X).

(6) The seller retrieves the random numbers N _S and N _B from the authentication information, generates a one-time key for encrypting the data based on the two random numbers, and then encrypts the transaction data including the watermark using the keyObtain/>Ciphertext data containing watermark information is then subjected toAnd digital signature/>And transmitted to the buyer.

(7) The buyer receives the authentication success message, verifies the authentication result according to the returned node address h and takes out the random numbers N _S and N _B, and also generates a key for decrypting the data based on the random numbers. If the delivered ciphertext data is received, the priori evidence is based on the integrity and correctness of the digital signature ciphertext data sent by the seller, and then the data is decrypted by using the secret key to obtain the transaction data containing the watermark

Experiment and analysis

In order to realize the simulation experiment of the watermark protocol, the open-source-based network security communication framework OpenSSL is used for realizing the communication of the transaction participants of the digital watermark protocol, and an RSA asymmetric encryption algorithm and an SHA-256 digest algorithm are used as a scheme for generating and verifying message digests and digital signatures; using an AES symmetric encryption algorithm as a data communication encryption scheme; related intelligent contract services are developed based on the ant open alliance chain as a blockchain platform.

(1) Watermark information generation and embedding

After the buyer Bob makes a request to purchase the data of the su state water area from the seller Alice, the watermark generation and embedding sub-protocol is triggered. Bob generates random unique private information, binds it with the information of the purchase data, and authenticates on the blockchain platform. The authentication result is shown in fig. 11.

The seller Alice encapsulates the transaction information m _S of the seller, and the transaction information includes the authentication address of the front transaction. The buyer Bob encapsulates the buyer's transaction information m _B. Both sides respectively send m _S and m _B to the blockchain platform, and the blockchain platform runs the verification and the uplink certification operation of the intelligent contract execution information. The authentication result is shown in fig. 12.

And (3) the seller Alice carries out QR coding on the returned transaction information authentication address to serve as watermark information, operates a digital watermark algorithm and embeds the watermark information into transaction data. A flow chart of watermark information generation and embedding is shown in fig. 13.

(2) Data transaction

The seller Alice uses the transaction information authentication address returned by successful authentication to initiate inquiry to the blockchain, takes out the random numbers generated by the two parties of the transaction from the inquiry result to generate an AES key, encrypts vector geographic data containing watermark information, and sends the result to the buyer Bob.

And the buyer Bob initiates inquiry to the blockchain by using the transaction information authentication address returned by successful authentication, takes out random numbers generated by both transaction sides from the inquiry result to generate an AES key, decrypts the received transaction data ciphertext, and obtains vector geographic data containing watermark information. A data transaction flow diagram is shown in fig. 14.

(3) Infringement tracking and arbitration

If Bob infringes maliciously, pirated data is spread on the Internet. If Alice finds infringement data, an infringement tracking sub-protocol is triggered. Alice extracts the digital watermark of pirated data, analyzes the transaction authentication address from the extracted watermark information, initiates inquiry to the blockchain platform to obtain the authentication information of the transaction, and then tracks Bob identity by combining with own data transaction record and pursues responsibility for the Bob identity. If the original owner Someone of the data finds infringing data, although the data transaction record of Someone does not have Bob's purchase information, someone may recursively initiate a transaction query to the blockchain based on the queried authentication information, obtain all pre-associated transactions for the current transaction, and thereby prove the source of the data. A schematic of a recursive query is shown in fig. 15.

If the obedient Bob denies the infringement of the entity, the arbitration sub-protocol is triggered to initiate arbitration, and the arbitrator performs arbitration by verifying evidence submitted by the obedient Alice or Someone, because the transaction information is authenticated on the blockchain, bob cannot deny the arbitration result.

Based on the scheme, the following problems are solved:

infringement tracking problem: malicious buyer B may attempt to forge false identities to initiate a purchase request to deceive the seller, thereby escaping responsibility after infringing. In this agreement, however, buyer B has only two possible approaches: 1. forging its own digital certificate. Since the digital certificate authority CA is assumed to be trusted, the B-forged digital certificate is not passed at the beginning of the verification of the protocol. 2. False identity information is provided when a transaction authentication request is sent to the blockchain platform BC, and the authentication information is forged. But the BC receives not only the information of B but also the transaction authentication information from the seller S, where the transaction authentication information of the seller includes the identity information from the digital certificate of B, and the BC runs the corresponding intelligent contract to verify the authentication information sent by the two parties. Therefore, if the identity information is forged by the B, the information verification is inconsistent, so that the transaction authentication is failed, and the transaction is terminated.

Consumer interest problems are that a malicious seller S can utilize the identity of B to construct a false transaction after obtaining the digital certificate of buyer B, thereby forging infringement data to trap B. In practice, such an action cannot be successful, and during the execution of the protocol, the digital certificate is used only for the identity verification at the beginning of the transaction to communicate securely with the data based on the public key cryptosystem. During the transaction, buyer B generates a piece of private information, signs it with the private key, and then authenticates the private information and the signature on the blockchain. The seller S cannot practically forge and authenticate the piece of private information on the blockchain without the buyer' S private key.

The binding problem is that the seller S ever makes a real transaction with the buyer B, the malicious seller S uses the real watermark in the transaction, embeds it in other data and counterfeits the innocent buyer of the transaction. During the transaction, the buyer generates unique private information which is authenticated in advance on the blockchain platform and is only bound with the current transaction. When the transaction information is authenticated, the authentication content contains the authentication address of the buyer private information, so that the binding relation of the transaction and the private information in one-to-one correspondence is realized. Therefore, even if the malicious seller S embeds the existing real watermark into other data, the arbitrator finds that the carrier data is inconsistent with the transaction data in the arbitration phase, so that the seller S is determined to be malicious frame.

Collusion problem: the lead-in blockchain platform takes the role of transaction authentication instead of a third party. The blockchain has the characteristics of decentralization and untampered information on the chain, the intelligent contract automatically verifies the transaction information and uploads the transaction information for verification, and the intelligent contract content is public and transparent. Obviously, collusion problems can be prevented.

Piracy disputes: malicious buyer B denies his own infringement when it is responsible for the infringement. In this case, the seller S will raise arbitration, submitting watermark information extracted from the infringing product and the block address storing watermark authentication information to the arbitrator J. The arbitrator J runs an arbitration sub-protocol to verify evidence, due to the transparent and non-tamperable nature of the disclosure of blockchain certificates, and transaction authentication information stored in the blockchain platform is generated jointly by both parties. Therefore, B cannot deny the evidence, and thus cannot deny its infringement.

Watermarking algorithm experiment

(1) Introduction to experimental data

Vector geographic data of two element types, namely line type and plane type, are used as experimental data. Road data and water area data in su state city are shown in fig. 16 (a) and 16 (b), respectively. The data details are shown in table 1.

Table 1 experimental data information table

(2) Introduction of watermark information

A character string is formed by 256-bit Hash values and is used for simulating a block chain transaction information authentication address, QR codes are carried out on the character string, a 45-bit and 45-bit QR code is generated to serve as watermark information, and a coding result is shown in fig. 17.

1.1.1 Imperceptibility experiments

Imperceptibility of a digital watermark refers to the degree to which the change in the carrier data itself can be perceived after the watermark is embedded in the carrier data. Quantitative evaluation of watermark imperceptibility is mainly performed by means of mean square error (MeanSquareError, MSE) and maximum error (MaxError) to count and evaluate the coordinate change degree of carrier data before and after embedding watermark. The smaller the MSE and the maximum error value, the smaller the data change before and after embedding the watermark, and the better the imperceptibility of the watermark algorithm. The calculation results of the MSE values and MaxError values before and after embedding the digital watermark into the experimental data are shown in table 2, and as can be seen from table 2, the MSE values and MaxError values before and after embedding the watermark are smaller, which indicates that the watermark algorithm has better imperceptibility.

Table 2 indices MSE and MaxError before and after watermark embedding

Geometric attack experiment

Geometric attack experiments select common geometric operations of vector geographic data: translation (Translation), scaling (Scale), rotation (Rotate). Translation, rotation and scaling experiments of different degrees are respectively designed to evaluate the resistance of the watermark algorithm to geometric attacks. And using a normalized correlation coefficient (NormalizedCorrelation, NC) as a robustness evaluation index, wherein the closer the result value obtained by calculating the normalized correlation coefficient is to 1, the better the quality of the extracted watermark is, and the stronger the robustness of the watermark is. Taking water area data as an example, a schematic diagram of a geometric attack against the water area data is shown in fig. 18.

(1) Translation attack

The experiment translates the original data by 0.1 °, 0.01 ° and 0.01 ° along the x-or y-axis direction, and extracts watermark information from the translated data. The experimental results are shown in table 3.

TABLE 3 translation attack experimental results

As can be seen from table 3, for any translation distance, the NC value of the extracted watermark is always 1.00, because the translation attack does not destroy the relative distance between the coordinates of the vector geographic data, and therefore the method is completely resistant to the translation attack.

(2) Spin attack

The original point is taken as a rotation center point in the experiment, and the original data are respectively rotated clockwise at angles of 30 degrees, 60 degrees, 90 degrees, 120 degrees and 210 degrees. The experimental results are shown in table 4.

Table 4 rotation attack experimental results table

As can be seen from table 4, after the experimental data is rotated, the NC value of the watermark extracted is always 1.00, because the minimum bounding rectangle according to the feature point set of the vector element in the algorithm establishes a coordinate system, and the minimum bounding rectangle has a rotation-invariant property, and when the vector element is rotated, the minimum bounding rectangle rotates along with the rotation of the vector element, so that the cartesian coordinate system established by the bounding rectangle also rotates, and therefore, the relative coordinate value of the vertex converted according to the cartesian coordinate system does not change due to the rotation of the element. Therefore, the algorithm can be completely resistant to rotation attacks.

(3) Equal-ratio scaling attack

In the experiment, the original point is used as a scaling point, and the original data are scaled in equal proportions by scaling scales of 0.3, 0.8, 1.5 and 2.0 respectively. The experimental results are shown in table 5.

Table 5 table of results of the equal-ratio scaling attack experiment

As can be seen from table 5, for the equal-ratio scaling transformation of the experimental data, the NC value of the extracted watermark is always 1.00, because the watermark information in the algorithm is finally embedded into the relative coordinate values subjected to the normalization processing, the normalization processing can effectively resist the scaling attack. From experiments, the algorithm is completely resistant to the scaling attack.

Subject attack experiment

The object attack experiment mainly uses vector geographic elements forming vector geographic data as operation objects, and attacks by changing elements in a vector geographic data element set. For example, a portion of the vector elements are randomly added or deleted. By adding additional vector geographic elements to the vector geographic data, which is equivalent to introducing noise into the whole vector element set, interference can be generated in the process of extracting watermarks from other elements containing watermark information. And deleting the vector geographic elements containing watermark information means destroying the watermark information embedded in the data. And respectively designing element addition and deletion experiments with different degrees to evaluate the resistance of the watermarking algorithm of the embodiment to the attack of the object. The normalized correlation coefficient is used as a robustness evaluation index. A schematic of the object attack is shown in fig. 19.

The experiment uses water area data as an experimental object, and carries out the operations of randomly adding and randomly deleting 20%, 40%, 60%, 80% and 90% of vector geographic elements respectively. And the NC value between the extracted watermark and the original watermark after attack is calculated to quantitatively evaluate the watermark quality, and meanwhile, the watermark quality is verified in a mode of scanning and analyzing the QR code, and whether the extracted watermark information is effective or not is verified. The experimental results are shown in table 6.

Table 6 results table of subject attack experiments

As can be seen from the experimental results in table 6, the object attack transformation was performed on the experimental data. When the proportion of the added elements is between 20% and 90%, the data can extract watermark information which is higher than an empirical threshold value of 0.75, and the extracted QR code can be normally decoded to obtain an authentication address of the transaction on the blockchain. When the deletion element ratio is between 20% and 90%, the data can still extract watermark information images which are higher than the empirical threshold value of 0.75. However, when the deletion rate reaches 90%, although the NC value of the extracted watermark information reaches 0.82, the QR code is no longer available at this time, and the final result of the extraction cannot be decoded normally. Since the watermark embedding operation is performed element by element, and each watermark bit is in fact redundantly embedded. Thus, when the deleted information or added noise is at a certain limit, the watermark can be extracted correctly.

Comparative experiments

In order to verify the robustness of the watermark algorithm of the chapter, a vector map digital watermark algorithm for improving DFT and QR codes is marked as a prior art 1,Blind Digital Watermarking Algorithm against Projection Transformation for Vector Geographic Data and is marked as a prior art 2, and an algorithm in the prior art 1 and the prior art 2 is selected as a comparison algorithm to carry out comparison experiments, respectively marked as an algorithm 1 and an algorithm 2, and rotation, equal-ratio scaling, object addition and object deletion attacks with different intensities are respectively carried out, wherein the comparison experiments are shown in figure 20.

As shown in fig. 20 (a), the present chapter algorithm selects different embedded domains with rotation invariance from algorithm 1 and algorithm 2 to embed watermarks, so that NC values of the three are maintained at about 1.00 under rotation attack, and rotation attack can be completely resisted.

As shown in fig. 20 (b), the NC value of algorithm 1 is about 0.5 at any scaling, indicating that it is completely unable to resist an equal-scale attack; the NC value of the method and the NC of the algorithm 2 is maintained to be about 1.00 under different scaling ratios, and the method and the algorithm can resist equal-ratio scaling attack.

As shown in fig. 20 (c), first, algorithm 1 cannot resist the attack of adding or deleting elements, and both algorithm 2 and the present chapter algorithm have the capability of resisting the attack of adding or deleting elements. With the increase of the number of elements, watermark information extracted by the chapter algorithm and the algorithm 2 can be interfered, and when the increase proportion reaches 90%, NC values of the two algorithms can still be kept above a threshold value of 0.75. With the increase of the number of the element deletion, the NC values of the chapter algorithm and the algorithm 2 still keep above the threshold, when the element deletion proportion reaches 90%, the NC value of the algorithm 2 is reduced to be below the threshold, and the NC value of the method still keeps above the threshold. Therefore, the method has better resistance to object attack than algorithm 1 and algorithm 2.

Aiming at the problems of low security, insufficient credibility and difficult tracing under a multi-level transaction network caused by the dependence of the current digital watermarking protocol on a credible third party, the block chain is introduced into the digital watermarking protocol, and the digital watermarking protocol combined with the block chain is designed. The protocol stores the related information of the transaction on the blockchain, so that the transaction tracing under a multi-level transaction network is realized, and the security and the credibility of the watermark protocol are improved. On the basis, a vector geographic data robust watermarking algorithm meeting the watermarking protocol requirements is provided, and the algorithm ensures the robustness of the watermark by utilizing a Douglas-Praeparata algorithm and a relative coordinate system strategy. Experiments show that the watermark algorithm has better robustness, and the watermark protocol can meet the safe and reliable transaction of vector geographic data.

Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.

Claims

1. A method of trading based on vector geographic data, comprising:

2. The method of claim 1, wherein obtaining transaction information authentication based on the buyer's transaction information, the seller's transaction information, a blockchain platform comprises;

3. The method of claim 1, wherein obtaining watermark information based on the transaction information authentication returned by the seller comprises:

4. The method of claim 1, wherein obtaining a transaction key based on a return address of transaction information successfully returned by the seller authentication, the blockchain platform, the buyer encrypting the vector geographic data including watermark information based on the key, the seller decrypting the vector geographic data including watermark information based on the key comprises:

5. The method of claim 1, wherein if the seller, and/or the original owner of the data, discovers infringing data and/or the buyer denies his/her infringement, triggering an infringement tracking sub-and arbitration protocol based on which the operation of querying the identity of the infringer and/or arbitrating the complete traceability and/or auxiliary arbitrators of all associated transactions comprises:

6. The method according to any of claims 1-5, wherein embedding the watermark information in the vector geographic data to be transacted to obtain vector geographic data containing watermark information comprises:

acquiring a coordinate set in the new Cartesian coordinate system;

7. The method of claim 6, wherein constructing a new cartesian coordinate system based on vector geographic data comprises:

8. The method of claim 7, wherein obtaining the set of coordinates in the new cartesian coordinate system comprises:

9. The method of claim 8, wherein obtaining embedded data based on coordinate values in a set of coordinates, the watermark information comprises:

10. The method of claim 9, wherein processing the embedded data to obtain vector geographic data comprising watermark information comprises: