CN110765472B - A Location Privacy Protection Method Based on Blockchain and Distributed Storage - Google Patents

Abstract

The invention discloses a location privacy protection method based on a block chain and distributed storage, which comprises the following steps: dividing a user query request into a plurality of data segments, and storing the plurality of data segments and user identification data by using a distributed storage network; randomly selecting one of the servers as a noise server, acquiring data segments positioned in other storage servers according to the user identification data to obtain a complete query request, and performing noise on the query request; all the position service providers together establish a alliance chain, and simultaneously establish an intelligent contract on the alliance chain; a user obtains a key pair comprising a public key and a private key through an encryption algorithm, and the public key is used for registering on a alliance chain; and the user selects a position service provider corresponding to the query request on the alliance chain, the noisy query request is sent to the selected position service provider, and the position service provider provides position service for the user according to the query request.

Description

A Location Privacy Protection Method Based on Blockchain and Distributed Storage

technical field

The invention relates to the technical field of privacy protection, in particular to a location privacy protection method based on blockchain and distributed storage.

Background technique

With the continuous development of mobile communication technology and the continuous popularization of smart products such as mobile phones and tablets, location-based services (Location-Based Service, LBS) have been widely used in e-commerce, health care, and mobile social networking. An essential part of everyday life. LBS is to obtain the location information (geographical coordinates, or geodetic coordinates) of mobile terminal users through the radio communication network (such as GSM network, CDMA network) or external positioning method (such as GPS) of the telecom mobile operator, supported by the geographic information system platform It provides users with value-added services including point-of-interest inquiry, advertisement push and entertainment games. While location-based services bring great convenience to life, they also pose potential dangers to users' personal privacy. LBS has the user's location information and query content, and the attacker can infer the user's personal privacy information through the user's submitted location, query content and combined with their own background knowledge. As users pay more attention to personal privacy, location privacy protection methods have also been extensively studied.

Traditional location privacy protection methods mainly include fake location, location K-anonymity, and encryption methods. The fake location method means that when a user sends a query, a fake location is generated according to a certain strategy to send the query. The location K-anonymity method is to blur the user's spatial location information to achieve the purpose of privacy protection by sending a query request together with other K-1 user locations. Spatial encryption uses some kind of encryption protocol to realize the protection of user identity and location. None of the above three privacy protection models can provide an effective and strict method to prove their privacy level. Therefore, in 2006, Dwork et al. proposed a stricter definition of provable privacy, that is, differential privacy protection method. The differential privacy protection method does not need to consider any possible background knowledge owned by the attacker, and it can achieve a data protection effect that does not have a significant impact on the output result after a certain record is inserted or deleted in the data set.

LBS privacy protection technology is generally realized through three system structures: centralized, distributed and hybrid. Among them, both centralized and hybrid methods require the participation of third-party anonymous servers. A completely trusted third-party anonymous server does not exist in real life. Once the third-party anonymous server becomes untrustworthy, the user's location privacy will be leaked. Therefore, it is very important to design effective privacy protection methods to protect users' personal privacy.

Contents of the invention

The purpose of the present invention is to provide a location privacy protection method based on blockchain and distributed storage to solve the semi-trusted problem of third-party anonymous servers in the location privacy protection process.

In order to achieve the above tasks, the present invention adopts the following technical solutions:

A location privacy protection method based on blockchain and distributed storage, including:

Dividing the user query request into multiple data segments, storing the multiple data segments and user identification data with a distributed storage network;

Among the plurality of servers storing the plurality of data segments, one of the servers is randomly selected as a noise adding server, on the noise adding server, the data segments located in other storage servers are obtained according to the user identification data to obtain a complete query request, and Noise the query request;

All location service providers jointly create a consortium chain and create a smart contract on the consortium chain;

The user obtains a key pair including a public key and a private key through an encryption algorithm, and uses the public key to register on the alliance chain;

The user selects the location service provider corresponding to the query request on the alliance chain, and sends the noise-added query request to the selected location service provider, and the location service provider provides location service to the user according to the query request.

Further, the smart contract is that when the location service provider provides the user with location service, the user automatically pays the cryptocurrency to the location service provider;

After using the public key to register on the alliance chain, it also includes:

Users need to deposit a certain amount of cryptocurrency in the alliance chain in advance;

After the location service provider provides the location service to the user according to the query request, it also includes:

The smart contract automatically runs the user to pay the location service provider in cryptocurrency.

Further, said adding noise to the query request includes:

First generate random noise that obeys the Laplace distribution, and add the noise to the query request. The calculation method is as follows:

Qu'=Qu+Laplace(ΔF/ε)

Among them, Qu' is the query request after adding noise, Laplace(ΔF/ε) represents the noise satisfying the Laplace distribution, ε represents the differential privacy budget of the Laplace noise distribution algorithm, and ΔF represents the differential privacy global sensitivity of the Laplace noise distribution algorithm.

Further, the user query request is divided into multiple data segments, and the distributed storage network is used to store the multiple data segments and user identification data, expressed as:

Divide the query request Qu into {(Qu1,ID),(Qu2,ID),..(QuN,ID)}, a total of N data segments, in each data segment (Quj,ID), Quj represents the jth data Segment, j=1, 2, ..., N, ID is user identification data such as user name; correspondingly, use N servers in the distributed storage network to respectively store the N data segments.

Further, the random selection of one of the servers as the noise-adding server, on the noise-adding server, according to the user identification data, obtains the data segment located in other storage servers to obtain a complete query request, including:

For the N servers that store the N data segments, randomly select the i∈N server as the noise adding server, in this server, find the stored data segment (Qui, ID) according to the ID, and then in other N- One server queries other N-1 data segments according to the ID, and combines these data segments on the noise adding server to obtain a query request Qu.

Compared with the prior art, the present invention has the following advantages and beneficial effects:

The existing location privacy protection system structure has certain untrustworthy problems and requires too high computing power and storage space. The present invention adopts the system architecture of blockchain and distributed storage server cooperation to have the following advantages:

1. Solve the semi-trusted problem of a single third-party anonymous server, and does not require the client to have powerful computing power and storage space.

2. Using the differential privacy protection method, there is no need to consider any possible background knowledge owned by the attacker, and it is proved by strict mathematical derivation that the degree of privacy protection is higher.

3. The establishment of the alliance chain makes the user's transaction information only visible to the creator of the alliance chain, that is, the service provider, and the user's query request is less likely to be leaked. Based on the pseudo-anonymity of the blockchain, the public key is used as the user's account information. The real identity of the user is also difficult to discover.

Description of drawings

Fig. 1 is a schematic flow chart of the method of the present invention.

Detailed ways

Location-based services provide users with great convenience in their daily lives. For example, they need to use location-based services in the process of inquiring about take-out at the current location through a mobile phone's take-out app, or using navigation software for navigation. The present invention proposes a location privacy protection method based on blockchain and distributed storage, which solves the semi-trusted problem of third-party anonymous servers in the location privacy protection process.

Method of the present invention mainly is divided into two stages, and concrete steps are as follows:

1. Distributed storage stage

S11, the user's query request Qu is divided into multiple data segments, expressed as: Qu={(x, y), Con}; the multiple data segments and user identification data are stored in a distributed storage network; user identification data Refers to the user ID, etc.

Wherein: (x, y) is the longitude and latitude coordinates of the user, and Con is the query content of the user; the splitting method of the query request is equal-length splitting or random splitting.

For example, the query request Qu is divided into {(Qu1, ID), (Qu2, ID), ... (QuN, ID)} a total of N data segments, in each data segment (Quj, ID), Quj represents the jth data segments, j=1, 2, ..., N, ID is user identification data such as user name; correspondingly, N servers in the distributed storage network are used to respectively store the N data segments.

Distributed storage is to disperse and store data on multiple independent servers. Dividing the query content into several data segments and storing them in different servers with a distributed storage network is to prevent attackers from attacking one of the servers and obtain complete user information.

S12. Among the multiple servers storing the multiple data segments in the distributed network, randomly select one of the servers as the noise-adding server, and acquire the data segments located in other storage servers on the noise-adding server according to the user identification data to obtain To complete the query request Qu, add noise to the query request Qu on the noise adding server.

For example, for the N servers that store the N data segments, randomly select the i∈N server as the noise adding server, and in this server, find the stored data segments (Qui, ID ), and then query other N-1 data segments according to the ID on other N-1 servers, and combine these data segments on the noise adding server to obtain a query request Qu.

Randomly selecting a server as a noise adding server to obtain a complete request is to add noise to the user request. If adding noise directly to each data segment will cause a lot of computing overhead, the purpose of adding noise is to prevent the location service provider from obtaining the real location. It is a process of anonymizing user information, so denoising is not required, and the query request after adding noise is directly sent by the user to the location service provider on the alliance chain.

Adding noise to the query request on the adding noise server; specifically:

First generate random noise that obeys the Laplace distribution, and add the noise to the query request. The calculation method is as follows:

Qu'=Qu+Laplace(ΔF/ε)

Among them, Qu' is the query request after adding noise, Laplace(ΔF/ε) represents the noise that satisfies the Laplace distribution, ε represents the differential privacy budget of the Laplace noise publishing algorithm, ΔF represents the differential privacy global sensitivity of the Laplace noise publishing algorithm, and the global Sensitivity represents the change in the output of the algorithm when any data record in the dataset is changed.

2. Alliance chain transaction stage

S21, all location service providers jointly create a consortium chain, and at the same time create a smart contract on the consortium chain; the smart contract is that when the location service provider provides the user with location service, the user automatically pays currency to the location service provider.

Consortium chain: only for members of a specific group and limited third parties, multiple pre-selected nodes are internally designated as bookkeepers, the generation of each block is jointly decided by all pre-selected nodes, and other access nodes can participate in transactions. But without asking about the bookkeeping process, other third parties can make limited inquiries through the open API of the blockchain.

Smart Contract: A set of promises defined in digital form, including an agreement by which parties to the contract can enforce those promises. From a program point of view, a smart contract is a program language programmed on the blockchain, which triggers relevant operations when certain specified conditions are met.

The establishment of the alliance chain makes the user's transaction information only visible to the creator of the alliance chain, that is, the service provider, and the user's query request is less likely to be leaked.

S22. The user obtains a key pair including a public key and a private key through an encryption algorithm, and uses the public key to register on the alliance chain. The user needs to deposit a certain amount of cryptocurrency in the alliance chain in advance.

In this step, the public key (Public Key) and the private key (Private Key) are a key pair obtained through an encryption algorithm (that is, a public key and a private key), and the public key is the public part of the key pair. The private key is a non-public part; the encryption algorithm can be a commonly used encryption algorithm such as RSA.

Based on the pseudo-anonymity of the blockchain, the public key is used as the user's account information, and the user's true identity is difficult to be discovered.

S23, the user selects the location service provider corresponding to the query request on the alliance chain, and sends the noise-added query request to the selected location service provider, and the location service provider provides location service to the user according to the query request, and the smart contract runs automatically Users pay cryptocurrency to location service providers.

The location service provider refers to the location service provider corresponding to the query request, such as querying food information around the current location, and the location service provider can choose Gaode Map, Meituan Waimai, Dianping, etc.

Application example: For a user A, it is necessary to query the available hotels near the current location through the mobile phone, use S11~S12 to add noise to the user's query request, and use S22 to generate an account information on the alliance chain. According to step S23, the user selects the hotel Tuan, a service provider, sends the query request after adding noise to Meituan, and Meituan displays the hotels that user A can stay near the location, and the smart contract runs immediately to pay the user to Meituan.

Claims (1)

1. A location privacy protection method based on block chain and distributed storage, characterized in that, comprising: Dividing the user query request into multiple data segments, storing the multiple data segments and user identification data with a distributed storage network; Among the plurality of servers storing the plurality of data segments, one of the servers is randomly selected as a noise adding server, on the noise adding server, the data segments located in other storage servers are obtained according to the user identification data to obtain a complete query request, and Noise the query request; All location service providers jointly create a consortium chain and create a smart contract on the consortium chain; The user obtains a key pair including a public key and a private key through an encryption algorithm, and uses the public key to register on the alliance chain; The user selects the location service provider corresponding to the query request on the alliance chain, and sends the noise-added query request to the selected location service provider, and the location service provider provides location service to the user according to the query request; The smart contract is that when the location service provider provides the user with the location service, the user automatically pays the encrypted currency to the location service provider; After using the public key to register on the alliance chain, it also includes: Users need to deposit a certain amount of cryptocurrency in the alliance chain in advance; After the location service provider provides the location service to the user according to the query request, it also includes: The smart contract automatically runs the user to pay the cryptocurrency to the location service provider; The noise adding to the query request includes: First generate random noise that obeys the Laplace distribution, and add the noise to the query request. The calculation method is as follows: Qu'=Qu+Laplace(ΔF/ε) Among them, Qu' is the query request after adding noise, Laplace(ΔF/ε) represents the noise that satisfies the Laplace distribution, ε represents the differential privacy budget of the Laplace noise publishing algorithm, and ΔF represents the differential privacy global sensitivity of the Laplace noise publishing algorithm; The described user query request is divided into multiple data segments, and the distributed storage network is used to store the multiple data segments and user identification data, expressed as: Divide the query request Qu into {(Qu1,ID),(Qu2,ID),..(QuN,ID)}, a total of N data segments, in each data segment (Quj,ID), Quj represents the jth data Segment, j=1,2,...,N, ID is user identification data; Correspondingly, store described N data segments respectively with N servers in the distributed storage network; The random selection of one of the servers as the noise-adding server, on the noise-adding server, obtains the data segment located in other storage servers according to the user identification data to obtain a complete query request, including: For the N servers that store the N data segments, randomly select the i∈N server as the noise adding server, in this server, find the stored data segment (Qui, ID) according to the ID, and then in other N- One server queries other N-1 data segments according to the ID, and combines these data segments on the noise adding server to obtain a query request Qu.

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