WO2022048107A1

WO2022048107A1 - Multi-dimensional statistical analysis system and method for sales amounts of seller users on e-commerce platform

Info

Publication number: WO2022048107A1
Application number: PCT/CN2021/074760
Authority: WO
Inventors: 沈华; 王胜男; 张明武; 张�浩
Original assignee: 湖北工业大学
Priority date: 2020-09-02
Filing date: 2021-02-02
Publication date: 2022-03-10
Also published as: CN112163227B; CN112163227A

Abstract

Disclosed in the present invention are a multi-dimensional statistical analysis system and method for sales amounts of seller users on an e-commerce platform. The system comprises one e-commerce platform service party (ECS), n cloud servers (CSs), and m sellers. The method comprises the steps of system initialization, block compression processing for the sales amounts of the sellers, and generation of corresponding secret shares; the CSs aggregate the secret shares; and the ECS obtains multidimensional statistical analysis results. The present invention avoids using encryption and decryption operations having high calculation cost to obtain the statistical analysis results of the sales amounts of various commodities under the condition of not revealing the sales amounts of the sellers, and implements lightweight multi-dimensional statistical analysis for the sales amounts of the sellers having privacy protection. According to the obtained statistical values, the ECS can analyze and discover the distribution of the sales amounts of the various commodities on the platform. The present invention effectively solves the problem of how to efficiently perform statistical analysis on the sales conditions of the various commodities under the condition of not revealing the privacy of the seller users.

Description

一种电商平台卖家用户销售额多维统计分析***及方法A multi-dimensional statistical analysis system and method for sales of sellers and users of e-commerce platforms

本申请要求于2020年09月02日提交中国专利局、申请号为202010910937.8、发明名称为“一种电商平台卖家用户销售额多维统计分析***及方法”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。This application claims the priority of the Chinese patent application filed on September 2, 2020, with the application number of 202010910937.8 and the invention titled "A system and method for multi-dimensional statistical analysis of sales of sellers and users of e-commerce platforms", all of which are The contents are incorporated herein by reference.

技术领域technical field

本发明属于信息安全技术领域，具体涉及一种具有隐私保护的轻量级电商平台卖家用户销售额多维统计分析***及方法。The invention belongs to the technical field of information security, and in particular relates to a system and method for multi-dimensional statistical analysis of sales of sellers and users of a lightweight e-commerce platform with privacy protection.

背景技术Background technique

在电商平台领域中，为了掌握市场的最新情况，电商平台需要了解平台卖家用户各类商品的销售情况。通过对平台卖家用户各类商品销售额进行统计分析，平台可以了解平台卖家用户整体销售情况，了解各类商品销售情况的季节性规律、地域性规律，以及预测市场未来的变化趋势，有助于其制定相关平台政策引导卖家用户合理配置各类商品的库存比例。但卖家用户各类商品的销售额属于他们的隐私数据，他们不希望泄漏给其他任何人或机构。因此，研究如何在***漏卖家各类商品销售额的情况下对这些数据进行统计分析是一个重要课题。In the field of e-commerce platforms, in order to keep abreast of the latest market situation, e-commerce platforms need to know the sales situation of various commodities of platform sellers and users. Through the statistical analysis of the sales of various commodities of the platform sellers and users, the platform can understand the overall sales of the platform sellers and users, understand the seasonal and regional laws of the sales of various commodities, and predict the future trends of the market, which is helpful for It formulates relevant platform policies to guide sellers and users to reasonably configure the inventory ratio of various commodities. However, the sales of various products of sellers and users belong to their private data, and they do not want to leak it to any other person or institution. Therefore, it is an important topic to study how to perform statistical analysis on these data without revealing the sales of various commodities of sellers.

发明内容SUMMARY OF THE INVENTION

为了解决上述的技术问题，本发明提供了一种具有隐私保护的轻量级电商平台卖家用户销售额多维统计分析***及方法，解决当前商品买卖过程中的隐私泄露问题。In order to solve the above technical problems, the present invention provides a lightweight e-commerce platform seller user sales multi-dimensional statistical analysis system and method with privacy protection, which solves the problem of privacy leakage in the current commodity buying and selling process.

为实现上述目的，本发明提供了如下方案：For achieving the above object, the present invention provides the following scheme:

一种电商平台卖家用户销售额多维统计分析方法，应用于电商平台卖家用户销售额多维统计分析***；其特征在于：所述***包括1个平台服务方ECS，n个云服务器CS和m个卖家；将第i个云服务器表示为CS _i，i＝1,2,…,n；将第j个卖家表示为U _j，j＝1,2,…,m；卖家U _j销售K种不同类商品；将卖家U _j的销售额数据记为A _j＝(a _j,1,a _j,2,…,a _j,K)，其中a _j,k是A _j的一个分量，它表示卖家U _j的第k种商品的销售额，其中k＝1,2,…,K； A method for multi-dimensional statistical analysis of sales of sellers and users on an e-commerce platform, which is applied to a multi-dimensional statistical analysis system for sales of sellers and users on an e-commerce platform; characterized in that the system includes a platform service party ECS, n cloud servers CS and m The i-th cloud server is represented as CS _i , i=1,2,…,n; the j-th seller is represented as U _j , j=1,2,…,m; the seller U _j sells K species Different types of commodities; record the sales data of seller U _j as A _j = ( _aj,1 , _aj,2 ,..., _aj,K ), where a _j,k is a component of A _j , it represents The sales of the k-th commodity of seller U _j , where k=1,2,...,K;

所述方法包括以下步骤：The method includes the following steps:

步骤1：***初始化；Step 1: System initialization;

步骤1.1：电商平台服务方ECS选择合适的整数T和R作为***参数，其中***参数T用在对卖家用户销售额的分块处理中，***参数R用在对块内销售额数据的压缩处理中，参数T是决定了每一个分块的大小，块大小会影响***性能，块大小越大通信开销越小但计算开销会增大，因此参数T的选择需要权衡各方面的性能开销来选定，参数R的选择需要满足其值要大于每块中每种商品销售额之和，假设一段时间内每种商品销售额不超过W，那么R需要满足R>TW；Step 1.1: The e-commerce platform service provider ECS selects the appropriate integers T and R as system parameters, where the system parameter T is used in the block processing of the sales of sellers and users, and the system parameter R is used to compress the sales data in the block. In the processing, the parameter T determines the size of each block, and the block size will affect the system performance. The larger the block size, the smaller the communication overhead but the higher the computational overhead. Therefore, the selection of the parameter T needs to weigh the performance overhead of various aspects. Selected, the selection of parameter R needs to satisfy that its value is greater than the sum of the sales of each commodity in each block. Assuming that the sales of each commodity in a period of time does not exceed W, then R needs to satisfy R>TW;

步骤1.2：电商平台服务方ECS向卖家发送***参数T和R；Step 1.2: The e-commerce platform service provider ECS sends the system parameters T and R to the seller;

步骤2：将卖家销售额数据进行分块压缩处理，并生成对应秘密份额；Step 2: Compress the seller's sales data in blocks and generate corresponding secret shares;

步骤3：云服务器聚合秘密份额；Step 3: The cloud server aggregates the secret share;

步骤4：电商平台服务方ECS获取多维统计分析结果。Step 4: The ECS, the service provider of the e-commerce platform, obtains multi-dimensional statistical analysis results.

根据本发明提供的具体实施例，本发明公开了以下技术效果：According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

(1)本发明解决了如何在***漏电商平台卖家用户的各类商品销售额的情况下对这些数据进行统计分析的问题，具有非常好的实际应用价值。(1) The present invention solves the problem of how to perform statistical analysis on these data without revealing the sales of various commodities of the sellers and users of the e-commerce platform, and has very good practical application value.

(2)为了在***漏卖家用户的各类商品销售额的情况下对这些数据进行统计分析，本发明采用了分块压缩的思想和(t,n)门限秘密共享的方法，将卖家的各类商品销售额分块压缩后，利用秘密共享技术针对压缩处理得到的值为每个云服务器产生相应的秘密分额，每个云服务器将所有用户相同块的压缩值对应的秘密分额进行聚合处理，最后电商平台服务方收到任意t个云服务器发送的聚合处理后的秘密分额后就可以恢复和提取出所有卖家用户各类商品销售额的总和。(2) In order to perform statistical analysis on these data without leaking the sales of various commodities of sellers and users, the present invention adopts the idea of block compression and the method of (t,n) threshold secret sharing, After the sales of similar commodities are compressed in blocks, the secret sharing technology is used to generate a corresponding secret share for each cloud server for the value obtained by the compression process, and each cloud server aggregates the secret share corresponding to the compressed value of the same block of all users. Finally, after receiving the aggregated secret share sent by any t cloud servers, the e-commerce platform service party can recover and extract the total sales of various commodities of all sellers and users.

(3)本发明避免使用了计算开销、存储开销和通信开销大的加密方案实现隐私保护，采用了计算开销小的秘密共享技术，同时使用的分块压缩和聚合技术减少了存储和通信开销，实现了轻量级的隐私保护电商平台卖家用户销售额多维统计分析方法。(3) The present invention avoids using an encryption scheme with large computational overhead, storage overhead and communication overhead to achieve privacy protection, adopts a secret sharing technology with small computational overhead, and simultaneously uses block compression and aggregation technology to reduce storage and communication overhead, A lightweight privacy-preserving e-commerce platform seller user sales multi-dimensional statistical analysis method is implemented.

说明书附图Instruction drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

图1为本发明实施例一提供的电商平台卖家用户销售额多维统计分析方法的***框架图；FIG. 1 is a system frame diagram of a multi-dimensional statistical analysis method for sales of sellers and users of e-commerce platforms provided by Embodiment 1 of the present invention;

图2为本发明实施例一提供的电商平台卖家用户销售额多维统计分析方法的控制流程图。FIG. 2 is a control flow chart of a method for multi-dimensional statistical analysis of sales of sellers and users of an e-commerce platform according to Embodiment 1 of the present invention.

具体实施方式detailed description

下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

本发明提供了一种具有隐私保护的轻量级电商平台卖家用户销售额多维统计分析***及方法，解决当前商品买卖过程中的隐私泄露问题。The invention provides a multi-dimensional statistical analysis system and method for the sales of sellers and users of a lightweight e-commerce platform with privacy protection, and solves the problem of privacy leakage in the current commodity buying and selling process.

为使本发明的上述目的、特征和优点能够更加明显易懂，下面结合附图和具体实施方式对本发明作进一步详细的说明。In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

实施例一：Example 1:

请参阅图1，本发明实施例提供了一种具有隐私保护的轻量级电商平台卖家用户销售额多维统计分析***，该***包括1个电商平台服务方ECS、n个云服务器和m个卖家用户；Referring to FIG. 1, an embodiment of the present invention provides a lightweight e-commerce platform seller user sales multi-dimensional statistical analysis system with privacy protection, the system includes an e-commerce platform server ECS, n cloud servers and m seller users;

将第i个云服务器表示为CS _i，i＝1,2,…,n； Denote the i-th cloud server as CS _i , i=1,2,...,n;

将第j个卖家表示为U _j，j＝1,2,…,m；卖家U _j销售K种不同类商品；将卖家Uj的销售额数据记为A _j＝(a _j,1,a _j,2,…,a _j,K)，其中a _j,k是A _j的一个分量，它表示卖家U _j的第k种商品的销售额，其中k＝1,2,…,K。 Denote the jth seller as U _j , j=1,2,...,m; seller U _j sells K kinds of commodities; denote the sales data of seller Uj as A _j =(a _j,1 ,a _{j ,2} ,...,a _j,K ), where a _j,k is a component of A _j , which represents the sales of the kth commodity of seller U _j , where k=1,2,...,K.

针对上述***，本发明实施例还提供了一种具有隐私保护的轻量级电商平台卖家用户销售额多维统计分析方法，如图2所示，本发明实施例提供的方法包括以下步骤：Aiming at the above system, the embodiment of the present invention also provides a method for multi-dimensional statistical analysis of sales of sellers and users on a lightweight e-commerce platform with privacy protection. As shown in FIG. 2 , the method provided by the embodiment of the present invention includes the following steps:

步骤1：***初始化。Step 1: System initialization.

请见图2，***初始化具体包括以下子步骤：See Figure 2, the system initialization includes the following sub-steps:

步骤1.1：电商平台服务方ECS选择合适的整数T和R作为***参数，其中***参数T用在对卖家用户销售额的分块处理中，***参数R 用在对块内销售额数据的压缩处理中；Step 1.1: The e-commerce platform service provider ECS selects appropriate integers T and R as system parameters, where the system parameter T is used in the block processing of the sales of sellers and users, and the system parameter R is used in the compression of the sales data in the block Processing;

参数T是步骤2中需要用到的分块参数，决定了每一个分块的大小，块大小会影响***性能，块大小越大通信开销越小但计算开销会增大，因此参数T的选择需要权衡各方面的性能开销来选定，参数R是步骤2中需要用到的压缩参数，它的选择需要满足其值要大于每块中每种商品销售额之和，假设一段时间内每种商品销售额不超过W，那么R需要满足R>TW；The parameter T is the block parameter that needs to be used in step 2, which determines the size of each block. The block size will affect the system performance. The larger the block size, the smaller the communication overhead but the higher the computational overhead. Therefore, the choice of parameter T It is necessary to weigh the performance costs of various aspects to select. The parameter R is the compression parameter that needs to be used in step 2. Its selection needs to satisfy that its value is greater than the sum of the sales of each commodity in each block. If the sales of goods do not exceed W, then R needs to satisfy R>TW;

步骤1.2：电商平台服务方ECS向卖家发送***参数T和R。Step 1.2: The e-commerce platform service provider ECS sends the system parameters T and R to the seller.

步骤2：卖家销售额数据的分块压缩处理及对应秘密份额的生成。其具体实现包括以下子步骤：Step 2: Block compression processing of seller sales data and generation of corresponding secret shares. Its specific implementation includes the following sub-steps:

步骤2.1：卖家U _j将其K种商品的销售额数据A _j＝(a _j,1,a _j,2,…,a _j,K)按T个分量为一组的规则进行分块处理，商品种类数K是否是块大小T的整数倍并不影响整个处理过程；唯一的区别是，如果商品种类数K不是块大小T的整数倍，则最后一个块不足T个分量，否则最后一块也包含T个分量；为了便于描述，不失一般性，假设商品种类数K是块大小T的整数倍；卖家U _j将A _j＝(a _j,1,a _j,2,…,a _j,K)划分为

组，其中第一组为SA _j,1＝(a _j,1,a _j,2,…,a _j,T)，第二组为SA _j,2＝(a _j,T+1,a _j,T+2,…,a _j,T+T)，第三组为SA _j,3＝(a _j,2T+1,a _j,2T+2,…,a _j,2T+T)，依次类推。 Step 2.1: The seller U _j divides the sales data A _j = (a _j,1 ,a _j,2 ,...,a _j,K ) of its K kinds of commodities according to the rule of T components as a group, Whether the number of commodity types K is an integer multiple of the block size T does not affect the entire processing process; the only difference is that if the number of commodity types K is not an integer multiple of the block size T, the last block is less than T components, otherwise the last block is also Contains T components; for the convenience of description, without loss of generality, it is assumed that the number of commodity types K is an integer multiple of the block size T; seller U _j will A _j = (a _j,1 ,a _j,2 ,...,a _{j, K} ) is divided into

groups, where the first group is SA _j,1 =(a _j,1 ,a _j,2 ,...,a _j,T ), and the second group is SA _j,2 =(a _j,T+1 ,a _{j ,T+2} ,…,a _j,T+T ), the third group is SA _j,3 =(a _j,2T+1 ,a _j,2T+2 ,…,a _j,2T+T ), in turn analogy.

步骤2.2：卖家U _j根据获得的***参数R将第l组销售额SA _j,l＝(a _j,(l-1)T+1,a _j,(l-1)T+2,…,a _j,(l-1)T+T)压缩为

S _j,l是一个整数，其中

Step 2.2: According to the obtained system parameter R, the seller U _{j calculates} the sales of the lth group SA _j,l =( _aj,(l-1)T+1 , _aj,(l-1)T+2 ,..., a _j,(l-1)T+T ) is compressed as

S _j,l is an integer, where

步骤2.3：卖家U _j采用(t，n)门限秘密共享方案为每个S _j,l生成n个秘密份额，分别表示为

其中

Step 2.3: The seller U _j uses the (t, n) threshold secret sharing scheme to generate n secret shares for each S _{j, l} , respectively expressed as

in

卖家U _j共产生了

个秘密份额：

Seller U _j produced a total of

A secret share:

本实施例中，卖家U _j采用Shamir(t，n)门限秘密共享方案为每个S _j,l生成n个秘密份额，分别表示为

其中

具体过程如下： In this embodiment, the seller U _j uses the Shamir(t,n) threshold secret sharing scheme to generate n secret shares for each S _j,l , which are respectively expressed as

in

The specific process is as follows:

针对S _j,l，卖家U _j构造一个t-1次多项式f _j,l(x)＝S _j,l+b _j,l,1x+b _j,l,2x ²+…+b _j,l,t-1x ^t-1，其中b _j,l,1、b _j,l,2、…、b _j,l,t-1是卖家U _j选的随机数，随后生成S _j,l的n个秘密份额

其中i＝1，2,…,n。 For S _j,l , seller U _j constructs a t-1 degree polynomial f _j,l (x)=S _j,l +b _j,l,1 x+b _j,l,2 x ² +...+b _{j ,l,t-1} x ^t-1 , where b _j,l,1 , b _j,l,2 ,...,b _j,l,t-1 are random numbers selected by seller U _j , and then generate S _j, n secret shares of _l

where i=1,2,...,n.

卖家U _j共产生了

个秘密份额： Seller U _j produced a total of

A secret share:

步骤2.4：卖家U _j将产生的S _jl的n个秘密份额向n个云服务器进行分发，卖家U _j将S _jl的秘密份额

发送给云服务器CS _i，其中

i＝1,2,…,n。 Step 2.4: The seller U _j distributes the generated n secret shares of S _jl to n cloud servers, and the seller U _j distributes the secret shares of S _jl

sent to the cloud server CS _i , where

i=1,2,...,n.

云服务器CS _i收到来自卖家U _j的

个秘密份额： Cloud server CS _i receives from seller U _j

A secret share:

一共收到来自m个卖家的

个秘密份额： A total of received from m sellers

A secret share:

步骤3，云服务器CS _i将每m个秘密份额

聚合为一个秘密份额，用符号

表示这个聚合得到的秘密份额，

实质上是所有卖家属于第l块的T类商品的销售额总和的压缩值

对应的一个秘密份额，其中

Step 3, the cloud server CS _i will share every m secret

Aggregate into a secret share, with the symbol

represents the secret share obtained by this aggregate,

Essentially the compressed value of the sum of the sales of all sellers belonging to the T category of products in block l

corresponds to a secret share, where

利用(t，n)门限秘密共享的同态性实现上述聚合，具体计算公式为：The above aggregation is realized by using the homomorphism of (t, n) threshold secret sharing, and the specific calculation formula is:

显然，

是聚合多项式f _l(x)当x＝i时的多项式值，f _l(x)的具体形式如下所示： Obviously,

is the polynomial value of the aggregate polynomial f _l (x) when x=i, and the specific form of f _l (x) is as follows:

根据Shamir(t,n)门限秘密共享方案中多项式的构造方法可知，

是

的一个秘密份额。 According to the construction method of the polynomial in the Shamir(t,n) threshold secret sharing scheme, it can be known that,

Yes

a secret share.

重复执行上述聚合操作

次，CS _i将

个秘密份额

压缩为

个秘密份额

其中

是

的一个秘密份额，

是

的一个秘密份额，…，

是

的一个秘密份额。 Repeat the above aggregation operation

times, CS _i will

secret share

compressed to

secret share

in

Yes

a secret share of

Yes

A secret share of,…,

Yes

a secret share.

步骤4，电商平台服务方ECS获取多维统计分析结果。其具体实现包括以下子步骤：In step 4, the ECS, the service provider of the e-commerce platform, obtains multi-dimensional statistical analysis results. Its specific implementation includes the following sub-steps:

步骤4.1：电商平台服务方ECS随机选择t个CS，让它们将其拥有的关于

的秘密份额发送给电商平台服务方ECS，假设ESC收到的关于

的t个秘密份额分别为

根据拉格拉日插值公式，ESC可以通过这t个秘密份额恢复多项式

从而，ESC可以获得

Step 4.1: ECS, the e-commerce platform service provider, randomly selects t CSs and asks them to use their own information about

The secret share is sent to the e-commerce platform service provider ECS, assuming that the

The t secret shares of

According to the Lagage interpolation formula, the ESC can recover the polynomial through these t secret shares

Thus, the ESC can obtain

电商平台服务方ECS重复执行上述过程共

次，可以恢复出所有卖家的所有

个块中的T种商品的销售额总和的压缩值

The e-commerce platform service provider ECS repeats the above process for a total of

times, you can restore all sellers'

Compressed value of the sum of sales of T items in blocks

步骤4.2：电商平台服务方ECS通过执行针对***参数R的T次取余操作和T-1次取整操作可以从压缩值

中提取出

具体过程如下： Step 4.2: ECS, the e-commerce platform service provider, can extract the compressed value from the compressed value by performing T remainder operations and T-1 rounding operations for the system parameter R.

extracted from

The specific process is as follows:

执行第1次

除以R取余，得到

Execute the 1st time

Divide by R and take the remainder, we get

执行第1次

除以R取整，并结果赋值给

得： Execute the 1st time

Divide by R to round, and assign the result to

have to:

执行第2次

除以R取余，得到

Execute the 2nd time

Divide by R and take the remainder, we get

执行第2次

除以R取整，并结果赋值给

得： Execute the 2nd time

Divide by R to round, and assign the result to

have to:

……

执行第T-1次

除以R取余，得到

Execute the T-1 time

Divide by R and take the remainder, we get

执行第T-1次

除以R取整，并结果赋值给

得： Execute the T-1 time

Divide by R to round, and assign the result to

have to:

执行第T次

除以R取余，得到

Execute the T time

Divide by R and take the remainder, we get

电商平台服务方ECS重复执行上述过程共

次，可以从压缩值

中提取出针对每种商品的所有卖家的销售额总和：

其中

表示m个卖家的第k种商品的销售总额，其中k＝1,2,…,K。 The e-commerce platform service provider ECS repeats the above process for a total of

times, the compressed value can be

Extract the sum of all sellers' sales for each item from:

in

Indicates the total sales of the k-th commodity of m sellers, where k=1,2,...,K.

本发明实施例有效地解决了如何在***漏卖家用户隐私的条件下高效地对卖家用户各种商品销售额统计分析的问题。本发明针对电商平台卖家用户销售额的具有隐私保护的统计分析提出的解决方法，该方法也可用于电商平台买家购买行为的具有隐私保护的统计分析，金融贸易领域中的商品进出口情况的具有隐私保护的分析，保险领域中的投保人投保习惯的具有隐私保护的分析，具有很高的实用性。The embodiments of the present invention effectively solve the problem of how to efficiently perform statistical analysis on the sales of various commodities of sellers and users without revealing the privacy of sellers and users. The present invention proposes a solution for the statistical analysis with privacy protection of the sales volume of sellers on the e-commerce platform, and the method can also be used for the statistical analysis of the purchase behavior of buyers on the e-commerce platform with privacy protection, and the import and export of commodities in the field of financial trade. The analysis of the situation with privacy protection and the analysis of the policyholder's insurance habits in the insurance field with privacy protection have high practicability.

应当理解的是，本说明书未详细阐述的部分均属于现有技术。It should be understood that the parts not described in detail in this specification belong to the prior art.

应当理解的是，上述针对较佳实施例的描述较为详细，并不能因此而认为是对本发明专利保护范围的限制，本领域的普通技术人员在本发明的启示下，在不脱离本发明权利要求所保护的范围情况下，还可以做出替换或变形，均落入本发明的保护范围之内，本发明的请求保护范围应以所附权利要求为准。It should be understood that the above description of the preferred embodiments is relatively detailed, and therefore should not be considered as a limitation on the protection scope of the patent of the present invention. In the case of the protection scope, substitutions or deformations can also be made, which all fall within the protection scope of the present invention, and the claimed protection scope of the present invention shall be subject to the appended claims.

提供以上实施例仅仅是为了描述本发明的目的，而并非要限制本发明的范围。本发明的范围由所附权利要求限定。不脱离本发明的精神和原理而做出的各种等同替换和修改，均应涵盖在本发明的范围之内。The above embodiments are provided for the purpose of describing the present invention only, and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims. Various equivalent replacements and modifications made without departing from the spirit and principle of the present invention should be included within the scope of the present invention.

Claims

一种电商平台卖家用户销售额多维统计分析方法，应用于电商平台卖家用户销售额多维统计分析***；其特征在于：所述***包括1个平台服务方ECS，n个云服务器CS和m个卖家；将第i个云服务器表示为CS _i，i＝1,2,…,n；将第j个卖家表示为U _j，j＝1,2,…,m；卖家U _j销售K种不同类商品；将卖家U _j的销售额数据记为A _j＝(a _j,1,a _j,2,…,a _j,K)，其中a _j,k是A _j的一个分量，它表示卖家U _j的第k种商品的销售额，其中k＝1,2,…,K； A method for multi-dimensional statistical analysis of sales of sellers and users on an e-commerce platform, which is applied to a multi-dimensional statistical analysis system for sales of sellers and users on an e-commerce platform; characterized in that the system includes a platform service party ECS, n cloud servers CS and m The i-th cloud server is represented as CS _i , i=1,2,…,n; the j-th seller is represented as U _j , j=1,2,…,m; the seller U _j sells K species Different types of commodities; record the sales data of seller U _j as A _j = ( _aj,1 , _aj,2 ,..., _aj,K ), where a _j,k is a component of A _j , it represents The sales of the k-th commodity of seller U _j , where k=1,2,...,K;

所述方法包括以下步骤：The method includes the following steps:

步骤1：***初始化；Step 1: System initialization;

步骤1.1：电商平台服务方ECS选择整数T和R作为***参数；Step 1.1: The e-commerce platform service provider ECS selects integers T and R as system parameters;

步骤1.2：电商平台服务方ECS向卖家发送***参数T和R；Step 1.2: The e-commerce platform service provider ECS sends the system parameters T and R to the seller;

步骤2：将卖家销售额数据进行分块压缩处理，并生成对应秘密份额；Step 2: Compress the seller's sales data in blocks and generate corresponding secret shares;

步骤3：云服务器聚合秘密份额；Step 3: The cloud server aggregates the secret share;

步骤4：电商平台服务方ECS获取多维统计分析结果。Step 4: The ECS, the service provider of the e-commerce platform, obtains multi-dimensional statistical analysis results.
根据权利要求1所述的电商平台卖家用户销售额多维统计分析方法，其特征在于，所述步骤2的具体实现包括以下子步骤：The method for multi-dimensional statistical analysis of sales of sellers and users on an e-commerce platform according to claim 1, wherein the specific implementation of step 2 includes the following sub-steps:

步骤2.1：卖家U _j将其K种商品的销售额数据A _j＝(a _j,1,a _j,2,…,a _j,K)按T个分量为一组的规则进行分块处理，卖家U _j将A _j＝(a _j,1,a _j,2,…,a _j,K)划分为
组，其中第一组为SA _j,1＝(a _j,1,a _j,2,…,a _j,T)，第二组为SA _j,2＝(a _j,T+1,a _j,T+2,…,a _j,T+T)，第三组为SA _j,3＝(a _j,2T+1,a _j,2T+2,…,a _j,2T+T)，依次类推； Step 2.1: The seller U _j divides the sales data A _j = (a _j,1 ,a _j,2 ,...,a _j,K ) of its K kinds of commodities according to the rule of T components as a group, The seller U _j divides A _j = (a _j,1 ,a _j,2 ,...,a _j,K ) into
groups, where the first group is SA _j,1 =(a _j,1 ,a _j,2 ,...,a _j,T ), and the second group is SA _j,2 =(a _j,T+1 ,a _{j ,T+2} ,…,a _j,T+T ), the third group is SA _j,3 =(a _j,2T+1 ,a _j,2T+2 ,…,a _j,2T+T ), in turn analogy;

步骤2.2：卖家U _j根据获得的***参数R将第l组销售额SA _j,l＝(a _j,(l-1)T+1,a _j,(l-1)T+2,…,a _j,(l-1)T+T)压缩为
S _j,l是一个整数，其中
Step 2.2: According to the obtained system parameter R, the seller U _{j calculates} the sales of the lth group SA _j,l =( _aj,(l-1)T+1 , _aj,(l-1)T+2 ,..., a _j,(l-1)T+T ) is compressed as
S _j,l is an integer, where

步骤2.3：卖家U _j为每个S _j,l生成n个秘密份额，分别表示为
其中
Step 2.3: The seller U _j generates n secret shares for each S _j,l , denoted as
in

卖家U _j共产生了
个秘密份额：

Seller U _j produced a total of
A secret share:

步骤2.4：卖家U _j将产生的S _jl的n个秘密份额向n个云服务器进行分发，卖家U _j将S _jl的秘密份额
发送给云服务器CS _i，其中
i＝1,2,…,n；云服务器CS _i收到来自卖家U _j的
个秘密份额：
一共收到来自m个卖家的
个秘密份额：
Step 2.4: The seller U _j distributes the generated n secret shares of S _jl to n cloud servers, and the seller U _j distributes the secret shares of S _jl
sent to the cloud server CS _i , where
i=1,2,...,n; cloud server CS _i receives from seller U _j
A secret share:
A total of received from m sellers
A secret share:
根据权利要求2所述的电商平台卖家用户销售额多维统计分析方法，其特征在于，所述步骤3的具体实现过程是：云服务器CS _i将每m个秘密份额
聚合为一个秘密份额，用符号
表示这个聚合得到的秘密份额，
实质上是所有卖家属于第l块的T类商品的销售额总和的压缩值
对应的一个秘密份额，其中
The method for multi-dimensional statistical analysis of sales of sellers and users on an e-commerce platform according to claim 2, wherein the specific implementation process of step 3 is: the cloud server CS _i stores every m secret shares
Aggregate into a secret share, with the symbol
represents the secret share obtained by this aggregate,
Essentially the compressed value of the sum of the sales of all sellers belonging to the T category of products in block l
corresponds to a secret share, where

利用(t,n)门限秘密共享的同态性实现上述聚合，具体计算公式为：
The above aggregation is realized by the homomorphism of (t,n) threshold secret sharing, and the specific calculation formula is:

重复执行上述聚合操作
次，CSi将
个秘密份额
压缩为
个秘密份额
Repeat the above aggregation operation
times, CSi will
secret share
compressed to
secret share
根据权利要求3所述的电商平台卖家用户销售额多维统计分析方法，其特征在于，所述步骤4的具体实现包括以下子步骤：The method for multidimensional statistical analysis of sales of sellers and users on an e-commerce platform according to claim 3, wherein the specific implementation of step 4 includes the following sub-steps:

步骤4.1：电商平台服务方ECS随机选择t个CS，让它们将其拥有的关于
的秘密份额发送给电商平台服务方ECS，ECS通过执行(t,n)门限秘密共享方案的重构算法恢复出
Step 4.1: ECS, the e-commerce platform service provider, randomly selects t CSs and asks them to use their own information about
The secret share of the e-commerce platform is sent to ECS, the service provider of the e-commerce platform, and the ECS recovers the

电商平台服务方ECS重复执行上述过程共
次，恢复出所有卖家的所有
个块中的T种商品的销售额总和的压缩值
The e-commerce platform service provider ECS repeats the above process for a total of
times, restore all sellers'
Compressed value of the sum of sales of T items in blocks

步骤4.2：电商平台服务方ECS通过执行针对***参数R的T次取余操作和T-1次取整操作从压缩值
中提取出
Step 4.2: ECS, the e-commerce platform service provider, performs T remainder operations and T-1 round operations for the system parameter R from the compressed value.
extracted from

电商平台服务方ECS重复执行上述过程共
次，从压缩值
中提取出针对每种商品的所有卖家的销售额总和：
表示m个卖家的第k种商品的销售总额，其中k＝1,2,…,K。 The e-commerce platform service provider ECS repeats the above process for a total of
times, from the compressed value
Extract the sum of all sellers' sales for each item from:
Indicates the total sales of the k-th commodity of m sellers, where k=1,2,...,K.
根据权利要求1所述的电商平台卖家用户销售额多维统计分析方法，其特征在于，所述步骤1的具体实现包括以下子步骤：The method for multidimensional statistical analysis of sales of sellers and users on an e-commerce platform according to claim 1, wherein the specific implementation of step 1 includes the following sub-steps:

步骤1.1：电商平台服务方ECS选择合适的整数T和R作为***参数，其中***参数T用在对卖家用户销售额的分块处理中，***参数R用在对块内销售额数据的压缩处理中；Step 1.1: The e-commerce platform service provider ECS selects the appropriate integers T and R as system parameters, where the system parameter T is used in the block processing of the sales of sellers and users, and the system parameter R is used to compress the sales data in the block. Processing;

参数T是步骤2中需要用到的分块参数，决定了每一个分块的大小，块大小会影响***性能，块大小越大通信开销越小但计算开销会增大，因此参数T的选择需要权衡各方面的性能开销来选定，参数R是步骤2中需要用到的压缩参数，它的选择需要满足其值要大于每块中每种商品销售额之和，假设一段时间内每种商品销售额不超过W，那么R需要满足R>TW；The parameter T is the block parameter that needs to be used in step 2, which determines the size of each block. The block size will affect the system performance. The larger the block size, the smaller the communication overhead but the higher the computational overhead. Therefore, the choice of parameter T It is necessary to weigh the performance costs of various aspects to select. The parameter R is the compression parameter that needs to be used in step 2. Its selection needs to satisfy that its value is greater than the sum of the sales of each commodity in each block. If the sales of goods do not exceed W, then R needs to satisfy R>TW;

步骤1.2：电商平台服务方ECS向卖家发送***参数T和R。Step 1.2: The e-commerce platform service provider ECS sends the system parameters T and R to the seller.