WO2020034749A1

WO2020034749A1 - Data compiling method and device

Info

Publication number: WO2020034749A1
Application number: PCT/CN2019/092186
Authority: WO
Inventors: 应鹏飞
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2018-08-14
Filing date: 2019-06-21
Publication date: 2020-02-20
Also published as: CN110825922B; CN110825922A; TW202009864A; TWI706370B

Abstract

Disclosed by the present description are a data compiling method and device, which are applied to the compiling of data by combining data of N data holders, the method comprising: negotiating with other data holders one by one to determine a common pseudo-random number sequence and to obtain N-1 pseudo-random number sequences which correspond one-to-one with negotiation objects; selecting a pseudo-random number from each pseudo-random number sequence according to completely identical selection strategies, so as to obtain N-1 pseudo-random numbers in one-to-one correspondence with the negotiation objects; determining a participation value for the pseudo-random number corresponding to each negotiation object participating in an operation according to the sorting order of the N data holders, the participation value being the pseudo-random number or a number opposite thereto; performing summation calculation on the held data and the participation values of the N-1 pseudo-random numbers; and sending the summation result to a third party, so that the third party performs summation calculation for the summation results of all data holders to obtain a statistical value.

Description

Data statistics method and device

Technical field

This specification relates to the field of Internet technologies, and in particular, to a data statistics method and device.

Background technique

In the era of big data, there are many data islands. For example, the data of a natural person can be distributed and stored in different enterprises, and due to the consideration of competition and user privacy protection between enterprises, they do not completely trust each other. This is the statistics involving data cooperation between enterprises. Work created obstacles. Under the premise of fully protecting the core data privacy of the enterprise, it is an urgent problem to be solved that it can use some data owned by both parties to complete some statistical calculations without leaking the respective data privacy security of the enterprise.

Summary of the Invention

In view of this, this specification provides a data statistics method and device.

Specifically, this specification is implemented through the following technical solutions:

A data statistics method, which is applied to perform data statistics by combining data among N data holders, the data holder holds data to be calculated, and the method is applied to the data holder, include:

Negotiate a common pseudo-random number sequence with other data holders one by one, and obtain N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

According to the globally same selection strategy, each pseudo-random number is selected from each pseudo-random number sequence, and N-1 pseudo-random numbers corresponding to the negotiation object are obtained.

Determine the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders, and the participation value is the pseudo-random number or the pseudo-random number Opposite number;

Performing summation calculation on the held data and the participating values of the N-1 pseudo-random numbers;

Sending the summation result to the third party for the third party to perform summation calculation on the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.

A data statistics device is applied to perform data statistics by combining data among N data holders, the data holder holds data to be calculated, and the device is applied to the data holder, include:

A pair-by-two negotiation unit negotiates a common pseudo-random number sequence with other data holders in pairs, and obtains N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

The pseudo-random number selection unit selects pseudo-random numbers from each pseudo-random number sequence according to the same global selection strategy, and obtains N-1 pseudo-random numbers corresponding to the negotiation object one-to-one;

The participation value determination unit determines, according to an arrangement order between the N data holders, a participation value of a pseudorandom number corresponding to each negotiation object when participating in the operation, and the participation value is the pseudorandom number or all The opposite of the pseudo-random number;

A summation calculation unit that performs summation calculation on the held data and the participation value of the N-1 pseudo-random numbers;

A result sending unit, sending the summation result to the third party, so that the third party sums up and calculates the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.

A data statistics device includes:

processor;

Memory for storing machine-executable instructions corresponding to data statistics logic;

The machine-executable instructions corresponding to the data statistics logic are applied to perform data statistics by combining data among N data holders, and the data holders hold data to be calculated,

By reading and executing the machine-executable instructions corresponding to the data statistics logic, the processor is caused to:

Here, N is a natural number of 2 or more.

As can be seen from the above description, when performing data statistics in this specification, each data holder can sum up the participation values of the held data and the pseudo-random number, thereby hiding its own real data in the summation result. Ensure that data is not leaked. In addition, each data holder regards other data holders as negotiation objects, and negotiates a common pseudo-random number sequence with the negotiation objects one by one. The globally identical pseudo-random number selection strategy can also be adopted from the pseudo-random number sequence. The pseudo-random number selection is performed in order to obtain the same pseudo-random number, and according to the permutation order, the participation value of the pseudo-random number when participating in the operation is determined, thereby ensuring that the third party can obtain the result of summing all data holders. Sum calculation is performed to obtain statistical values, and multi-party safe sum calculation is realized. In addition, when performing data statistics, each data holder does not need to communicate with each other, which can effectively reduce the communication volume in the data statistics process and improve the calculation efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic flowchart of a data statistics method according to an exemplary embodiment of the present specification.

Fig. 2 is a schematic structural diagram of a data statistics device according to an exemplary embodiment of the present specification.

Fig. 3 is a block diagram of a data statistics device according to an exemplary embodiment of the present specification.

detailed description

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Rather, they are merely examples of devices and methods consistent with certain aspects of the specification, as detailed in the appended claims.

The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the specification. As used in this specification and the appended claims, the singular forms "a", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, the information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "at" or "when" or "in response to determination".

In the era of big data, multiple data holders can hold data of the same statistical object. In this case, when performing statistical calculations on data, multiple data holders may be involved and multiple data holders are required. Cooperate to complete statistics. However, due to the competition between different companies or the consideration of privacy protection, the respective data of the companies cannot be leaked in the statistical process.

For example, the same natural person can borrow on different P2P (peer-to-peer, Internet financial point-to-point lending) platforms, and each P2P platform stores the amount of the natural person's borrowing on this platform. When counting the total borrowing amount of this natural person, it is often necessary to cooperate with multiple P2P platforms to complete statistical calculations.

In this example, the P2P platform is the data holder, the amount of borrowing by the natural person is data held by the data holder, and the total borrowing amount of the natural person is the statistical value to be calculated.

As another example, each bicycle sharing platform can provide users with bicycle usage services, and each bicycle sharing platform stores the daily usage of bicycle sharing on the platform. When counting the total amount of shared bicycle use on a certain day, it is often necessary to combine multiple shared bicycle platforms to complete statistical calculations.

In this example, the bike sharing platform is the data holder. The usage of bike sharing on this day is the data held by the data holder. The total usage of bike sharing on this day is the statistical value to be calculated.

This embodiment is applied to perform data statistics by combining data among N data holders, where N is a natural number greater than or equal to 2.

Please refer to FIG. 1. The data statistics method can be applied to a data holder and includes the following steps:

Step 102: Negotiate a common pseudo-random number sequence with other data holders one by one to obtain N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one.

In this embodiment, each data holder can treat other data holders as negotiation objects, and then negotiate with each negotiation object in pairs to negotiate a common pseudo-random number sequence.

In one example, the data holder may negotiate the N-1 pseudo-random number sequences with other data holders each time data statistics are performed. That is, each time data statistics are performed, the pseudo-random number sequence is updated, and the pseudo-random number sequence is only used for data statistics once.

In another example, the data holder may negotiate with other data holders in advance to obtain the N-1 pseudo random number sequences, and the N-1 pseudo random number sequences may be used for multiple data statistics.

In step 104, pseudo-random numbers are selected from each pseudo-random number sequence according to the globally same selection strategy, and N-1 pseudo-random numbers corresponding to the negotiation object are obtained.

In this embodiment, the selection strategy may be used to select a pseudorandom number from a pseudorandom number sequence, and finally obtain a pseudorandom number corresponding to the pseudorandom number sequence, and the pseudorandom number also corresponds to the negotiation object.

In one example, the selection strategy may be a sequence number. The sequence number may be used to indicate that a pseudo-random number corresponding to the sequence number in the pseudo-random number sequence is selected. Assuming the sequence number is 5, it means that the fifth random number in the pseudo-random number sequence is selected.

The sequence number may also be used to indicate that selection is started from a pseudo-random number corresponding to the sequence number in a pseudo-random number sequence. Still assuming that the sequence number is 5, it can mean starting from the 5th pseudorandom number in the pseudorandom number sequence, and selecting K pseudorandom numbers one by one; it can also mean that it starts from the 5th + Hth pseudorandom number in the pseudorandom number sequence. , Select K pseudo-random numbers one by one; it can also mean that starting from the 5th pseudo-random number in the pseudo-random number sequence, K pseudo-random numbers are selected according to the interval of J, etc. There is no special limitation on this in this specification. After selecting K pseudo-random numbers, the K pseudo-random numbers can be combined to obtain a combined pseudo-random number. Among them, K is a natural number of 2 or more, and J and H are natural numbers of 1 or more.

Of course, the selection strategy may also include several sequence numbers, which can be used to indicate that the pseudo-random numbers corresponding to the sequence numbers in the pseudo-random number sequence are selected, and then the selected pseudo-random numbers are combined to obtain a combined pseudo-random number .

In another example, the selection strategy may include a sequence number and a sorting rule. The sorting rule may include: arranging from large to small, arranging from small to large, and the like. In this example, a pseudo-random number can be selected from the sorted pseudo-random number sequence according to the sequence number. For a specific selection method, refer to the foregoing description. This embodiment will not repeat them one by one here.

The above selection strategy is only an exemplary description. In actual applications, other selection strategies may also be adopted, and this specification does not specifically limit this.

Step 106: Determine the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders, and the participation value is the pseudo-random number or the pseudo-random number. The opposite of a random number.

In this embodiment, the arrangement order may be determined by the ID numbers of the data holders. For example, all data holders are sorted according to the ID numbers in ascending or descending order.

Of course, data holders can also be sorted based on other information, for example, algorithms based on IP addresses, etc. This specification does not specifically limit this.

In this embodiment, each data holder can determine the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the ranking result.

In one example, when the negotiation object is arranged behind the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation may be determined as the pseudo-random number; when the negotiation When the object is arranged before the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation may be determined as the reverse of the pseudo-random number.

In another example, when the negotiation object is arranged behind the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation may be determined as the opposite of the pseudo-random number; When the negotiation object is arranged in front of the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the calculation may be determined as the pseudo-random number, and there is no special limitation on this in this specification.

Step 108: Sum the calculated data and the participation values of the N-1 pseudo-random numbers.

In this embodiment, each data holder may perform a sum calculation on the data it holds and the participation value of the N-1 pseudorandom numbers obtained in the foregoing step 106, so as to hide its real data in the summation result. .

Step 110: Send the summation result to the third party, so that the third party performs summation calculation on the summation results of all data holders to obtain the statistical value.

In this embodiment, after the data holder obtains the summation result, the summation result may be sent to a third party, and the third party sums up the summation result of each data holder to obtain a statistical value. .

As can be seen from the above description, each data holder in this specification can negotiate a common pseudo-random number sequence with other data holders in pairs, so that each data holder holds N-1 pseudo-random numbers. Sequence, you can also select pseudo-random numbers from each pseudo-random number sequence according to the globally same pseudo-random number selection strategy to obtain N-1 pseudo-random numbers corresponding to the negotiation object, and then determine each pseudo-random number The participation value when participating in the calculation is combined with the data held by the local end to perform the summation calculation to hide the real data of the local end in the summing result and ensure that the data is not leaked. Each data holder can send the summation result to a third party, and the third party performs the summation calculation to obtain the statistical value, thereby achieving multi-party secure calculation. In addition, during data statistics, there is no need for communication between the data holders, which can greatly reduce the amount of communication during data statistics and improve computing efficiency.

The specific implementation process of this specification is described below through two embodiments, namely, the first embodiment and the second embodiment.

Example one

In this embodiment, before generating a pseudo-random number sequence, each data holder can treat other data holders as negotiation objects, and then negotiate with each negotiation object in pairs to negotiate a common seed.

For example, suppose there are 4 data holders, which are data holder 1 to data holder 4. Taking data holder 1 as an example, data holder 1 can regard data holder 2 to data holder 4 as negotiation objects, and then negotiate with these three negotiation objects to determine the pseudo-randomness. Sequence of seeds.

Table 1

Please refer to the example in Table 1. Data holder 1 and data holder 2 negotiate to determine the common seed X ₁₂ . The data holder 1 negotiates with the data holder 3 to determine a common seed X ₁₃ . Data holder 1 negotiates with data holder 4 to determine a common seed X ₁₄ . For data holder 1, X ₁₂ corresponds to data holder 2, X ₁₃ corresponds to data holder 3, and X ₁₄ corresponds to data holder 4.

Table 2

On the basis of Table 1, Table 2 refer to the example, the data for the holders 2, which negotiate with the data common seed holders 1 is determined by X _12, and the data holders 3 negotiation may be determined together The seed X ₂₃ is determined in consultation with the data holder 4 to determine a common seed X ₂₄ . Among them, X ₁₂ corresponds to data holder 1, X ₂₃ corresponds to data holder 3, and X ₂₄ corresponds to data holder 4.

Zh	种子seed
数据持有方1Data Holder 1	X ₁₂、X ₁₃、X ₁₄ X ₁₂ , X ₁₃ , X ₁₄
数据持有方2Data holder 2	X ₁₂、X ₂₃、X ₂₄ X ₁₂ , X ₂₃ , X ₂₄
数据持有方3Data Holder 3	X ₁₃、X ₂₃、X ₃₄ X ₁₃ , X ₂₃ , X ₃₄
数据持有方4Data Holder 4	X ₁₄、X ₂₄、X ₃₄ X ₁₄ , X ₂₄ , X ₃₄

table 3

By analogy, the data holder 1 to the data holder 4 can generate the seed examples shown in Table 3. As a result, the seeds generated by each data holder correspond one-to-one with the other three data holders.

In this embodiment, each data holder can generate in advance N-1 pseudo-random number sequences corresponding to the negotiation objects in a one-to-one manner, and the N-1 pseudo-random number sequences can be used for multiple data statistics.

In one example, each data holder may use a seed as the only input parameter to input a pseudo-random number generator to generate a pseudo-random number sequence, and the pseudo-random number sequence generated by the same seed is also the same.

Table 4

Taking the seed example shown in Table 3 as an example, please refer to the example in Table 4. The data holder 1 can generate three pseudo-random number sequences, which are R ₁₂ , R _13, and R _{14 respectively} . Among them, R ₁₂ corresponds to data holder 2, R ₁₃ corresponds to data holder 3, R ₁₄ corresponds to data holder 4, and so on.

So far, data holder 1 to data holder 4 all generate 3 pseudo-random number sequences, and each two data holders have a common pseudo-random number sequence, for example, the data holder 1 and data holder 2 have a common pseudo-random number sequence R ₁₂ , data holder 1 and data holder 3 have a common pseudo-random number sequence R _13, and so on.

In the application scenario of N data holders, each data holder holds N-1 pseudo-random number sequences, and these N-1 pseudo-random number sequences are respectively different from other N-1 data holders. One correspondence, and any two data holders will have a common pseudo-random number sequence.

In this embodiment, the number of elements of the pseudo-random number sequence can be determined by the algorithm of the pseudo-random number generator. For example, the pseudo-random number sequence generated by the AES128 (Advanced Encryption Standard) algorithm has 128 elements, which is generated by the AES256 algorithm. The pseudo-random number sequence has 256 elements, and the pseudo-random number sequence generated by the HMAC256 (Hash-based Message Authentication Code) algorithm also has 256 elements.

In another example, when generating a pseudo-random number sequence, in addition to seeds, there may be other input parameters, such as a count value and the like.

Taking the count value as an example, when the data holders negotiate the seed, they can also negotiate a common count value with the negotiation object, and then input the seed and the count value into the pseudo-random number generator to generate a pseudo-random number sequence. Based on the same seed and the same count value, the same pseudo-random number sequence can also be generated.

After generating the pseudo-random number sequence, the data holder can select pseudo-random numbers from each pseudo-random number sequence according to the globally same selection strategy, and obtain N-1 pseudo-random numbers corresponding to the negotiation object one-to-one.

In this embodiment, the selection strategy may be specified by a third party every time data statistics are performed.

The third party is independent of each data holder, and can specify a count value for each data holder, and can also calculate a statistical value by combining the summation results of all data holders.

In actual implementation, the above-mentioned functions provided by the third party may be implemented by one platform or by different platforms, for example, a designated platform may specify a count value for each data holder, and a computing platform may unite all data holders. The summation result of the square can be used to calculate statistical values, etc., and there is no special restriction on this in this specification.

In one example, the foregoing data holder 1 to data holder 4 are still taken as an example. Assuming that the pseudo-random number selection strategy is sequence number 5, which indicates that the fifth pseudo-random number in the pseudo-random number sequence is selected, then Each data holder selects the 5th pseudorandom number from the 3 pseudorandom number sequences generated by itself as the pseudorandom number corresponding to the negotiation object.

table 5

Based on the example of Table 4, a selection data holding section 5 side pseudo-random number from the pseudo random number sequence R _12, assuming that the pseudo-random number bit 5 is r _12, selected from the first pseudo random number sequence 5 R _13, Bit pseudo-random number, assuming that the fifth bit pseudo-random number is r ₁₃ , and so on, the pseudo-random number examples shown in Table 5 can be obtained. Three of the data holders 1 to 4 are selected and negotiated. Pseudo-random number corresponding to the object one-to-one.

In this embodiment, since each two data holders have a common pseudo-random number sequence, and for each pseudo-random number sequence, each data holder adopts the same global selection strategy The random number is selected, so after the pseudo-random number is selected, each of the two data holders has a common pseudo-random number. For example, data holder 1 and data holder 2 are selected to obtain a common pseudo-random number r ₁₂ , data holder 1 and data holder 3 are selected to obtain a common pseudo-random number r _13, and so on.

Therefore, after each data holder and its negotiation object generate a common pseudo-random number sequence, they also select a common pseudo-random number from the pseudo-random number sequence.

In another example, it is assumed that the selection strategy is sequence number 5, which means that starting from the 5th pseudo-random number in the pseudo-random number sequence, K pseudo-random numbers are selected one by one, K is globally unique, and is pre-empted by the data holder. By convention, its value is 3. Each data holder can select the 5th, 6th, and 7th pseudorandom numbers from the pseudorandom number sequence held by them, and then combine the 3 pseudorandom numbers selected and combine the results. As a pseudo-random number corresponding to the pseudo-random number sequence.

Taking data holder 1 as an example, assuming that the fifth pseudorandom number selected from the pseudorandom number sequence R ₁₂ is 123, the sixth pseudorandom number is 456, and the seventh pseudorandom number is 789, then 123, 456 and 789 are combined.

For example, the three pseudo-random numbers can be stitched together in ascending order of sequence numbers to obtain the combined result 123456789, that is, r ₁₂ is 123456789.

For another example, three pseudo-random numbers can also be stitched together in order from large to small to obtain a combined result of 789456123, that is, r ₁₂ is 789456123.

Of course, other combination schemes can also be adopted, or the selected three pseudo-random numbers can be set for calculation, etc. This specification does not make any special restrictions on this.

In this embodiment, after N-1 pseudo-random numbers corresponding to the negotiation object are selected and obtained, the participation value of each pseudo-random number when participating in the operation can be determined.

Taking the four data holders shown in Table 5 as an example, the ID numbers are sorted from small to large, and the ranking results are: data holder 1, data holder 2, data holder 3, data holder Party 4.

It is assumed that when the negotiation object is arranged behind the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation is determined as the pseudo-random number; when the negotiation object is arranged in the present Before the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation is determined as the reverse of the pseudo-random number.

Table 6

Please continue to refer to Table 5. For the data holder 2, the data holder 1 whose negotiation object is ranked first, so the participation value of the pseudo-random number r ₁₂ corresponding to the data holder 1 can be determined as the opposite number. -r ₁₂ , the negotiation data holder 3 is arranged behind, so the participation value of the pseudo-random number r ₂₃ corresponding to the data holder 3 can be determined as r ₂₃ , and so on, the participation values shown in Table 6 can be obtained Examples.

In this embodiment, after determining the participation values of the N-1 pseudo-random numbers corresponding to the N-1 negotiation objects, each data holder may perform a check on the held data and the N-1 pseudo-random numbers. Participation values are summed to hide their true data in the summation results.

Table 7

Please continue to refer to Table 6. Assume that the data held by data holder 1 is X ₁ , the data held by data holder 2 is X ₂ , and so on. After performing the summation, you can get the requirements shown in Table 7. And results.

Please continue to refer to Table 7. The third party sums up the summation results of the data holder 1 to the data holder 4, and obtains the statistical value X ₁ + X ₂ + X ₃ + X ₄ .

In this embodiment, a third party can obtain a statistical value by performing a summation calculation on the summation result of each data holder, without other calculations, which is simple and fast.

Optionally, in another example, after each data holder calculates and obtains a summation result, the summation result may also be broadcast, and then the summation calculation is performed on the summation results of all data holders participating in the statistics to obtain Statistics.

Optionally, in order to ensure the randomness of the summing result of the data holder, a third party may specify a different global selection strategy each time the data statistics are performed. Still taking the selection strategy as sequence number as an example, a third party can specify a different sequence number for each data statistic, for example: the first time the sequence number is 1, the second time the sequence number is 2, and so on until the sequence number The value is the number of pseudo-random numbers in the pseudo-random number sequence. When the sequence number value is the number of pseudo-random numbers in the pseudo-random number sequence, each data holder can re-negotiate pairwise to generate a new common pseudo-random number sequence, and the third party can reassign the sequence number to 1 , 2, ..., and so on.

With such an implementation manner, the selection strategy can be verified on the data holder side. For example, each data holder may record the selection strategy. When a third-party-selected selection strategy is received again, it is determined whether the received selection strategy conflicts with the recorded selection strategy, and the conflict usually indicates that the received The selection strategy has been used.

In case of conflict, an error message can be returned to a third party.

If there is no conflict, a step of selecting a pseudo-random number from each pseudo-random number sequence according to the globally same selection strategy is performed, and the record selection strategy is updated.

Taking the sequence number assigned by the third party from 1 as an example, the data holder can record the sequence number sent by the third party. When the sequence number sent by the third party is received again, it can be determined whether the received sequence number is greater than the recorded one. Sequence number.

If it is greater than that, it indicates that the pseudo-random number corresponding to the sequence number has not been used. You can select a pseudo-random number from each pseudo-random number sequence according to the received sequence number, and you can record the sequence number after the selection is completed. Update.

If it is less than or equal to, it can indicate that the pseudo-random number corresponding to the sequence number has been used, and an error prompt can be returned to a third party.

Similarly, when the sequence number indicates that K pseudo-random numbers are selected one by one from the pseudo-random number corresponding to the sequence number in the pseudo-random number sequence and then combined, the data holder can record the maximum order of the selected pseudo-random number Number, that is, the sequence number + K-1. When the sequence number sent by the third party is received again, it is determined whether the received sequence number is greater than the maximum sequence number recorded.

In this embodiment, different strategy records and conflict judgment schemes can be formulated based on the selected strategy, which will not be described in detail in this specification.

In this embodiment, each time when data statistics are performed, different pseudo-random numbers can be selected from the pseudo-random number sequence to participate in the summation calculation, so that the summation result has randomness, and it can effectively prevent an illegal person from taking multiple summation results. Analyze the real data held by the data holder to ensure data security and no leakage.

It is worth noting that the implementation scheme of the third-party delivery selection strategy, when a data holder goes offline, does not affect the data statistics of the online data holder, and the online data holder can still send based on the third party The selection strategy performs steps such as pseudo-random number selection, summation calculation, etc. to obtain the statistical value of the data held by all online data holders.

Example two

In this embodiment, before generating a pseudo-random number sequence, each data holder can also treat other data holders as negotiation objects, and then negotiate with each negotiation object in pairs to negotiate a common seed. .

For the process of seed negotiation, reference may be made to the foregoing Embodiment 1, and details are not described herein again.

In this embodiment, each time a third party performs data statistics, the data holder can specify the globally same count value. After receiving the count value, each data holder can use the seed and the count value as The input parameter is a pseudo-random number generator to generate a pseudo-random number sequence.

In order to prevent the data holder from generating the same pseudo-random number sequence during multiple data statistics, a third party may specify a different count value each time the data statistics are performed.

For example, a third party may specify the counting value sequentially from 1, that is, the first designated counting value is 1, the second designated counting value is 2, and so on, and so on.

In this embodiment, the count value can be verified on the data holder side. For example, each data holder may record the count value, and when the count value specified by the third party is received again, it is determined whether the received count value is greater than the recorded count value.

If it is larger than that, it can be said that the count value has not been used, the pseudo-random number sequence generation step can be performed, and the recorded count value can be updated after the pseudo-random number sequence is generated.

If it is less than or equal to, it can indicate that the count value has been used, and an error prompt can be returned to a third party.

Of course, in actual implementation, the count value will not be taken to infinity, and a cycle period can be set, such as three months, half a year, and so on. When this cycle is reached, each data holder can re-seed the seed, and the third party can also reset the value of the count to 1.

The implementation of a third-party-designated count value can effectively reduce frequent seed negotiation between data holders and reduce network traffic.

In this embodiment, each data holder can also generate N-1 pseudo-random number sequences, and these N-1 pseudo-random number sequences respectively correspond to the other N-1 data holders, and any Both data holders will have a common pseudo-random number sequence.

The pseudo-random number sequence generated each time can be used for data statistics only once.

In this embodiment, a globally same selection strategy may also be specified by a third party. For a specific implementation solution, refer to the foregoing first embodiment.

If the selection strategy is a sequence number, it is relatively simple. When the count value does not exceed the number of elements of the pseudo-random number sequence, the count value specified by the third party can also be used as the sequence number of the selection strategy. .

Optionally, in this embodiment, since each data holder regenerates a pseudo-random number sequence each time data statistics are performed, the globally same fixed selection strategy may also be adopted. For example, each time a pseudo-random number is selected, a 10- to 20-bit pseudo-random number is selected from the pseudo-random number sequence, and then these pseudo-random numbers are combined, and the combined result is used as the pseudo-random corresponding to the negotiation object. number.

In this embodiment, after a pseudo-random number corresponding to the negotiation object is selected, the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation can be determined according to the arrangement order between the data holders. , And then perform a summation calculation on the held data and the participation values of the N-1 pseudo-random numbers, and send the summation result to the third party, and the third party sums up all the data holders. Sum the results and calculate to obtain the statistical value. For the processing and implementation of this part, refer to the first embodiment described above, which will not be described in detail in this embodiment.

Corresponding to the foregoing embodiment of the data statistics method, this specification also provides an embodiment of a data statistics device.

The embodiments of the data statistics apparatus in this specification may be applied to a server or a server cluster deployed by a data holder. The device embodiments may be implemented by software, or by hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by reading the corresponding computer program instructions in the non-volatile memory into the memory through the processor of the server where it is located. In terms of hardware, as shown in FIG. 2, it is a hardware structure diagram of the server where the data statistics device of this specification is located. In addition to the processor, memory, network interface, and non-volatile memory shown in FIG. 2, The server where the device is located in the embodiment may generally include other hardware according to the actual function of the server, and details are not described herein again.

Referring to FIG. 3, the data statistics device 200 may be applied to perform data statistics by combining data among N data holders, and the data holder holds data to be calculated, and the data statistics device 200 It includes: a pair of negotiation unit 201, a pseudo-random number selection unit 202, a participation value determination unit 203, a sum calculation unit 204, a result sending unit 205, a conflict determination unit 206, and a count value determination unit 207.

Among them, the pair-by-two negotiation unit 201 negotiates a common pseudo-random number sequence with other data holders in pairs, and obtains N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

The pseudo-random number selecting unit 202 selects pseudo-random numbers from each pseudo-random number sequence according to the globally same selection strategy, and obtains N-1 pseudo-random numbers corresponding to the negotiation object one-to-one;

The participation value determination unit 203 determines the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders, and the participation value is the pseudo-random number or An opposite number of the pseudo-random number;

A summation calculation unit 204 performs a summation calculation on the held data and the participation values of the N-1 pseudo-random numbers;

A result sending unit 205, sending the summation result to the third party, so that the third party sums up and calculates the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.

Optionally, the pairwise negotiation unit 201:

Negotiate common seeds with other data holders one by one, and get N-1 seeds corresponding to the negotiation object one-to-one;

Generate N-1 pseudo-random number sequences according to the N-1 seeds.

Optionally, the selection strategy is specified by the third party each time data statistics are performed.

The conflict judging unit 206 records the selection strategy, and when a third-party-selected selection strategy is received again, determines whether the received selection strategy conflicts with the recorded selection strategy; if there is no conflict, the selection strategy based on the same global is executed Steps to select pseudo-random numbers from each pseudo-random number sequence, and update the record selection strategy.

Optionally, the pairwise negotiation unit 201:

Negotiate a common seed with other data holders in advance, and get N-1 seeds corresponding to the object of negotiation;

Receiving the globally same count value specified by the third party every time data statistics are performed;

Generate N-1 pseudo-random number sequences according to the N-1 seeds and the count value.

The count value judging unit 207 records the count value; when the count value designated by the third party is received again, it is judged whether the count value is greater than the recorded count value; if it is greater, the execution is performed according to the N-1 seeds and all The steps of generating counted N-1 pseudo-random number sequences are described, and the recorded count value is updated.

Optionally, the selection strategy is fixed.

Optionally, the selection strategy is a sequence number.

Optionally, the pseudo-random number selecting unit 202 selects a pseudo-random number corresponding to a globally same sequence number from each pseudo-random number sequence.

Optionally, the pseudo-random number selecting unit 202 selects a plurality of pseudo-random numbers for each pseudo-random number sequence, starting from a pseudo-random number corresponding to a globally identical sequence number in the pseudo-random number sequence; Several pseudo-random numbers, and the combined result is used as a pseudo-random number selected from the pseudo-random number sequence.

Optionally, the pseudo-random number selecting unit 202 selects a fixed number of pseudo-random numbers one by one, and the fixed number is greater than one.

Optionally, the participation value determination unit 203:

When the negotiation object is arranged behind the data holder, determining the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation as the pseudo-random number;

When the negotiation object is arranged before the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation is determined as the reverse of the pseudo-random number.

For details about the implementation process of the functions and functions of the units in the foregoing device, see the implementation process of the corresponding steps in the foregoing method for details, and details are not described herein again.

As for the device embodiment, since it basically corresponds to the method embodiment, the relevant part may refer to the description of the method embodiment. The device embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, may be located One place, or it can be distributed across multiple network elements. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution in this specification. Those of ordinary skill in the art can understand and implement without creative efforts.

The system, device, module, or unit described in the foregoing embodiments may be specifically implemented by a computer chip or entity, or a product with a certain function. A typical implementation device is a computer, and the specific form of the computer may be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email sending and receiving device, and a game control Desk, tablet computer, wearable device, or a combination of any of these devices.

Corresponding to the foregoing embodiment of the data statistics method, the present specification also provides a data statistics device. The data statistics device includes a processor and a memory for storing machine-executable instructions corresponding to the data statistics logic. Wherein, the machine-executable instructions corresponding to the data statistics logic are applied to combine data among N data holders to perform data statistics, and the data holder holds data to be calculated. The processor and the memory are usually interconnected by an internal bus. In other possible implementations, the device may further include an external interface to enable communication with other devices or components.

In this embodiment, by reading and executing machine-executable instructions corresponding to data statistics logic stored in the memory, the processor is caused to:

Here, N is a natural number of 2 or more.

Optionally, when negotiating a common pseudo-random number sequence with other data holders in pairs, the processor is caused to:

Generate N-1 pseudo-random number sequences according to the N-1 seeds.

Optionally, the processor is further caused to:

Record the selection strategy;

When a third-party selection strategy is received again, determine whether the received selection strategy conflicts with the recorded selection strategy;

Negotiate a common seed with other data holders in advance, and get N-1 seeds corresponding to the negotiation object one-to-one;

Optionally, the processor is further caused to:

Recording said count value;

When the count value specified by the third party is received again, determine whether the count value is greater than the recorded count value;

If it is greater than that, the step of generating N-1 pseudo-random number sequences according to the N-1 seeds and the count value is performed, and the recorded count value is updated.

Optionally, the selection strategy is fixed.

Optionally, the selection strategy is a sequence number.

Optionally, when a pseudo-random number is selected from each pseudo-random number sequence separately according to a globally same selection strategy, the processor is further prompted:

A pseudo-random number corresponding to a globally identical sequence number is selected from each pseudo-random number sequence.

For each pseudo-random number sequence, starting from a pseudo-random number corresponding to a globally identical sequence number in the pseudo-random number sequence, selecting a plurality of pseudo-random numbers;

The selected pseudo-random numbers are combined, and the combined result is used as the pseudo-random number selected from the pseudo-random number sequence.

Optionally, when selecting several pseudo-random numbers, the processor is caused to:

A fixed number of pseudo-random numbers are selected one by one, and the fixed number is greater than one.

Optionally, when determining the participation value of the pseudo-random number corresponding to each negotiation object in the operation according to the arrangement order between the N data holders, the processor is caused to:

Corresponding to the foregoing embodiment of the data statistics method, the present specification also provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, the program being applied to unite N data holders. The data is subjected to data statistics. The data holder holds the data to be calculated. When the program is executed by the processor, the following steps are implemented:

Here, N is a natural number of 2 or more.

Optionally, the negotiation of a common pseudo-random number sequence with other data holders includes:

Generate N-1 pseudo-random number sequences according to the N-1 seeds.

Optional, also includes:

Record the selection strategy;

Optional, also includes:

Recording said count value;

Optionally, the selection strategy is fixed.

Optionally, the selection strategy is a sequence number.

Optionally, the step of selecting a pseudo-random number from each pseudo-random number sequence according to a globally same selection strategy includes:

Optionally, the selecting a plurality of pseudo-random numbers includes:

Optionally, determining the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders includes:

The specific embodiments of the present specification have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and the desired result may still be achieved. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The above is only a preferred embodiment of this specification, and is not intended to limit the specification. Any modification, equivalent replacement, or improvement made within the spirit and principles of this specification shall be included in this specification. Within the scope of protection.

Claims

A data statistics method, which is applied to perform data statistics by combining data among N data holders, the data holder holds data to be calculated, and the method is applied to the data holder, include:

Negotiate a common pseudo-random number sequence with other data holders one by one, and obtain N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

According to the globally same selection strategy, each pseudo-random number is selected from each pseudo-random number sequence, and N-1 pseudo-random numbers corresponding to the negotiation object are obtained.

Determine the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders, and the participation value is the pseudo-random number or the pseudo-random number Opposite number;

Performing summation calculation on the held data and the participating values of the N-1 pseudo-random numbers;

Sending the summation result to the third party for the third party to perform summation calculation on the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.
The method according to claim 1, wherein said negotiating a common pseudo-random number sequence with other data holders includes:

Negotiate common seeds with other data holders one by one, and get N-1 seeds corresponding to the negotiation object one-to-one;

Generate N-1 pseudo-random number sequences according to the N-1 seeds.
The method according to claim 2,

The selection strategy is specified by the third party every time data statistics are performed.
The method of claim 3, further comprising:

Record the selection strategy;

When a third-party selection strategy is received again, determine whether the received selection strategy conflicts with the recorded selection strategy;

If there is no conflict, a step of selecting a pseudo-random number from each pseudo-random number sequence according to the globally same selection strategy is performed, and the record selection strategy is updated.
The method according to claim 1, wherein said negotiating a common pseudo-random number sequence with other data holders includes:

Negotiate a common seed with other data holders in advance, and get N-1 seeds corresponding to the negotiation object one-to-one;

Receiving the globally same count value specified by the third party every time data statistics are performed;

Generate N-1 pseudo-random number sequences according to the N-1 seeds and the count value.
The method of claim 5, further comprising:

Recording said count value;

When the count value specified by the third party is received again, determine whether the count value is greater than the recorded count value;

If it is greater than that, the step of generating N-1 pseudo-random number sequences according to the N-1 seeds and the count value is performed, and the recorded count value is updated.
The method according to claim 5,

The selection strategy is fixed.
The method according to claim 1,

The selection strategy is a sequence number.
The method according to claim 8, wherein the selecting a pseudo-random number from each pseudo-random number sequence according to a globally same selection strategy comprises:

A pseudo-random number corresponding to a globally identical sequence number is selected from each pseudo-random number sequence.
The method according to claim 8, wherein the selecting a pseudo-random number from each pseudo-random number sequence according to a globally same selection strategy comprises:

For each pseudo-random number sequence, starting from a pseudo-random number corresponding to a globally identical sequence number in the pseudo-random number sequence, selecting a plurality of pseudo-random numbers;

The selected pseudo-random numbers are combined, and the combined result is used as the pseudo-random number selected from the pseudo-random number sequence.
The method according to claim 10, wherein the selecting a plurality of pseudo-random numbers comprises:

A fixed number of pseudo-random numbers are selected one by one, and the fixed number is greater than one.
The method according to claim 1, wherein determining a participation value of a pseudo-random number corresponding to each negotiation object when participating in an operation according to an arrangement order between the N data holders comprises:

When the negotiation object is arranged behind the data holder, determining the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation as the pseudo-random number;

When the negotiation object is arranged before the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation is determined as the reverse of the pseudo-random number.
A data statistics device is applied to perform data statistics by combining data among N data holders, the data holder holds data to be calculated, and the device is applied to the data holder, include:

A pair-by-two negotiation unit negotiates a common pseudo-random number sequence with other data holders in pairs, and obtains N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

The pseudo-random number selection unit selects pseudo-random numbers from each pseudo-random number sequence according to the same global selection strategy, and obtains N-1 pseudo-random numbers corresponding to the negotiation object one-to-one;

The participation value determination unit determines, according to an arrangement order between the N data holders, a participation value of a pseudorandom number corresponding to each negotiation object when participating in the operation, and the participation value is the pseudorandom number or all The opposite of the pseudo-random number;

A summation calculation unit that performs summation calculation on the held data and the participation value of the N-1 pseudo-random numbers;

A result sending unit, sending the summation result to the third party, so that the third party sums up and calculates the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.
The apparatus according to claim 13, the pair of negotiation units:

Negotiate common seeds with other data holders one by one, and get N-1 seeds corresponding to the negotiation object one-to-one;

Generate N-1 pseudo-random number sequences according to the N-1 seeds.
The device according to claim 14,

The selection strategy is specified by the third party every time data statistics are performed.
The apparatus according to claim 15, further comprising:

The conflict judgment unit records the selection strategy, and when a third-party-selected selection strategy is received again, determines whether the received selection strategy conflicts with the recorded selection strategy; if there is no conflict, it executes the same selection strategy according to the global Steps to select a pseudo-random number from each pseudo-random number sequence, and update the record selection strategy.
The apparatus according to claim 13, the pair of negotiation units:

Negotiate a common seed with other data holders in advance, and get N-1 seeds corresponding to the negotiation object one-to-one;

Receiving the globally same count value specified by the third party every time data statistics are performed;

Generate N-1 pseudo-random number sequences according to the N-1 seeds and the count value.
The apparatus according to claim 17, further comprising:

The count value judging unit records the count value; when a count value designated by a third party is received again, it is judged whether the count value is greater than the recorded count value; if it is greater, execution is performed according to the N-1 seeds and the The step of generating the count value of N-1 pseudo-random number sequences and updating the recorded count value.
The device according to claim 17,

The selection strategy is fixed.
The device according to claim 13,

The selection strategy is a sequence number.
The device according to claim 20,

The pseudo-random number selecting unit selects a pseudo-random number corresponding to a globally same sequence number from each pseudo-random number sequence.
The device according to claim 20,

The pseudo-random number selecting unit selects, for each pseudo-random number sequence, a plurality of pseudo-random numbers starting from the pseudo-random number corresponding to a globally identical sequence number in the pseudo-random number sequence; And use the combination result as a pseudo-random number selected from the pseudo-random number sequence.
The device according to claim 22,

The pseudo-random number selecting unit selects a fixed number of pseudo-random numbers one by one, and the fixed number is greater than one.
The apparatus according to claim 13, the participation value determination unit:

When the negotiation object is arranged behind the data holder, determining the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation as the pseudo-random number;

When the negotiation object is arranged before the data holder, the participation value of the pseudo-random number corresponding to the negotiation object when participating in the operation is determined as the reverse of the pseudo-random number.
A data statistics device includes:

processor;

Memory for storing machine-executable instructions corresponding to data statistics logic;

The machine-executable instructions corresponding to the data statistics logic are applied to perform data statistics by combining data among N data holders, and the data holders hold data to be calculated,

By reading and executing the machine-executable instructions corresponding to the data statistics logic, the processor is caused to:

Negotiate a common pseudo-random number sequence with other data holders one by one, and obtain N-1 pseudo-random number sequences corresponding to the negotiation object one-to-one;

According to the globally same selection strategy, each pseudo-random number is selected from each pseudo-random number sequence, and N-1 pseudo-random numbers corresponding to the negotiation object are obtained.

Determine the participation value of the pseudo-random number corresponding to each negotiation object when participating in the operation according to the arrangement order between the N data holders, and the participation value is the pseudo-random number or the pseudo-random number Opposite number;

Performing summation calculation on the held data and the participating values of the N-1 pseudo-random numbers;

Sending the summation result to the third party for the third party to perform summation calculation on the summation results of all data holders to obtain the statistical value;

Here, N is a natural number of 2 or more.