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Differential privacy budget allocation-based data query method and system

A differential privacy and data query technology, applied in the field of information security, can solve the problems of too fast exhaustion of privacy budget, unsatisfactory effect, low data availability, etc., and achieve the effect of privacy protection, easy operation, and simple method

Active Publication Date: 2018-06-22
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

Differential privacy is realized through the noise mechanism, that is, random noise is added to the output to protect data security. The greater the noise added, the more secure the data, however, the lower the availability of the data, and vice versa
[0003] For the infinite allocation of differential privacy budget ε, a more conventional way of thinking is dichotomy, that is, the privacy budget allocated to the i-th query This scheme is simple and easy to operate, but it will cause the privacy budget to be exhausted too quickly. When the number of queries is large, the shared privacy budget is close to 0, so the effect is not ideal

Method used

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  • Differential privacy budget allocation-based data query method and system
  • Differential privacy budget allocation-based data query method and system
  • Differential privacy budget allocation-based data query method and system

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[0060] The differential privacy budget sequence of the present invention {ε i} Generated as figure 1 As shown, let ε=0.1, because F:

[0061]

[0062]

[0063]

[0064] …

[0065] There are 21,583,529 records in the age and income data of the United States, which is recorded as D. Each record contains age and income information, and the data set is queried below. In order to simplify the operation, we set the query set F={f|f to find the total number of people whose income is in the interval [2000, 5000]}, namely f 1 = f 2 =...=f n =...=f, Δf 1 =Δf 2 =...=Δf n =...=Δf=1,f 1 (D) = f 2 (D)=...=f n (D)=...=f(D)=941026.

[0066] like figure 2 As shown, the infinite query implementation process is as follows:

[0067] Step 1 initialize f=1;

[0068] Step 2 input f i ;

[0069] Stcp 3 generates ε i , and generate random noise

[0070] Step 4 Calculate M i (D) = f i (D)+η;

[0071] Step 5 output M i (D);

[0072] Step 6f++;

[0073] Step 7 to St...

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Abstract

The invention discloses a differential privacy budget allocation-based data query method, which realizes privacy protection in data query and release processes. According to the scheme, by utilizing asequence combination property of differential privacy protection, a privacy budget sequence is obtained through establishing infinite non-uniform segmentation of a differential privacy budget total quantity; and according to a privacy budget allocated to each item in the sequence, Laplace random noises added in data are calculated. The method is simple and easy in operation, does not limit querytypes, ensures infinite segmentation of the privacy budgets, meets differential privacy protection conditions, reduces increment speed of added noises, enables released data to reflect real data as far as possible, and protects data privacy. The invention furthermore provides a differential privacy budget allocation-based data query system.

Description

technical field [0001] The invention relates to a differential privacy budget allocation scheme in data query service, and belongs to the technical field of information security. Background technique [0002] The rapid development of the information age makes it easier to obtain data, which puts forward higher requirements for the security of data query. With the proposal and development of privacy protection technology, differential privacy protection method has become a popular privacy protection technology. How to allocate the privacy budget is an important issue often involved in differential privacy protection technology. Differential privacy is realized through the noise mechanism, that is, random noise is added to the output to protect the data security. The greater the noise added, the more secure the data, however, the lower the availability of the data, and vice versa. [0003] For the infinite allocation of differential privacy budget ε, a more conventional way ...

Claims

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Application Information

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IPC IPC(8): G06F21/62G06F17/30
CPCG06F21/6245G06F16/9032
Inventor 杨庚王璇唐海霞夏春婷
Owner NANJING UNIV OF POSTS & TELECOMM
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