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Differential privacy is often discussed in the context of identifying individuals whose information may be in a database. Although it does not directly refer to identification and reidentification attacks, differentially private algorithms probably resist such attacks.

Differential privacy is often discussed in the context of identifying individuals whose information may be in a database. Although it does not directly refer to identification and reidentification attacks, differentially private algorithms probably resist such attacks.

粗略地说，如果一个观察者看到一个算法的输出不能判断一个特定个体的信息是否被用于计算，那么这个算法就是有差异的私有的。差分隐私通常是在识别数据库中的个人信息时讨论的。虽然它不直接涉及身份识别和重新身份识别攻击，但差别私有算法可能抵抗这种攻击。

粗略地说，如果一个观察者看到一个算法的输出不能判断一个特定个体的信息是否被用于计算，那么这个算法就是有差异的私有的。差分隐私通常是在识别数据库中的个人信息时讨论的。虽然它不直接涉及身份识别和重新身份识别攻击，但差别私有算法可能抵抗这种攻击。<ref name="DMNS06" />

Differential privacy was developed by [[Cryptography|cryptographers]] and thus is often associated with cryptography, and draws much of its language from cryptography.

Differential privacy was developed by [[Cryptography|cryptographers]] and thus is often associated with cryptography, and draws much of its language from cryptography.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

|-

|-

!姓名! ！患有糖尿病(x) |-| Ross | | 1 |-| Monica | | | 1 | |-| Joey | | 0 |-| Phoebe | 0 |-|-| Chandler | | 1 |-|-| Rachel | | | | |

!姓名! ！患有糖尿病(x) |<nowiki>-| Ross | | 1 |-| Monica | | | 1 | |-| Joey | | 0 |-| Phoebe | 0 |-|-| Chandler | | 1 |-|-| Rachel | | | | |</nowiki>

Now suppose a malicious user (often termed an ''adversary'') wants to find whether Chandler has diabetes or not. Suppose he also knows in which row of the database Chandler resides. Now suppose the adversary is only allowed to use a particular form of query <math>Q_i</math> that returns the partial sum of the first <math>i</math> rows of column <math>X</math> in the database. In order to find Chandler's diabetes status the adversary executes <math>Q_5(D_1)</math> and <math>Q_4(D_1)</math>, then computes their difference. In this example, <math>Q_5(D_1) = 3</math> and <math>Q_4(D_1) = 2</math>, so their difference is 1. This indicates that the "Has Diabetes" field in Chandler's row must be 1. This example highlights how individual information can be compromised even without explicitly querying for the information of a specific individual.

Now suppose a malicious user (often termed an ''adversary'') wants to find whether Chandler has diabetes or not. Suppose he also knows in which row of the database Chandler resides. Now suppose the adversary is only allowed to use a particular form of query <math>Q_i</math> that returns the partial sum of the first <math>i</math> rows of column <math>X</math> in the database. In order to find Chandler's diabetes status the adversary executes <math>Q_5(D_1)</math> and <math>Q_4(D_1)</math>, then computes their difference. In this example, <math>Q_5(D_1) = 3</math> and <math>Q_4(D_1) = 2</math>, so their difference is 1. This indicates that the "Has Diabetes" field in Chandler's row must be 1. This example highlights how individual information can be compromised even without explicitly querying for the information of a specific individual.

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