Generating minimality-attack-resistant data
First Claim
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1. A method comprising:
- receiving, at a computer executing an anonymization application, a data set at an anonymization engine, the data set comprising a plurality of tuples;
ordering, by the computer, the tuples in the data set according to an aspect of the tuples;
partitioning, by the computer, the tuples into a plurality of buckets, each of the plurality of buckets comprising a predefined number of the tuples;
selecting, by the computer, a bucket of the plurality of buckets as a group;
determining, by the computer, if the group satisfies a privacy requirement; and
if a determination is made that the group does not satisfy the privacy requirement,determining if a further bucket of the plurality of buckets is available,merging the further bucket into the group to form a further group,determining if the further group satisfies the privacy requirement, andif a determination is made that the further group satisfies the privacy requirement, outputting a new data set comprising the group and the further group.
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Abstract
The present disclosure is directed to systems, methods, and computer-readable storage media for generating data and data sets that are resistant to minimality attacks. Data sets having a number of tuples are received, and the tuples are ordered according to an aspect of the tuples. The tuples can be split into groups of tuples, and each of the groups may be analyzed to determine if the group complies with a privacy requirement. Groups that satisfy the privacy requirement may be output as new data sets that are resistant to minimality attacks.
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Citations
16 Claims
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1. A method comprising:
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receiving, at a computer executing an anonymization application, a data set at an anonymization engine, the data set comprising a plurality of tuples; ordering, by the computer, the tuples in the data set according to an aspect of the tuples; partitioning, by the computer, the tuples into a plurality of buckets, each of the plurality of buckets comprising a predefined number of the tuples; selecting, by the computer, a bucket of the plurality of buckets as a group; determining, by the computer, if the group satisfies a privacy requirement; and if a determination is made that the group does not satisfy the privacy requirement, determining if a further bucket of the plurality of buckets is available, merging the further bucket into the group to form a further group, determining if the further group satisfies the privacy requirement, and if a determination is made that the further group satisfies the privacy requirement, outputting a new data set comprising the group and the further group. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system comprising:
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a processor; and a memory that stores computer-executable instructions that, when executed by the processor, cause the processor to perform operations comprising receiving a data set comprising a plurality of tuples, each of the tuples comprising sensitive data and non-sensitive data; order the tuples in the data set according to the non-sensitive data; partitioning, by the computer, the tuples into a plurality of buckets, each of the plurality of buckets comprising a predefined number of the tuples; selecting a bucket of the plurality of buckets as a group; determining if the group satisfies a privacy requirement; and if a determination is made that the group does not satisfy the privacy requirement, determining if a further bucket of the plurality of buckets is available, merging the further bucket into the group to form a further group, determining if the further group satisfies the privacy requirement, and if a determination is made that the further group satisfies the privacy requirement, outputting a new data set comprising the group and the further group. - View Dependent Claims (13)
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14. A computer-readable storage medium comprising computer-executable instructions that, when executed by a processor, cause the processor to perform operations comprising:
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receiving a data set comprising a plurality of tuples, each of the tuples comprising sensitive data and non-sensitive data; order the tuples in the data set according to the non-sensitive data; partitioning, by the computer, the tuples into a plurality of buckets, each of the plurality of buckets comprising a predefined number of the tuples; selecting a bucket of the plurality of buckets as a group; determining if the group satisfies a privacy requirement; and if a determination is made that the group does not satisfy the privacy requirement determining if a further bucket of the plurality of buckets is available, merging the further bucket into the group to form a further group, determining if the further group satisfies the privacy requirement, and if a determination is made that the further group satisfies the privacy requirement, outputting a new data set comprising the group and the further group. - View Dependent Claims (15, 16)
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Specification