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T-closeness

Index T-closeness

t-closeness is a further refinement of ''l''-diversity group based anonymization that is used to preserve privacy in data sets by reducing the granularity of a data representation. [1]

6 relations: Data mining, Differential privacy, K-anonymity, L-diversity, Philip S. Yu, Suresh Venkatasubramanian.

Data mining

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

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Differential privacy

In cryptography, differential privacy aims to provide means to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records.

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K-anonymity

k-anonymity is a property possessed by certain anonymized data.

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L-diversity

l-diversity is a form of group based anonymization that is used to preserve privacy in data sets by reducing the granularity of a data representation.

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Philip S. Yu

Philip S. Yu (born 1952) is an American computer scientist and Professor in Information Technology at the University of Illinois at Chicago, known for his work in the field of data mining.

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Suresh Venkatasubramanian

Suresh Venkatasubramanian is an Indian computer scientist and professor at the University of Utah.

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References

[1] https://en.wikipedia.org/wiki/T-closeness

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