Sensitivity Based Data Anonymization Model with Mixed Generalization
نویسندگان
چکیده
منابع مشابه
Generalization-Based k-Anonymization
Microaggregation is an anonymization technique consisting on partitioning the data into clusters no smaller than k elements and then replacing the whole cluster by its prototypical representant. Most of microaggregation techniques work on numerical attributes. However, many data sets are described by heterogeneous types of data, i.e., numerical and categorical attributes. In this paper we propo...
متن کاملGeneralization-Based k-Anonymization
Microaggregation is an anonymization technique consisting on partitioning the data into clusters no smaller than k elements and then replacing the whole cluster by its prototypical representant. Most of microaggregation techniques work on numerical attributes. However, many data sets are described by heterogeneous types of data, i.e., numerical and categorical attributes. In this paper we propo...
متن کاملGeneralization-Based k-Anonymization
Microaggregation is an anonymization technique consisting on partitioning the data into clusters no smaller than k elements and then replacing the whole cluster by its prototypical representant. Most of microaggregation techniques work on numerical attributes. However, many data sets are described by heterogeneous types of data, i.e., numerical and categorical attributes. In this paper we propo...
متن کاملAnonymization of Set-Valued Data via Top-Down, Local Generalization
Set-valued data, in which a set of values are associated with an individual, is common in databases ranging from market basket data, to medical databases of patients’ symptoms and behaviors, to query engine search logs. Anonymizing this data is important if we are to reconcile the conflicting demands arising from the desire to release the data for study and the desire to protect the privacy of ...
متن کاملOntology-Based Quality Evaluation of Value Generalization Hierarchies for Data Anonymization
In privacy-preserving data publishing, approaches using Value Generalization Hierarchies (VGHs) form an important class of anonymization algorithms. VGHs play a key role in the utility of published datasets as they dictate how the anonymization of the data occurs. For categorical attributes, it is imperative to preserve the semantics of the original data in order to achieve a higher utility. De...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advances in Scientific Research and Engineering
سال: 2019
ISSN: 2454-8006
DOI: 10.31695/ijasre.2019.33150