منابع مشابه
Pattern-Guided k-Anonymity
We suggest a user-oriented approach to combinatorial data anonymization. A data matrix is called k-anonymous if every row appears at least k times—the goal of the NP-hard k-ANONYMITY problem then is to make a given matrix k-anonymous by suppressing (blanking out) as few entries as possible. Building on previous work and coping with corresponding deficiencies, we describe an enhanced k-anonymiza...
متن کاملk-Anonymity
To protect respondents’ identity when releasing microdata, data holders often remove or encrypt explicit identifiers, such as names and social security numbers. De-identifying data, however, provide no guarantee of anonymity. Released information often contains other data, such as race, birth date, sex, and ZIP code, that can be linked to publicly available information to re-identify respondent...
متن کامل($k$,$\epsilon$)-Anonymity: $k$-Anonymity with $\epsilon$-Differential Privacy
The explosion in volume and variety of data offers enormous potential for research and commercial use. Increased availability of personal data is of particular interest in enabling highly customised services tuned to individual needs. Preserving the privacy of individuals against reidentification attacks in this fast-moving ecosystem poses significant challenges for a one-size fits all approach...
متن کاملAnonymity: Formalisation of Privacy – k-anonymity
Microdata is the basis of statistical studies. If microdata is released, it can leak sensitive information about the participants, even if identifiers like name or social security number are removed. A proper anonymization for statistical microdata is essential. K-anonymity has been intensively discussed as a measure for anonymity in statistical data. Quasi identifiers are attributes that might...
متن کاملMultidimensional K-Anonymity
K-Anonymity has been proposed as a mechanism for privacy protection in microdata publishing, and numerous recoding “models” have been considered for achieving kanonymity. This paper proposes a new multidimensional model, which provides an additional degree of flexibility not seen in previous (single-dimensional) approaches. Often this flexibility leads to higher-quality anonymizations, as measu...
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ژورنال
عنوان ژورنال: Algorithms
سال: 2013
ISSN: 1999-4893
DOI: 10.3390/a6040678