Data privacy through optimal k-anonymization
WebResearch on the anonymization of static data has made great progress in recent years. Generalization and suppression are two common technologies for quasi-identifiers' anonymization. However, the characteristics of data streams, such as potential ... WebEnter the email address you signed up with and we'll email you a reset link.
Data privacy through optimal k-anonymization
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WebMay 5, 2005 · This paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is ... WebOct 22, 2011 · The k -anonymity method has the property that each record is indistinguishable from at least k −1 records where the value of k reflects the degree of privacy level. Because of its simplicity and effectiveness, k -anonymity has become a popular approach where many studies on privacy preservation have been focused on or …
WebSep 22, 2024 · Bayardo RJ, Agrawal A. Data privacy through optimal k-anonymization. In: Proceedings 21st international conference on data engineering, 2005 (ICDE 2005). … WebThrough experiments on real census data, we show the resulting algorithm can find optimalk-anonymizations under two representative cost measures and a wide range of k. …
Webk-匿名性 （英語： k-anonymity ）是 匿名化数据 的一种性质。. 如果一组公开的数据中，任何一个人的信息都不能和其他至少 人区分开，则称该数据满足 k -匿名性。. k -匿名性的 … WebMethods for k-anonymization. To use k-anonymity to process a dataset so that it can be released with privacy protection, a data scientist must first examine the dataset and …
WebBlockchain is a kind of distributed ledger technology with the characteristics of decentralization,security reliability,tamper-proof and programmable.The open and transparent feature of the blockchain system has seriously threatened the transaction privacy of users,and the corresponding privacy problem solution is designed for …
WebApr 8, 2005 · Data de-identification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and … sharp pain in index finger knuckleWebTo use k-anonymity to process a dataset so that it can be released with privacy protection, a data scientist must first examine the dataset and decide if each attribute (column) is an identifier(identifying), a non-identifier(not-identifying), or a … porotherm calepinageWebApr 6, 2024 · The paradigm-shifting developments of cryptography and information theory have focused on the privacy of data-sharing systems, such as epidemiological studies, where agencies are collecting far more personal data than they need, causing intrusions on patients’ privacy. To study the capability of the data collection while protecting … sharp pain in hip when runningWebThis paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is indistinguishable from at least k - 1 others. Even simple restrictions of optimized k-anonymity are NP-hard, leading to significant computational … porotherm brickWebMay 1, 2007 · A useful approach to combat such linking attacks, called k-anonymization [1], is anonymizing the linking attributes so that at least k released records match each … sharp pain in knee areaWebDe-identifying data through common formulations of -anonymity is unfortunately NP-hard if one wishes to guarantee an optimal anonymization [8]. Algorithms that are suitable for … porotherm briqueWebThis alert has been successfully added and will be sent to: You will be notified whenever a record that you have chosen has been cited. sharp pain in hip while running