We study privacy guarantees for the owner of an information system who wants to share some of the information in the system with clients while keeping some other information secret. The privacy guarantees ensure that publishing the new information will not compromise the secret one. We present a framework for describing privacy guarantees that generalises existing probabilistic frameworks in re...

Breaching privacy of individual data and the measures to prevent the same from attackers has become the most interesting topic of research on the day. In this paper we have made a brief survey on various anonymization principles and practices, privacy preserving techniques beyond kanonymity. Principles designed inorder to prevent the proximity breaching of data are studied in depth. Concept of ...

Privacy-preserving data publishing is a process of releasing the anonymized dataset for various purposes analysis and research. Earlier, researchers have dealt with datasets considering it would contain only one record an individual [1:1 dataset], which uncompromising in applications. Later, many concentrate on dataset, where has multiple records [1:M dataset]. In paper, model f-slip was propos...

The data mining figures out accurate information for requesting user after the raw data is analyzed. Among lots of developments, data mining face hot issues on security, privacy and integrity. Data mining use one of the latest technique called privacy preserving data publishing (PPDP), which enforces security for the digital information provided by governments, corporations, companies and indiv...

Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Ever-escalating internet phishing posed severe threat on widespread propagation of sensitive information over the web. Conversely, the dubious feelings and contentions mediated unwillingness of various information providers...

Differential privacy is a security guarantee model which widely used in privacy preserving data publishing, but the query result can’t be used in data research directly, especially in high-dimensional datasets. To address this problem, we propose a dimensionality reduction method. The core idea of this method is using a series of lowdimensional datasets to reconstruct a high-dimensional dataset...

Recent interest in data collection and monitoring using data mining for security and business-related applications has raised privacy. Privacy Preserving Data Mining (PPDM) techniques require data modification to disinfect them from sensitive information or to anonymize them at an uncertainty level. This study uses PPDM with adult dataset to investigate effects of K-anonymization for evaluation...

Through data mining collect large amount of data in many organizations. A key value of huge databases today is technical or financial research. In a huge collection of data there arises a key issue that is privacy. Due to personal interests, medical databases or business interests privacy is needed. Due to privacy infringement while performing the data mining operations this is often not possib...