The problem of publishing personal data without giving up privacy is becoming increasingly important. An interesting formalization recently proposed is the k-anonymity. This approach requires that the rows in a table are clustered in sets of size at least k and that all the rows in a cluster become the same tuple, after the suppression of some records. The natural optimization problem, where th...

K-anonymity is the approach used for preventing identity disclosure. Identity disclosure means an individual is linked to a particular record in the published data and individual’s sensitive data is accessed .Some important information such as Name, Income details , Medical Status and Property details are considered as a sensitive data( or Attribute) because these data have to be kept secure fr...

Protecting privacy in microdata publishing is K-Anonymity, Here recoding “models” have been considered for achieving k anonymity[1,2]. We proposes a new multidimensional model, which gives high flexibility. Often this flexibility leads to higher-quality anonymizations, as measured both by generalpurpose metrics and more specific notions of query answerability. Like previous multidimensional mod...

Continued advances in mobile networks and positioning technologies have created a strong market push for location-based services (LBSs). Examples include location-aware emergency services, location based service advertisement, and location sensitive billing. One of the big challenges in wide deployment of LBS systems is the privacy-preserving management of location-based data. Without safeguard...

Advances in data storage, data collection and inference techniques have enabled the creation of huge databases of personal information. Dissemination of information from such databases even if formally anonymised, creates a serious threat to individual privacy through statistical disclosure. One of the key methods developed to limit statistical disclosure risk is k-anonymity. Several methods ha...

One of the emerging concept in micro data protection is k-anonymity. It permits to assess the risk of disclosure for a data set protected with micro aggregation. Suppose if John owns a k-anonymous database and Kevin wants to insert his own tuple. After insertion if Kevin check the whole database to find out whether anonymity is maintained or not it will violate confidentiality maintained by Joh...

Online social networks and publication of social network data has led to the risk of leakage of confidential information of individuals. This requires the preservation of privacy before such network data is published by service providers. Privacy in online social networks data has been of utmost concern in recent years. Hence, the research in this field is still in its early years. Several publ...

In this paper, we have proposed new variants of the El-Gamal and the Cramer-Shoup encryption schemes. In our schemes, the anonymity property holds even if each user chooses an arbitrary prime q where |q| = k and p = 2q + 1 is also prime. More precisely, our El-Gamal variants provide anonymity against the chosen-plaintext attack, and our Cramer-Shoup variants provide anonymity against the adapti...

Recent research studied the problem of publishing microdata without revealing sensitive information, leading to the privacy preserving paradigms of k-anonymity and `-diversity. k-anonymity protects against the identification of an individual’s record. `-diversity, in addition, safeguards against the association of an individual with specific sensitive information. However, existing approaches s...