K-concealment based Distributed Anonymization for the Cloud

There is a growing interest in cloud computing due to its various benefits such as the sharing of computing resources and the data containing personal information across multiple distributed and private databases. However, privacy and security concerns are among the main obstacles facing the widespread adoption of this new technology. Data Economization makes data worthless to anyone except the owner of the data. It is one of the methods for transforming the data in such a way that it prevents identification of key information from an unauthorized person. Most of the existing works use a k-anonym at model for preserving privacy for data subject that offers lower utility. Motivated by this, we develop a new distributed anonymization protocol to satisfy multiple data providers privacy requirements based on a k-concealment model that offers a higher utility.