A collection of real world data causes very complex data structure. In large scale companies, there will be serious issues in Data storage, Data Management, Data Retrieving. It’s really a hard thing to do the data anonymization in live environment. Data Anonymization is a type of information disinfect whose intention is to protect the data for information loss and it will provide data security. It is also a process of removing the personal identifiable information from data set, so that the people whom the data can be described remains anonymous.
In this paper “We have expressed the association between the different values and different structures in different databases using syntax, e.g. XML values. Its concentrates on the privacy guarantee and the data with very simple data structure. In this paper, we focus on the tree structured data from various applications, even when the structure is not directly applied into the syntax.
This paper defines the km-n anonymity which provides the complete data privacy protection against unique and it’s proposes the greedy cut search GCS algorithm, which is able to disinfect the high level datasets.
N. NANDHINI : Computer Science and Engineering, Computer Science and Engineering,
VELS University, Chennai, India.
V. BINDU : (Assistant Professor),
Computer Science and Engineering, Computer Science and Engineering,
VELS University, Chennai, India. VELS University, Chennai, India.
Tree structured Data, Data privacy, Anonymity, Data sanitation, structural disassociation, Data generalization, synopsis tree.
In this paper, the proposed method is based on k(m-n) anonymity. Addressing the problem of anonymizing the tree structured data in the presence of structural knowledge. We propose km-n anonymity privacy guarantee which addressing the background knowledge of both structure and value. This anonymization algorithm is used to create the k (m-n) anonymous datasets, by examine the value generalization and a data transformation of novels, which we determined about the structural disassociation.
