DOUBLE KEY SEEDS BASED PRIVACY PRESERVING DATA MINING APPROACH FOR ENHANCED REVERSIBLE DATA HIDING

Abstract

The ultimate goal of Privacy Preserving Data Mining is to develop efficient algorithms that allow one to extract relevant knowledge from large amount of data, while preventing sensitive information from disclosure or inference. Several data mining algorithms, incorporating privacy preserving mechanisms, have been developed over the last years. There is an emerging need of synthesizing literature to understand the nature of problem and evaluate the relative performance of different approaches. In the proposed privacy optimal aggregation (POA) method, the original data is perturbed and embedded with a fragile watermark to accomplish privacy preserving and data integrity of mined data and to recover the original data. This technique is a high quality reversible method with crypto analysis for data embedding. A Special case of information hiding is digital watermarking poses double key distribution for data recovery process. The proposed method is for protecting privacy data as well as preventing illegal users from searching correlation of the distributed data security.