Classification of Negative Databases

Abstract

Due to the rapid growth and diversity of data, it has become essential to develop effective methods for maintaining data privacy when applying data mining algorithms. Large-scale data environments require secure methods that enable the classification and prediction of new inputs while preserving data confidentiality. This paper will propose farmwork for implementing classification algorithms based on the concept of negative databases (NDBs), aiming to perform binary and multi classification in secure environment. It will evaluate in terms of performance metrics, and prediction.