Reconstructing positive surveys from negative surveys by improved artificial immune network

Abstract

Privacy protection in high efficiency and low energy consumption is a vital aspect in mobile and sensor networks. The negative survey acts as an advisable approach to sensitive data protection and individual privacy because negative survey can collect negative categories with high efficiency. To some extent, the conventional method is still less than satisfactory and leaves much to be desired in this aspect. Present methods for reconstructing positive survey and eliminating negative values (i.e. less than zero) may have problems such as rapid convergence or cannot achieving optimal values. In this paper, a novel method is proposed to reconstruct positive survey from negative survey. The proposed method based on artificial immune network can reconstruct preferable positive survey: more accuracy and no negative values. Experimental results show this method is conducive to the realization of more reasonable outcomes.