W-DiffGen:Differentially Private Data Released Via Wavelet Transform

The arrival of Big Data Era leads to a boom of data analysis technology.With the growing demand for data analysis,it is necessary for various types of data to be analyzed,and the protection of the hidden private information becomes the key restriction on the opening of data.In response to the times and conditions,the privacy protection technology rises,applied to solving the problem of the sensitive information leak during data publishing and analysis.In recent years,the differential privacy data protection technology has attracted wide attention in the academic circle,and gradually becomes the most prominent one in the research field of the privacy protection.Due to the accuracy it limits the degree of privacy leakage,differential privacy protection technology has rised to become the standard technology used in the field of privacy protection.Among numerous algorithms of differential privacy data protection,the DiffGen is a representative one.Founded on the basis of DiffGen algorithm,the research of this paper aims at improving its defects and deficiencies by providing a differential privacy data publishing method based on the wavelet transform,which refers to W-DiffGen.It combines the additive noise mechanism of the differential privacy data based on the wavelet transform,effectively reduces noise volume during the algorithm process,as well,it promotes the availability of data after the provess of addition of noise.