Multiple-negative survey method for enhancing the accuracy of negative survey-based cloud data privacy

The development of cloud computing brings convenience to our lives due to high efficiency, usability, accessibility and affordability. But the cloud data privacy faces severe challenges. Although Negative survey, which is spired by Artificial Immune System (AIS), can protect users´ privacy data with high efficiency and degree of privacy protection, its accuracy is influenced by the number of client terminals, and insufficient client terminals may lead to many errors. This study focuses on a multiple-negative survey method of remedying this weakness. Compared with traditional negative survey, the multiple-negative survey method collects each user´s multiple different negative categories rather than only one negative category. The accuracy is analysed and simulation experiments verify the analysis.