Preferred Keyword Search over Encrypted Data in Cloud Computing

Cloud computing cuts down large capital outlays in facilities purchase and eliminates complex system management for users. To protect data confidentiality in cloud utilization, sensitive data are usually stored in encrypted form, making traditional search service on plaintext inapplicable. Thus, enabling keyword search over encrypted data becomes a paramount urgency. Given massive data users with various search preferences, it becomes necessary to support preferred keyword search and output the data files in the order of the user's preference. In this paper, for the first time, we investigate the challenging problem of preferred keyword search over encrypted data (PSED). We first establish a set of privacy requirements and utilize the appearance frequency of each keyword to serve as its "weight". A preference preprocessing mechanism is then explored to ensure that the search result will faithfully respect the user's preference and the Lagrange polynomial is introduced to express the user's preference formula. We further represent keyword weights of each file by using vectors, convert the preference polynomial into the vector form, and securely calculate their inner products to quantitatively characterize the relevance measure between data files and a query. Finally, an extensive performance evaluation demonstrates the proposed scheme can achieve acceptable efficiency.