A Comparison of the Query Execution Algorithms in Secure Database System

In accordance with the database management, DAS(Database as Service) model is one solution for outsourcing. However, we need some data protection mechanisms in order to maintain the database security The most effective algorithm to secure databases from the security threat of third party attackers is to encrypt the sensitive data within the database. However, once we encrypt the sensitive data, we have difficulties in queries execution on the encrypted database. In this paper, we focus on the search process on the encrypted database. We proposed the selective tuple encryption method using Bloom Filter which could tell us the existence of the data. Finally, we compare the search performance between the proposed method and the other encryption methods we know

An effective approach for the protection of privacy text data in the CloudDB

© 2017, Springer Science+Business Media, LLC. Due to the advantages of pay-on-demand, expand-on-demand and high availability, cloud databases (CloudDB) have been widely used in information systems. However, since a CloudDB is distributed on an untrusted cloud side, it is an important problem how to effectively protect massive private information in the CloudDB. Although traditional security strategies (such as identity authentication and access control) can prevent illegal users from accessing unauthorized data, they cannot prevent internal users at the cloud side from accessing and exposing personal privacy information. In this paper, we propose a client-based approach to protect personal privacy in a CloudDB. In the approach, privacy data before being stored into the cloud side, would be encrypted using a traditional encryption algorithm, so as to ensure the security of privacy data. To execute various kinds of query operations over the encrypted data efficiently, the encrypted data would be also augmented with additional feature index, so that as much of each query operation as possible can be processed on the cloud side without the need to decrypt the data. To this end, we explore how the feature index of privacy data is constructed, and how a query operation over privacy data is transformed into a new query operation over the index data so that it can be executed on the cloud side correctly. The effectiveness of the approach is demonstrated by theoretical analysis and experimental evaluation. The results show that the approach has good performance in terms of security, usability and efficiency, thus effective to protect personal privacy in the CloudDB