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

Abstract

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.

Searchable Encrypted String for Query Support on Different Encrypted Data Types

“…Methods that implement queryable encrypted databases on string data types need to support LIKE operator to search on encrypted data. These methods can be considered in three categories: based on Bloom filter [22], [23], based on mapping [24], [25] and converting string to number [26], [27].…”

Authentication Protocol for Cloud Databases Using Blockchain Mechanism

“…Wu et al [1] observed the encryption technique to prevent understanding of user data. Before applying the query on the user data, it should be decrypted first and after finishing the query process, the data is again encrypted.…”

“…The users can store, modify and retrieve the data anywhere in the world. Therefore, it is essential to secure privacy in a cloud databases [1]. According to the Information security breaches survey (ISBS), 2015 large organizations stated that there was an element 81% of staff involved in some of the breaches they suffered [2], 90% of organizations feel vulnerable to an insider threat according to the Insider Threat 2018 Report [3] and Forrester Research [4].…”

“…In literature, researchers have worked on other security issues like outside malicious attacks, access control issues, network breaches, data provenance, resource exhaustion, consistency management, etc. However, much less work has been proposed on anticipating insider attacks [1,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23], which is the primary objective of this study.…”

An approach for the protection of users’ book browsing preference privacy in a digital library

“…Recently, researchers also attempt to study the problem from the view of technologies, e.g. by using encryption (Wu et al, 2017), identity authentication (Han et al, 2016) and authorization and access control (Shao et al, 2014;Li et al, 2015). However, most of the existing methods are designed only for users' data privacy, so are not practicable for users' behavior privacy.…”