Secure sql query over encrypted database
204848131
A novel approach for query over encrypted data in database
Database management is considered an essential component of many information systems to store data. Some database system contains secure data; these data are protected by using encryption techniques. The query performance is affected by encryption techniques. Therefore; should be a balance between the security and performance. A new technique in this research work has been proposed to enhance the query performance over the encrypted fields in a database system. This technique is based on producing a unique hash value for each secure data and transforms the SQL query into an appropriate formula to be executed over the hash value fields. The proposed approach has eliminated any statistical relationship between encrypted and hash value fields. The time of execution encryption/decryption is reduced to enhance the performance of the query over encrypted secure data in the proposed technique. A set of experiments are carried out, and the results indicate that the performance of SQL query is enhanced by reducing the average response time to 14 compared with others related approaches.
Int. J. Inf. Comput. Secur.
Ja'afer Al-Saraireh
45938873
SQL Based Fuzzy Query Mechanism Over Encrypted Database
With the development of cloud computing and big data, data privacy protection has become an urgent problem to solve. Data encryption is the most effective way to protect privacy; however, it will change the data format and result in: 1. database structure and application software will be changed; 2. structured query language (SQL) operations cannot work properly, especially in SQL based fuzzy query. As a result, it is necessary to provide an SQL based fuzzy query mechanism over encrypted databases, including traditional databases and cloud outsourced databases. This paper establishes a secure database system using format preserving encryption (FPE) as the underlying primitive to protect the data privacy while not change the database structure. It further proposes a new SQL based fuzzy query mechanism supporting directly query over encrypted data, which is constructed by FPE and universal hash function (UHF) The security of the proposed mechanism is analyzed as well. In the end, it makes extensive experiments on the system to demonstrate its practical performance.
Int. J. Data Warehous. Min.
Zheli Liu Jingwei Li Jin Li Chunfu Jia Jun Yang Ke Yuan
203655911
Secure and Efficient Query Processing Technique for Encrypted Databases in Cloud
Cloud computing is an attractive environment for both organizations and individual users, as it provides scalable computing and storage services at an affordable price. However, privacy and confidentiality are two challenges that trouble most users. Data encryption, using a powerful encryption algorithm such as the Advanced Encryption Standard (AES) is one solution that can allay users' concerns, but other challenges with searching over encrypted data have arisen. Researchers have proposed many different schemes to execute Standard Query Language (SQL) queries over encrypted data by encrypting the data with more than one encryption algorithm. However, other researchers have proposed systems based on the fragmentation of encrypted data. In this paper, we propose bit vector based model (BVM) a secure database system that works as an intermediary between users and the cloud provider. In BVM, before the encryption and outsourcing processes, the query manager (QM) takes each record from the main table, parses it, builds a bit vector for it, and stores it. The BV stores bits, zero and one, and its length equals the total number of sub columns for all sensitive columns. BVM aims to reduce the range of retrieved encrypted records that are related to a user's query from the cloud. In our model, the cloud provider cannot deduce information from the encrypted data nor can infer which encryption algorithm was used to encrypt data. We implement BVM and run different experiments to compare our model with the methods in which data are not encrypted in the cloud. Our evaluation shows that BVM reduces the range of the retrieved encrypted records from the cloud to less than 35 percent of encrypted records. As a result, our model avoids unnecessary decryption processes that affect delay times.
2019 2nd International Conference on Data Intelligence and Security (ICDIS)
Sultan Almakdi Brajendra Panda
218650883
A Secure Model to Execute Queries Over Encrypted Databases in the Cloud
Recently, database users have begun to use cloud database services to outsource their databases. This is due to the high computation speed and the huge storage capacity the cloud owners provide at low prices. Despite cloud computing being an attractive environment for database users, privacy issues are cause for concern for database owners since the data access will be out of their control. Encryption is the only way of assuaging users' fears surrounding data privacy. However, executing Structured Query Language (SQL) queries over encrypted data is a challenging task, especially if the data are encrypted by a randomized encryption algorithm. Many researchers have addressed the privacy issues by using deterministic encryption, onion layers encryption, or homomorphic encryption to encrypt data. But, even with these systems, the encrypted data can still be subject to attack. In this research, we propose a model to execute SQL queries over encrypted data, where the data are encrypted by a single randomized encryption algorithm namely, Advanced Encryption Standard AES CBC. We move most of the computations to the cloud and leave users with no crypto computation. Our model intends to narrow the range of retrieved encrypted records from the cloud to a small set of records that are candidates for the user's query. We implement and evaluate our model and find that it is both practical and efficient. Our experiments show that our model succeeds in minimizing the decryption processes to less than 30% of decryption the whole set of encrypted records in a table.
2019 IEEE International Conference on Smart Cloud (SmartCloud)
Sultan Almakdi Brajendra Panda
174820507
ServeDB: Secure, Verifiable, and Efficient Range Queries on Outsourced Database
Data outsourcing to cloud has been a common IT practice nowadays due to its significant benefits. Meanwhile, security and privacy concerns are critical obstacles to hinder the further adoption of cloud. Although data encryption can mitigate the problem, it reduces the functionality of query processing, e.g. disabling SQL queries. Several schemes have been proposed to enable one dimensional query on encrypted data, but multi dimensional range query has not been well addressed. In this paper, we propose a secure and scalable scheme that can support multi dimensional range queries over encrypted data. The proposed scheme has three salient features: (1) Privacy: the server cannot learn the contents of queries and data records during query processing. (2) Efficiency: we utilize hierarchical cubes to encode multi dimensional data records and construct a secure tree index on top of such encoding to achieve sublinear query time. (3) Verifiability: our scheme allows users to verify the correctness and completeness of the query results to address server's malicious behaviors. We perform formal security analysis and comprehensive experimental evaluations. The results on real datasets demonstrate that our scheme achieves practical performance while guaranteeing data privacy and result integrity.
2019 IEEE 35th International Conference on Data Engineering (ICDE)
Songrui Wu Qi Li Guoliang Li Dong Yuan Xingliang Yuan Cong Wang
3345155
Secure query processing with data interoperability in a cloud database environment
We address security issues in a cloud database system which employs the DBaaS model. In such a model, a data owner (DO) exports its data to a cloud database service provider (SP) To provide data security, sensitive data is encrypted by the DO before it is uploaded to the SP. Existing encryption schemes, however, are only partially homomorphic in the sense that each of them was designed to allow one specific type of computation to be done on encrypted data. These existing schemes cannot be integrated to answer real practical queries that involve operations of different kinds. We propose and analyze a secure query processing system (SDB) on relational tables and a set of elementary operators on encrypted data that allow data interoperability, which allows a wide range of SQL queries to be processed by the SP on encrypted information. We prove that our encryption scheme is secure against two types of threats and that it is practically efficient.
SIGMOD Conference
W Wong Ben Kao David Wai-Lok Cheung Rongbin Li Siu-Ming Yiu
3731560
Efficient secure similarity computation on encrypted trajectory data
Outsourcing database to clouds is a scalable and cost effective way for large scale data storage, management, and query processing. Trajectory data contain rich spatio temporal relationships and reveal many forms of individual sensitive information (e.g. home address, health condition) which necessitate them to be encrypted before being outsourced for privacy concerns. However, efficient query processing over encrypted trajectory data is a very challenging task. Though some achievements have been reported very recently for simple queries (e.g. SQL queries, kNN queries) on encrypted data, there is rather limited progress on secure evaluation of trajectory queries because they are more complex and need special treatment. In this paper, we focus on secure trajectory similarity computation that is the cornerstone of secure trajectory query processing. More specifically, we propose an efficient solution to securely compute the similarity between two encrypted trajectories, which reveals nothing about the trajectories, but the final result. We theoretically prove that our solution is secure against the semi honest adversaries model as all the intermediate information in our protocols can be simulated in polynomial time. Finally we empirically study the efficiency of the proposed method, which demonstrates the feasibility of our solution.
2015 IEEE 31st International Conference on Data Engineering
An Liu Kai Zheng Lu-qun Li Guanfeng Liu Lei Zhao Xiaofang Zhou
6639443
Secure cipher index over encrypted character data in database
With the development of the information technology, database security draws more and more attention than before. It is desirable to store data in encrypted form to protect the sensitive data from various attacks. But the efficiency of DBMS will fall as the SQL clauses can not execute over the encrypted data directly. In this paper we propose a secure cipher index with great efficiency over the encrypted character data to improve the performance of the encrypted database. The radical idea is to map the character data in the database into its index value, and translate the SQL clauses into a usable form to execute over the index attribute. Hash key and confuse number are introduced to make the cipher index in security in our scheme. In this schema, the same character data in different rows has different index value and the index value has no statistical characteristic, so it can alleviate the problem of statistical attack and plain attack. When there is a query over the encrypted character attribute, we filter out the majority of useless tulpes through the index and only decrypt the remainder, which could reduce the decryption cost greatly and prevent the information leaking.
2008 International Conference on Machine Learning and Cybernetics
Yong Ou Zhang Wei-xin Li Xiamu Niu
214753446
A Survey: Query Processing Techniques for Secure Cloud Databases
The Major challenge in cloud computing is to manage distributed cloud. Traditional relational database management systems (RDBMS) are a choice but they are not compatible to measure crossways large clusters of distributed servers. Therefore changeovers to RDBMS have been developed. The development of new database management systems (DBMS) for the cloud computing environment or flexibility of the existing systems to the cloud computing environment is a critical component of cloud computing research. This paper focuses on the study of a relational database system based on holomorphic encryption schemes to preserve the integrity and confidentiality of the data. And also examines various SQL queries over encrypted data. And this paper helps in focusing where research is needed.
N Swetha Prof S Ramachandram
16102448
Database query privacy using homomorphic encryptions
Homomorphic encryption is a novel encryption method for it enables computing over encrypted data. This has a wide range of real world ramifications such as being able to blindly compute a search result sent to a remote server without revealing it's content. In this paper we summarize how SQL queries can be made secure using a homomorphic encryption scheme based on the ideas of Gahi, et al [1] Gahi's model is based on the DGHV scheme which is a homomorphic encryption scheme which acts on plaintext bits and produce corresponding ciphertext. We use Gahi's blueprint to propose an improved model which is based on the more recent Ring based homomorphic encryption scheme by Braserski, et al [2] Our method is more general in the sense that it can be extended to use with any fully homomorphic encryption scheme rather than being restricted to the DGHV scheme as in Gahi's method.
2015 IEEE 14th Canadian Workshop on Information Theory (CWIT)
Sudharaka Palamakumbura Hamid Usefi