Biblio

Database outsourcing is one of the important utilities in cloud computing in which the Information Proprietor (IP) transfers the database administration to the Cloud Service Provider (CSP) in order to minimize the administration cost and preservation expenses of the database. Inspite of its immense profit, it undergoes few security issues such as privacy of deployed database and provability of search results. In the recent past, few of the studies have been carried out on provability of search results of Outsourced Database (ODB) that affords correctness and completeness of search results. But in the existing schemes, since there is flow of data between the Information Proprietor and the clients frequently, huge communication cost prevails at the Information Proprietor side. To address this challenge, in this paper we propose Efficient Auditing for Outsourced Database with Token Enforced Cloud Storage (EAODBT). The proposed scheme reduces the large communication cost prevailing at the Information Proprietor side and achieves correctness and completeness of search results even if the mischievous CSP knowingly sends a null set. Experimental analysis show that the proposed scheme has totally reduced the huge communication cost prevailing between Information Proprietor and clients, and simultaneously achieves the correctness and completeness of search results.

Data security has become an issue of increasing importance, especially for Web applications and distributed databases. One solution is using cryptographic algorithms whose improvement has become a constant concern. The increasing complexity of these algorithms involves higher execution times, leading to an application performance decrease. This paper presents a comparison of execution times for three algorithms using asymmetric keys, depending on the size of the encryption/decryption keys: RSA, ElGamal, and ECIES. For this algorithms comparison, a benchmark using Java APIs and an application for testing them on a test database was created.

With the growth of cloud computing, database outsourcing has attracted much interests. Due to the serious privacy threats in cloud computing, databases needs to be encrypted before being outsourced to the cloud. Therefore, various Top-k query processing algorithms have been studied for encrypted databases. However, existing algorithms are either insecure or inefficient. Therefore, in this paper we propose an efficient and secure Top-k query processing algorithm. Our algorithm guarantees the confidentiality of both the data and a user query while hiding data access patterns. Our algorithm also enables the query issuer not to participate in the query processing. To achieve a high level of query processing efficiency, we use new secure protocols using Yao's garbled circuit and a data packing technique. A performance analysis shows that the proposed algorithm outperforms the existing works in terms of query processing costs.

The security of order-revealing encryption (ORE) has been unclear since its invention. Dataset characteristics for which ORE is especially insecure have been identified, such as small message spaces and low-entropy distributions. On the other hand, properties like one-wayness on uniformly-distributed datasets have been proved for ORE constructions. This work shows that more plaintext information can be extracted from ORE ciphertexts than was previously thought. We identify two issues: First, we show that when multiple columns of correlated data are encrypted with ORE, attacks can use the encrypted columns together to reveal more information than prior attacks could extract from the columns individually. Second, we apply known attacks, and develop new attacks, to show that the leakage of concrete ORE schemes on non-uniform data leads to more accurate plaintext recovery than is suggested by the security theorems which only dealt with uniform inputs.