With the many benefits of cloud computing, an entity may want to outsource its data and their related analytics tasks to a cloud. When data are sensitive, it is in the interest of the entity to outsource encrypted data to the cloud; however, this limits the types of operations that can be performed on the cloud side. Especially, evaluating queries over the encrypted data stored on the cloud without the entity performing any computation and without ever decrypting the data become a very challenging problem. In this paper, we propose solutions to conduct range queries over outsourced encrypted data. The existing methods leak valuable information to the cloud which can violate the security guarantee of the underlying encryption schemes. In general, the main security primitive used to evaluate range queries is secure comparison (SC) of encrypted integers. However, we observe that the existing SC protocols are not very efficient. To this end, we first propose a novel SC scheme that takes encrypted integers and outputs encrypted comparison result. We empirically show its practical advantage over the current state-of-the-art. We then utilize the proposed SC scheme to construct two new secure range query protocols. Our protocols protect data confidentiality, privacy of user's query, and also preserve the semantic security of the encrypted data; therefore, they are more secure than the existing protocols. Furthermore, our second protocol is lightweight at the user end, and it can allow an authorized user to use any device with limited storage and computing capability to perform the range queries over outsourced encrypted data.
@cite_29 proposed a new technique for protecting confidentiality as well as access patterns to the data in outsourced environments. Their technique is based on constructing shuffled index structures using B+-trees. In order to hide the access patterns, their method introduces fake searches in conjunction with the actual index value to be searched. We emphasize that their work solves a different problem - mainly how to securely outsource the index and then obliviously search over this data structure. Their technique has a straight-forward application to keyword search over encrypted data since it deals with exact matching. However, at this point, it is not clear how their work can be extended for range queries that require implicit comparison operations to be performed in a secure manner.
@cite_29
2105751742
As the use of external storage and data processing services for storing and managing sensitive data becomes more and more common, there is an increasing need for novel techniques that support not only data confidentiality, but also confidentiality of the accesses that users make on such data. In this paper, we propose a technique for guaranteeing content, access, and pattern confidentiality in the data outsourcing scenario. The proposed technique introduces a shuffle index structure, which adapts traditional B+-trees. We show that our solution exhibits a limited performance cost, thus resulting effectively usable in practice.