A fast single server private information retrieval protocol with low communication cost

Existing single server Private Information Retrieval (PIR) protocols are far from practical. To be practical, a single server PIR protocol has to be both communicationally and computationally efficient. In this paper, we present a single server PIR protocol that has low communication cost and is much faster than existing protocols. A major building block of the PIR protocol in this paper is a tree-based compression scheme, which we call folding/unfolding. This compression scheme enables us to lower the communication complexity to O(loglogn). The other major building block is the BGV fully homomorphic encryption scheme. We show how we design the protocol to exploit the internal parallelism of the BGV scheme. This significantly reduces the server side computational overhead and makes our protocol much faster than the existing protocols. Our protocol can be further accelerated by utilising hardware parallelism. We have built a prototype of the protocol. We report on the performance of our protocol based on the prototype and compare it with the current most efficient protocols

Additively Homomorphic Encryption with d-Operand Multiplications

The search for encryption schemes that allow to evaluate functions (or circuits) over encrypted data has attracted a lot of attention since the seminal work on this subject by Rivest, Adleman and Dertouzos in 1978. In this work we define a theoretical object, chained encryption schemes, which allow an efficient evaluation of polynomials of degree d over encrypted data. Chained encryption schemes are generically constructed by concatenating cryptosystems with the appropriate homomorphic properties; such schemes are common in lattice-based cryptography. As a particular instantiation we propose a chained encryption scheme whose IND-CPA security is based on a worst-case/average-case reduction from uSVP

Supporting Concurrency and Multiple Indexes in Private Access to Outsourced Data

Data outsourcing has recently emerged as a successful solution allowing individuals and organizations to delegate data and service management to external third parties. A major challenge in the data outsourcing scenario is how to guarantee proper privacy protection against the external server. Recent promising approaches rely on the organization of data in indexing structures that use encryption and the dynamic allocation of encrypted data to physical blocks for destroying the otherwise static relationship between data and the blocks in which they are stored. However, dynamic data allocation implies the need to re-write blocks at every read access, thus requesting exclusive locks that can affect concurrency. Also, these solutions only support search conditions on the values of the attribute used for building the indexing structure. In this paper, we present an approach that overcomes such limitations by extending the recently proposed shuffle index structure with support for concurrency and multiple indexes. Support for concurrency relies on the use of several differential versions of the data index that are periodically reconciled and applied to the main data structure. Support for multiple indexes relies on the definition of secondary shuffle indexes that are then combined with the primary index in a single data structure whose content and allocation is unintelligible to the server. We show how using such differential versions and combined index structure guarantees privacy, provides support for concurrent accesses and multiple search conditions, and considerably increases the performance of the system and the applicability of the proposed solution

Data privacy

Data privacy studies methods, tools, and theory to avoid the disclosure of sensitive information. Its origin is in statistics with the goal to ensure the confidentiality of data gathered from census and questionnaires. The topic was latter introduced in computer science and more particularly in data mining, where due to the large amount of data currently available, has attracted the interest of researchers, practitioners, and companies. In this paper we will review the main topics related to data privacy and privacy-enhancing technologies

Confidential database-as-a-service approaches: taxonomy and survey

Outsourcing data to external providers has gained momentum with the advent of cloud computing. Encryption allows data confidentiality to be preserved when outsourcing data to untrusted external providers that may be compromised by attackers. However, encryption has to be applied in a way that still allows the external provider to evaluate queries received from the client. Even though confidential database-as-a-service (DaaS) is still an active field of research, various techniques already address this problem, which we call confidentiality preserving indexing approaches (CPIs). CPIs make individual tradeoffs between the functionality provided, i.e., the types of queries that can be evaluated, the level of protection achieved, and performance.In this paper, we present a taxonomy of requirements that CPIs have to satisfy in deployment scenarios including the required functionality and the required level of protection against various attackers. We show that the taxonomy?s underlying principles serve as a methodology to assess CPIs, primarily by linking attacker models to CPI security properties. By use of this methodology, we survey and assess ten previously proposed CPIs. The resulting CPI catalog can help the reader who would like to build DaaS solutions to facilitate DaaS design decisions while the proposed taxonomy and methodology can also be applied to assess upcoming CPI approaches