A flexible framework for secure and efficient program obfuscation.

Outsourcing database as service instead of using in-house database management is a new trend emerging in a computing industry; there has been growing interest in outsourcing database services in both the commercial world and the research community. In this paper, we present analysis of non-concurrent model of fast single-database Private Information Retrieval (PIR) scheme for maintaining data privacy with data confidentiality using encryption algorithm like AES for Outsourced Database Service (ODBS) Model. In this model encryption method maintains data confidentiality and a utility that help to create PIR reply which maintains data privacy. In PIR Scheme data privacy is achieved by adding noise data into the result of a typical query which is called as PIR reply. Single-database PIR schemes are generally not practical because of its expensiveness from computational point of view. Here we propose a model that suggests the use of General-Purpose computation using Graphic Processing Units (GPGPU) commodity to process such type of computationally intensive operations. This model will help to achieve practical implementation of single-database PIR scheme which uses encryption algorithm to maintain data confidentiality as secondary goal and it serves to create database reply to maintain data privacy as primary goal. This paper shows some real time results that proves need of concurrency in PIR algorithms. It also describes the use of lattice based single-database PIR protocol with GPGPU as a processing unit to achieve high speed-up and hence, the performance of the system.

This paper is eligible for the Jack Keil Wolf ISIT Student Paper Award. In this work, a flexible and robust private information retrieval (PIR) scheme based on binary non-maximum distance separable (non-MDS) codes is considered. This combines previous works on PIR schemes based on transitive non-MDS codes on one hand, and PIR from MDS-coded Byzantine and nonresponsive servers on the other hand. More specifically, a PIR scheme employing binary Reed–Muller (RM) codes tolerant to colluding, Byzantine, and non-responsive servers is constructed, and bounds for the achievable rates are derived under certain conditions. The construction of such schemes turns out to be much more involved than for MDS codes. Namely, the binary query vectors have to be selected with great care to hit the desired information sets, which is technically challenging as will be shown.

SummaryIn big cities, the drivers face a major problem in identifying an optimal vacant parking space for their vehicles as the number of vehicles has rapidly grown over the recent years. This objective of determining the available parking space results in wastage of time, air pollution, and traffic congestion. Smart parking systems facilitate the driver to book parking slots and attain real‐time parking information. However, the existing smart parking solutions necessitate the disclosure of sensitive information like desired destination from the vehicle drivers. Moreover, the current smart parking solutions are highly centralized, making them vulnerable for launching privacy breaches by service providers and resulting in the issues of single‐point failure. In this paper, ring signature and improved multi‐transaction mode consortium blockchain‐based private information retrieval (RS‐IMTMCB‐PIR) scheme is proposed for privacy preserving in smart parking system. This RS‐IMTMCB‐PIR scheme initially utilizes an improved multi‐transaction mode consortium blockchain constructed by different number of parking lot owners in order to achieve maximized parking offers based on the factor of availability, transparency, and security. It incorporates an improved private information retrieval approach for protecting the location privacy of drivers and secretly retrieving the offers of parking from the improved multi‐transaction mode consortium blockchain. It further utilizes the benefits of ring signature for permitting the drivers in a potential anonymous authentication process that aids in available parking slot reservation. The simulation results of this proposed RS‐IMTMCB‐PIR scheme portrayed a predominant performance in ensuring maximized degree of drivers' privacy with reduced computation and communication overheads.

This paper presents an overview of the current single-database private information retrieval (PIR) schemes and proposes to explore the usage of these protocols with statistical databases. The vicinity of this research field with the one of Oblivious Transfer, and the different performance measures used for the last few years have resulted in re-discoveries and contradictory comparisons of performance in different publications. The contribution of this paper is twofold. First, we present the different schemes through the innovations they have brought to this field of research, which gives a global view of the evolution since the first of these schemes was presented by Kushilevitz and Ostrovsky in 1997. We know of no other survey of the current PIR protocols. We also compare the most representative of these schemes with a single set of communication performance measures. When compared to the usage of global communication cost as a single measure, we assert that this set simplifies the evaluation of the cost of using PIR and reveals the best adapted scheme to each situation. We conclude this overview and performance study by introducing some important issues resulting from PIR usage with statistical databases and highlighting some directions for further research.

The problem of private information retrieval (PIR) gets renewed attentions in recent years due to its information-theoretic reformulation and applications in distributed storage systems. Let M files be stored in a distributed storage system consisting of N servers, where each file is stored via an (N, K)-MDS code. A PIR scheme will allow a user to retrieve a specific file from the distributed storage system without revealing the identity of the file to any T colluding servers. PIR rate is defined as the number of symbols privately retrieved per one downloaded symbol and the supremum of all achievable rates is called the PIR capacity. The capacity has been solved for some degenerate cases, i.e. $$K=1$$ or $$T=1$$ . For the general case $$K\ge 2$$ and $$T\ge 2$$ , the exact PIR capacity remains unknown. In this paper we propose a general private information retrieval scheme for MDS coded databases with colluding servers achieving PIR rate $$(1+R+R^2+\cdots +R^{M-1})$$ , where $$R=1-\frac{{{N-T}\atopwithdelims ()K}}{{N\atopwithdelims ()K}}$$ . Our scheme captures the essence of the optimal schemes for degenerate cases. We also compare our scheme with some other known PIR schemes for non-degenerate cases. The advantages of our scheme include its independence of the property of the storage code and a better performance when the number of files M is small.

Database outsourcing as a service is a new trend emerging in the computing industry instead of managing database in-house. This introduces several security issues related to database. One of the important security requirements is privacy. A Private Information Retrieval protocol (PIR) allows user to retrieve an element from the database in such way that identity of that element is not get revealed by database server. In this project work, we present the optimized lattice based PIR schema. This proposed schema is based on use of different techniques like General Purpose Graphics Processing Unit (GPGPU) and cache like technology to reduce accessibility. The latest proposed PIR scheme deal with user privacy, use of GPGPU but left to focus on data privacy, data confidentiality and accessibility cost. In our approach our system focusing on issues like user privacy, data confidentiality and accessibility cost by using cache and computational overhead by using GPGPU. Thus searching time of proposed PIR protocol is minimized to number of records in the cache. Thus our proposed design improves the overall performance of PIR protocol.

Historically, privacy and efficiency have largely been at odds with one another when querying remote data sources: traditional query optimization techniques provide efficient retrieval by exporting information about the intension of a query to data sources, while private information retrieval (PIR) schemes hide query intension at the cost of extreme computational or communication overheads. Given the increasing use of Internet-scale distributed databases, exploring the spectrum between these two extremes is worthwhile. In this paper, we explore the degree to which query intension is leaked to remote data sources when a variety of existing query processing and view materialization techniques are used. We show that these information flows can be quantified in a concrete manner, and investigate the notion of privacy-aware distributed query evaluation. We then propose two techniques to improve the balance between privacy and efficiency when processing distributed queries, and discuss a number of interesting directions for future work.

Private Information Retrieval (PIR) allows to privately request a block of data from a database such that no information about the queried block is revealed to the database owner. With the rapid rise of cloud computing, data is often shared across multiple servers, making multi-server PIR a promising privacy-enhancing technology.In this paper, we introduce RAID-PIR, an efficient and simple multi-server PIR scheme, which has similar approach to RAID (Redundant Arrays of Inexpensive Disks) systems. Each server stores only a part of the database, its computational complexity depends only on this part, and multiple blocks can be queried efficiently in parallel. RAID-PIR improves efficiency over known PIR protocols, using only very efficient cryptographic primitives (pseudo-random generator). We demonstrate that RAID-PIR is practical and well-suited for cloud deployment as it reduces the communication as well as the computational workload per server.

Consider $N$ servers with replicated databases containing $M$ records. Suppose a user wants to privately retrieve one record by accessing the servers such that the identity of the retrieved record is secret against any up to $T$ servers. A scheme designed for this purpose is called a $T$ -private information retrieval ( $T$ -PIR) scheme. Three indexes are concerned for PIR schemes: (1) rate, indicating the amount of retrieved information per unit of downloaded data. The highest achievable rate is characterized by the capacity; (2) sub-packetization, reflecting the implementation complexity for linear schemes; (3) field size. We consider linear schemes over a finite field. In this paper, a general $T$ - PIR scheme simultaneously attaining the optimality of almost all of the three indexes is presented. Specifically, we design a linear capacity-achieving T-PIR scheme with sub-packetization $dn^{M-1}$ over a finite field $\mathbb{F}_{q}, q\geq N$ . The sub-packetization $dn^{M-1}$ , where $d=\mathrm{gcd}(N, T)$ and $n=N/d$ , has been proved to be optimal in our previous work. The field size is reduced by an exponential factor in our scheme comparing with existing capacity -achieving $T$ - PIR schemes.

An information theoretic approach to security and privacy called Secure And Private Information Retrieval (SAPIR) is introduced. SAPIR is applied to distributed data storage systems. In this approach, random combinations of all contents are stored across the network. Our coding approach is based on Random Linear Fountain (RLF) codes. To retrieve a content, a group of servers collaborate with each other to form a Reconstruction Group (RG). SAPIR achieves asymptotic perfect secrecy if at least one of the servers within an RG is not compromised. Further, a Private Information Retrieval (PIR) scheme based on random queries is proposed. The PIR approach ensures the users privately download their desired contents without the servers knowing about the requested contents indices. The proposed scheme is adaptive and can provide privacy against a significant number of colluding servers.

A private information retrieval (PIR) scheme on coded storage systems with colluding, byzantine, and non-responsive servers is presented. Furthermore, the scheme can also be used for symmetric PIR in the same setting. An explicit scheme using an [n, k] generalized Reed-Solomon storage code is designed, protecting against t-collusion and handling up to b byzantine and r non-responsive servers, when n ≥ n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1'</sup> =(ν+1)k+t+2b+r-1, for some integer ν ≥ 1. This scheme achieves a PIR rate of 1-[(k+2b+t+r-1)/(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">'</sup> -r)]. In the case where the capacity is known, namely when k=1, it is asymptotically capacity achieving as the number of files grows.

A lot of new applications in the field of electronic commerce require customers to pay small amounts of money to purchase low-value services, goods or pieces of information. These kinds of payments, called micropayments, provide a trade-off between efficiency and security requirements. In a previous work, we presented an efficient and secure micropayment scheme which fulfills both the security properties that guarantee no financial risk and the desired privacy for customers. In this paper we present a successful implementation of the scheme on the Android Platform and its performance evaluation to prove that the proposal is viable using current mobile devices. Several tests validate that our scheme can execute very fast payments with our simple but secure spending protocol, even when we need to use multiple tokens to pay for more expensive products. Moreover, we have proved that data storage requirements are low.

Enforcing security properties in a Cloud is a difficult task, which requires expertise. However, it is not the only security-related challenge met by a company migrating to a Cloud environment. Indeed, the tenant must also have assurance that the requested security properties have effectively been enforced. Therefore, the Cloud provider has to offer a way of monitoring the security. In this paper, we present a solution to express the assurance properties based on the security requirements of the tenant and to deploy these assurance properties. First, we introduce a language that expresses the assurance based on the tenant's security requirements. Secondly, we propose an infrastructure that deploys the assurance in a Cloud environment. This solution aims to be easy to use: the assurance directly results from the high-level expression of the tenant's security requirements, and no additional action is needed from the tenant. Consequently, we address one of the greatest drawback of security and assurance - the complexity of their configuration - while providing a complete assurance mechanism.

Reverse k-nearest neighbor (RkNN) queries are prevalent in location-based services to find those locations that have the query point as one of their k nearest neighbors. However, such query requires users to disclose the location of the query point to a service provider who might be untrustworthy. Previous attempts to preserve the privacy of RkNN queries are either based on weaker notions of privacy such as location cloaking or not efficient when k > 1. In this paper, we propose novel solutions based on the private information retrieval (PIR) mechanism to preserve the privacy of RkNN query points. Our solutions include server-side data indexing and client-side query processing methods to facilitate PIR which is an inherently expensive data retrieval mechanism. We experimentally evaluate our approach using real-world datasets and show that it preserves the location privacy of queries with reasonable computation and storage overhead.

In this paper, we propose a multi-client secure and efficient keyword search scheme for cloud storage, which is built upon distributed point function (DPF). Specifically, outsourced keyword indexes are encoded by using garbled bloom filter and cuckoo filter, instead of bloom filter adopted by most of the state-of-the-art DPF-based schemes. In this way, clients can apply cuckoo hashing into DPF and utilize a segmentation method to interact with cloud servers for keyword search, and servers can obliviously aggregate DPF evaluation results to perform the search. Accordingly, the computational complexity at server side can be significantly reduced. Furthermore, the proposed scheme preserves constant downlink overheads, which is more communication-efficient for multi-keyword conjunctive search. To achieve privacy preservation and access control for multiple clients, we propose a double encryption method to encrypt outsourced indexes and correspondingly put forward an authorization algorithm from set-constrained pseudorandom functions by which fine-grained search-authorized keys can be generated, and collusion attacks among clients are addressed by integrating Wegman-Carter message authentication codes and cover-free systems. Since our scheme is designed under both semi-honest and malicious models (i.e., malicious servers may return incorrect query results), we use a simulation-based proof to formally demonstrate its security properties. Finally, we develop a proof-of-concept prototype and perform extensive experiments to show our scheme's practicality and efficiency in terms of computation, communication, and storage overheads.