An evaluation between Bloom Filter join and PERF join in Distributed Query Processing

Nowadays, with the explosion of information and the telecommunication era\u27s coming, more and more huge applications encourage decentralization of data while accessing data from different sites [HFB00]. The process of retrieving data from different sites called Distributed Query Processing. The objective of distributed query optimization is to find the most cost-effective of executing query across the network [OV99]. Semijoin [BC81] [BG+81] is known as an effective operator to eliminate the tuples of a relation which are not contributive to a query. 2-way semijoin [KR87] is an extended version of semijoin which not only performs forward reduction like traditional semijoin does, but also provides backward reduction always in cost-effective way. Bloom Filter[B70] and PERF [LR95] are 2 filter based techniques which use a bit vector to represent of the original join attributes projection during the data transmission. Compare with generating a bit array with hash function in bloom filter, Perf join is based on the tuples scan order to avoid losing information caused by hash collision. In the thesis, we will apply both bloom filter and pert on 2-way semijoin algorithms to reduce transmission cost of distributed queries. Performance of propose algorithms will compare against each others and IFS (Initial Feasible Solution) through amount of experiments. \u27Keywords:\u27 Distributed Query Processing, Semijoin, Bloom Filter, Perf Join

Privacy-Preserving Secret Shared Computations using MapReduce

Data outsourcing allows data owners to keep their data at \emph{untrusted} clouds that do not ensure the privacy of data and/or computations. One useful framework for fault-tolerant data processing in a distributed fashion is MapReduce, which was developed for \emph{trusted} private clouds. This paper presents algorithms for data outsourcing based on Shamir's secret-sharing scheme and for executing privacy-preserving SQL queries such as count, selection including range selection, projection, and join while using MapReduce as an underlying programming model. Our proposed algorithms prevent an adversary from knowing the database or the query while also preventing output-size and access-pattern attacks. Interestingly, our algorithms do not involve the database owner, which only creates and distributes secret-shares once, in answering any query, and hence, the database owner also cannot learn the query. Logically and experimentally, we evaluate the efficiency of the algorithms on the following parameters: (\textit{i}) the number of communication rounds (between a user and a server), (\textit{ii}) the total amount of bit flow (between a user and a server), and (\textit{iii}) the computational load at the user and the server.\BComment: IEEE Transactions on Dependable and Secure Computing, Accepted 01 Aug. 201

Lattice-Based Group Signatures: Achieving Full Dynamicity (and Deniability) with Ease

In this work, we provide the first lattice-based group signature that offers full dynamicity (i.e., users have the flexibility in joining and leaving the group), and thus, resolve a prominent open problem posed by previous works. Moreover, we achieve this non-trivial feat in a relatively simple manner. Starting with Libert et al.'s fully static construction (Eurocrypt 2016) - which is arguably the most efficient lattice-based group signature to date, we introduce simple-but-insightful tweaks that allow to upgrade it directly into the fully dynamic setting. More startlingly, our scheme even produces slightly shorter signatures than the former, thanks to an adaptation of a technique proposed by Ling et al. (PKC 2013), allowing to prove inequalities in zero-knowledge. Our design approach consists of upgrading Libert et al.'s static construction (EUROCRYPT 2016) - which is arguably the most efficient lattice-based group signature to date - into the fully dynamic setting. Somewhat surprisingly, our scheme produces slightly shorter signatures than the former, thanks to a new technique for proving inequality in zero-knowledge without relying on any inequality check. The scheme satisfies the strong security requirements of Bootle et al.'s model (ACNS 2016), under the Short Integer Solution (SIS) and the Learning With Errors (LWE) assumptions. Furthermore, we demonstrate how to equip the obtained group signature scheme with the deniability functionality in a simple way. This attractive functionality, put forward by Ishida et al. (CANS 2016), enables the tracing authority to provide an evidence that a given user is not the owner of a signature in question. In the process, we design a zero-knowledge protocol for proving that a given LWE ciphertext does not decrypt to a particular message