Computing FO-Rewritings in $$\mathcal{EL}$$ in Practice: From Atomic to Conjunctive Queries

Responsibility Analysis for Lineages of Conjunctive Queries with Inequalities

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2013.58 ◽

2014 ◽

Vol 26 (6) ◽

pp. 1532-1543 ◽

Cited By ~ 3

Author(s):

Biao Qin ◽

Shan Wang ◽

Xiaofang Zhou ◽

Xiaoyong Du

Keyword(s):

Conjunctive Queries

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Semantic Optimization in Tractable Classes of Conjunctive Queries

ACM SIGMOD Record ◽

10.1145/3137586.3137588 ◽

2017 ◽

Vol 46 (2) ◽

pp. 5-17 ◽

Cited By ~ 2

Author(s):

Pablo Barceló ◽

Andreas Pieris ◽

Miguel Romero

Keyword(s):

Conjunctive Queries

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Efficient Private Conjunctive Query Protocol Over Encrypted Data

Cryptography ◽

10.3390/cryptography5010002 ◽

2021 ◽

Vol 5 (1) ◽

pp. 2

Author(s):

Tushar Kanti Saha ◽

Takeshi Koshiba

Keyword(s):

Homomorphic Encryption ◽

Data Access ◽

Conjunctive Query ◽

Conjunctive Queries ◽

Private Data ◽

Binary Format ◽

Main Technique ◽

Batch Technique ◽

Outsourced Database ◽

Packing Method

Conjunctive queries play a key role in retrieving data from a database. In a database, a query containing many conditions in its predicate, connected by an “and/&/∧” operator, is called a conjunctive query. Retrieving the outcome of a conjunctive query from thousands of records is a heavy computational task. Private data access to an outsourced database is required to keep the database secure from adversaries; thus, private conjunctive queries (PCQs) are indispensable. Cheon, Kim, and Kim (CKK) proposed a PCQ protocol using search-and-compute circuits in which they used somewhat homomorphic encryption (SwHE) for their protocol security. As their protocol is far from being able to be used practically, we propose a practical batch private conjunctive query (BPCQ) protocol by applying a batch technique for processing conjunctive queries over an outsourced database, in which both database and queries are encoded in binary format. As a main technique in our protocol, we develop a new data-packing method to pack many data into a single polynomial with the batch technique. We further enhance the performances of the binary-encoded BPCQ protocol by replacing the binary encoding with N-ary encoding. Finally, we compare the performance to assess the results obtained by the binary-encoded BPCQ protocol and the N-ary-encoded BPCQ protocol.

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