Search Condition-Hiding Query Evaluation on Encrypted Databases

Abstract

Private database query (PDQ) is a protocol between a client and a database server, designed for processing queries to encrypted databases. Specifically, PDQ enables a client to submit a search query and to learn a resulting set satisfying its search condition, without revealing sensitive information about a query statement. The whole query can be protected from the server, but for efficiency reasons known PDQ solutions generally consider to hide the constants only in a query statement. In this paper, we provide two fully homomorphic encryption (FHE)-based PDQ protocols that hide type of queries as well as the constants of a query statement. Particularly, our constructions focus on conjunctive, disjunctive, and threshold conjunctive queries. To this end, we first build a single compact logical expression to cover both conjunctive and disjunctive queries. On top of the logical expression, we design a PDQ protocol that enables to evaluate conjunctive and disjunctive queries without revealing any information on a given query. The second PDQ protocol comes from our observation that if a threshold conjunctive query has a particular threshold value, it results in either a conjunctive query or a disjunctive query. Because the PDQ protocol writes the three types of queries into a single polynomial expression, the resulting protocol can evaluate the three types of query statements without revealing any information on queries. To demonstrate their efficiency, we provide proof-of-concept implementation results of our proposed PDQ protocols. According to our rudimentary experiments, it takes 37.57 seconds to perform a query on 316 elements consisting of 16 attributes of 64 bits using Brakerski-Gentry-Vaikuntanathan's leveled FHE with SIMD techniques for 149-bit security, yielding an amortized rate of just 0.119 seconds per element. INDEX TERMS Private queries, encrypted database, homomorphic encryption.

PENDA: Privacy ENhanced Data Aggregator

“…These experiments show that the merging using the PENDA algorithm is faster than other techniques using FHE, FE or ORAM. A simple equality comparison on ciphertext encrypted with FHE [9] takes an order of seconds.…”

Cybersecurity Considerations in Disaster Recovery Planning

“…Strong encryption methods, like AES-256, make sure that even if data is stolen, it can't be read by people who aren't supposed to [27]. To keep encryption keys safe and stop people from decrypting them without permission [28], secure key management should be used. The NIST says that a hardware security module (HSM) is the best way to store and handle encryption keys because it is safer than software-based key management [29].…”

Efficient Private Conjunctive Query Protocol Over Encrypted Data

“…Here, information leakage is caused by revealing many of the record IDs of the data owner to the user before the intersection operation. After this, Kim et al [35] introduced another private database query protocol in which 0.119 seconds were required to process each record. They generated random databases that consisted of 16 keyword attributes with entries with maximum sizes of 48 or 64 bits.…”