A novel secure scheme for supporting complex SQL queries over encrypted databases in cloud computing

With the advance of database-as-a-service (DaaS) and cloud computing, increasingly more data owners are motivated to outsource their data to cloud database for great convenience and economic savings. Many encryption schemes have been proposed to process SQL queries over encrypted data in the database. In order to obtain the desired data, the SQL queries contain some statements to describe the requirement, e.g., arithmetic and comparison operators (+, -, ×, , and =). However, to support different operators (+, -, ×, , and =) in SQL queries over encrypted data, multiple encryption schemes need to be combined and adjusted to work together. Moreover, repeated encryptions will reduce the efficiency of execution. This paper presents a practical and secure homomorphic order-preserving encryption (FHOPE) scheme, which allows cloud server to perform complex SQL queries that contain different operators (such as addition, multiplication, order comparison, and equality checks) over encrypted data without repeated encryption. These operators are data interoperable, so they can be combined to formulate complex SQL queries. We conduct security analysis and efficiency evaluation of the proposed scheme FHOPE. The experiment results show that, compared with the existing approaches, the FHOPE scheme incurs less overhead on computation and communication. It is suitable for large batch complex SQL queries over encrypted data in cloud environment

Chameleon: A Secure Cloud-Enabled and Queryable System with Elastic Properties

There are two dominant themes that have become increasingly more important in our technological society. First, the recurrent use of cloud-based solutions which provide infrastructures, computation platforms and storage as services. Secondly, the use of applicational large logs for analytics and operational monitoring in critical systems. Moreover, auditing activities, debugging of applications and inspection of events generated by errors or potential unexpected operations - including those generated as alerts by intrusion detection systems - are common situations where extensive logs must be analyzed, and easy access is required. More often than not, a part of the generated logs can be deemed as sensitive, requiring a privacy-enhancing and queryable solution. In this dissertation, our main goal is to propose a novel approach of storing encrypted critical data in an elastic and scalable cloud-based storage, focusing on handling JSONbased ciphered documents. To this end, we make use of Searchable and Homomorphic Encryption methods to allow operations on the ciphered documents. Additionally, our solution allows for the user to be near oblivious to our system’s internals, providing transparency while in use. The achieved end goal is a unified middleware system capable of providing improved system usability, privacy, and rich querying over the data. This previously mentioned objective is addressed while maintaining server-side auditable logs, allowing for searchable capabilities by the log owner or authorized users, with integrity and authenticity proofs. Our proposed solution, named Chameleon, provides rich querying facilities on ciphered data - including conjunctive keyword, ordering correlation and boolean queries - while supporting field searching and nested aggregations. The aforementioned operations allow our solution to provide data analytics upon ciphered JSON documents, using Elasticsearch as our storage and search engine.O uso recorrente de soluções baseadas em nuvem tornaram-se cada vez mais importantes na nossa sociedade. Tais soluções fornecem infraestruturas, computação e armazenamento como serviços, para alem do uso de logs volumosos de sistemas e aplicações para análise e monitoramento operacional em sistemas críticos. Atividades de auditoria, debugging de aplicações ou inspeção de eventos gerados por erros ou possíveis operações inesperadas - incluindo alertas por sistemas de detecção de intrusão - são situações comuns onde logs extensos devem ser analisados com facilidade. Frequentemente, parte dos logs gerados podem ser considerados confidenciais, exigindo uma solução que permite manter a confidencialidades dos dados durante procuras. Nesta dissertação, o principal objetivo é propor uma nova abordagem de armazenar logs críticos num armazenamento elástico e escalável baseado na cloud. A solução proposta suporta documentos JSON encriptados, fazendo uso de Searchable Encryption e métodos de criptografia homomórfica com provas de integridade e autenticação. O objetivo alcançado é um sistema de middleware unificado capaz de fornecer privacidade, integridade e autenticidade, mantendo registos auditáveis do lado do servidor e permitindo pesquisas pelo proprietário dos logs ou usuários autorizados. A solução proposta, Chameleon, visa fornecer recursos de consulta atuando em cima de dados cifrados - incluindo queries conjuntivas, de ordenação e booleanas - suportando pesquisas de campo e agregações aninhadas. As operações suportadas permitem à nossa solução suportar data analytics sobre documentos JSON cifrados, utilizando o Elasticsearch como armazenamento e motor de busca

CryptDB: A Practical Encrypted Relational DBMS

CryptDB is a DBMS that provides provable and practical privacy in the face of a compromised database server or curious database administrators. CryptDB works by executing SQL queries over encrypted data. At its core are three novel ideas: an SQL-aware encryption strategy that maps SQL operations to encryption schemes, adjustable query-based encryption which allows CryptDB to adjust the encryption level of each data item based on user queries, and onion encryption to efficiently change data encryption levels. CryptDB only empowers the server to execute queries that the users requested, and achieves maximum privacy given the mix of queries issued by the users. The database server fully evaluates queries on encrypted data and sends the result back to the client for final decryption; client machines do not perform any query processing and client-side applications run unchanged. Our evaluation shows that CryptDB has modest overhead: on the TPC-C benchmark on Postgres, CryptDB reduces throughput by 27% compared to regular Postgres. Importantly, CryptDB does not change the innards of existing DBMSs: we realized the implementation of CryptDB using client-side query rewriting/encrypting, user-defined functions, and server-side tables for public key information. As such, CryptDB is portable; porting CryptDB to MySQL required changing 86 lines of code, mostly at the connectivity layer

d'Artagnan: a trusted NoSQL database on untrusted clouds

Privacy sensitive applications that store confidential information such as personal identifiable data or medical records have strict security concerns. These concerns hinder the adoption of the cloud. With cloud providers under the constant threat of malicious attacks, a single successful breach is sufficient to exploit any valuable information and disclose sensitive data. Existing privacy-aware databases mitigate some of these concerns, but sill leak critical information that can potently compromise the entire system's security. This paper proposes d'Artagnan, the first privacy-aware multi-cloud NoSQL database framework that renders database leaks worthless. The framework stores data as encrypted secrets in multiple clouds such that i) a single data breach cannot break the database's confidentiality and ii) queries are processed on the server-side without leaking any sensitive information. d'Artagnan is evaluated with industry-standard benchmark on market-leading cloud providers.This work is financed by National Funds through thePortuguese funding agency, FCT - Fundação para a Ciência ea Tecnologia within project: UID/EEA/50014/2019. This workis financed by National Funds through the Portuguese fundingagency, FCT - Fundação para a Ciência e a Tecnologia withthe grant: SFRH/BD/142704/201

Privacy-preserving key-value store

Cloud computing is arguably the foremost delivery platform for data storage and data processing. It turned computing into a utility based service that provides consumers and enterprises with on-demand access to computing resources. Although advantageous, there is an inherent lack of control over the hardware in the cloud computing model, this may constitute an increased privacy and security risk. Multiple encrypted database systems have emerged in recent years, they provide the functionality of regular databases but without compromising data confidentiality. These systems leverage novel encryption schemes such as homomorphic and searchable encryp tion. However, many of these proposals focus on extending existing centralized systems that are very difficult to scale, and offer poor performance in geo-replicated scenarios. We propose a scalable, highly available, and geo-replicated privacy-preserving key value store. A system that provides its users with secure data types meant to be replicated, along with a rich query interface with configurable privacy that enables one to issue secure and somewhat complex queries. We accompany our proposal with an implementation of a privacy-preserving client library for AntidoteDB, a geo-replicated key-value store. We also extend the AntidoteDB’s query language interface by adding support for secure SQL-like queries with configurable privacy. Experimental evaluations show that our proposals offer a feasible solution to practical applications that wish to improve their privacy and confidentiality