SoK: Cryptographically Protected Database Search

Protected database search systems cryptographically isolate the roles of reading from, writing to, and administering the database. This separation limits unnecessary administrator access and protects data in the case of system breaches. Since protected search was introduced in 2000, the area has grown rapidly; systems are offered by academia, start-ups, and established companies. However, there is no best protected search system or set of techniques. Design of such systems is a balancing act between security, functionality, performance, and usability. This challenge is made more difficult by ongoing database specialization, as some users will want the functionality of SQL, NoSQL, or NewSQL databases. This database evolution will continue, and the protected search community should be able to quickly provide functionality consistent with newly invented databases. At the same time, the community must accurately and clearly characterize the tradeoffs between different approaches. To address these challenges, we provide the following contributions: 1) An identification of the important primitive operations across database paradigms. We find there are a small number of base operations that can be used and combined to support a large number of database paradigms. 2) An evaluation of the current state of protected search systems in implementing these base operations. This evaluation describes the main approaches and tradeoffs for each base operation. Furthermore, it puts protected search in the context of unprotected search, identifying key gaps in functionality. 3) An analysis of attacks against protected search for different base queries. 4) A roadmap and tools for transforming a protected search system into a protected database, including an open-source performance evaluation platform and initial user opinions of protected search.Comment: 20 pages, to appear to IEEE Security and Privac

GraphSE2^2: An Encrypted Graph Database for Privacy-Preserving Social Search

In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE$^2$ provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE$^2$ with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE$^2$ is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search". It includes the security proof of the proposed scheme. If you want to cite our work, please cite the conference version of i

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

Searchable Encryption for Cloud and Distributed Systems

The vast development in information and communication technologies has spawned many new computing and storage architectures in the last two decades. Famous for its powerful computation ability and massive storage capacity, cloud services, including storage and computing, replace personal computers and software systems in many industrial applications. Another famous and influential computing and storage architecture is the distributed system, which refers to an array of machines or components geographically dispersed but jointly contributes to a common task, bringing premium scalability, reliability, and efficiency. Recently, the distributed cloud concept has also been proposed to benefit both cloud and distributed computing. Despite the benefits of these new technologies, data security and privacy are among the main concerns that hinder the wide adoption of these attractive architectures since data and computation are not under the control of the end-users in such systems. The traditional security mechanisms, e.g., encryption, cannot fit these new architectures since they would disable the fast access and retrieval of remote storage servers. Thus, an urgent question turns to be how to enable refined and efficient data retrieval on encrypted data among numerous records (i.e., searchable encryption) in the cloud and distributed systems, which forms the topic of this thesis. Searchable encryption technologies can be divided into Searchable Symmetric Encryption (SSE) and Public-key Encryption with Keyword Search (PEKS). The intrinsical symmetric key hinders data sharing since it is problematic and insecure to reveal one’s key to others. However, SSE outperforms PEKS due to its premium efficiency and is thus is prefered in a number of keyword search applications. Then multi-user SSE with rigorous and fine access control undoubtedly renders a satisfactory solution of both efficiency and security, which is the first problem worthy of our much attention. Second, functions and versatility play an essential role in a cloud storage application but it is still tricky to realize keyword search and deduplication in the cloud simultaneously. Large-scale data usually renders significant data redundancy and saving cloud storage resources turns to be inevitable. Existing schemes only facilitate data retrieval due to keywords but rarely consider other demands like deduplication. To be noted, trivially and hastily affiliating a separate deduplication scheme to the searchable encryption leads to disordered system architecture and security threats. Therefore, attention should be paid to versatile solutions supporting both keyword search and deduplication in the cloud. The third problem to be addressed is implementing multi-reader access for PEKS. As we know, PEKS was born to support multi-writers but enabling multi-readers in PEKS is challenging. Repeatedly encrypting the same keyword with different readers’ keys is not an elegant solution. In addition to keyword privacy, user anonymity coming with a multi-reader setting should also be formulated and preserved. Last but not least, existing schemes targeting centralized storage have not taken full advantage of distributed computation, which is considerable efficiency and fast response. Specifically, all testing tasks between searchable ciphertexts and trapdoor/token are fully undertaken by the only centralized cloud server, resulting in a busy system and slow response. With the help of distributed techniques, we may now look forward to a new turnaround, i.e., multiple servers jointly work to perform the testing with better efficiency and scalability. Then the intractable multi-writer/multi-reader mode supporting multi-keyword queries may also come true as a by-product. This thesis investigates searchable encryption technologies in cloud storage and distributed systems and spares effort to address the problems mentioned above. Our first work can be classified into SSE. We formulate the Multi-user Verifiable Searchable Symmetric Encryption (MVSSE) and propose a concrete scheme for multi-user access. It not only offers multi-user access and verifiability but also supports extension on updates as well as a non-single keyword index. Moreover, revocable access control is obtained that the search authority is validated each time a query is launched, different from existing mechanisms that once the search authority is granted, users can search forever. We give simulation-based proof, demonstrating our proposal possesses Universally Composable (UC)-security. Second, we come up with a redundancy elimination solution on top of searchable encryption. Following the keyword comparison approach of SSE, we formulate a hybrid primitive called Message-Locked Searchable Encryption (MLSE) derived in the way of SSE’s keyword search supporting keyword search and deduplication and present a concrete construction that enables multi-keyword query and negative keyword query as well as deduplication at a considerable small cost, i.e., the tokens are used for both search and deduplication. And it can further support Proof of Storage (PoS), testifying the content integrity in cloud storage. The semantic security is proved in Random Oracle Model using the game-based methodology. Third, as the branch of PEKS, the Broadcast Authenticated Encryption with Keyword Search (BAEKS) is proposed to bridge the gap of multi-reader access for PEKS, followed by a scheme. It not only resists Keyword Guessing Attacks (KGA) but also fills in the blank of anonymity. The scheme is proved secure under Decisional Bilinear Diffie-Hellman (DBDH) assumption in the Random Oracle Model. For distributed systems, we present a Searchable Encryption based on Efficient Privacy-preserving Outsourced calculation framework with Multiple keys (SE-EPOM) enjoying desirable features, which can be classified into PEKS. Instead of merely deploying a single server, multiple servers are employed to execute the test algorithm in our scheme jointly. The refined search, i.e., multi-keyword query, data confidentiality, and search pattern hiding, are realized. Besides, the multi-writer/multi-reader mode comes true. It is shown that under the distributed circumstance, much efficiency can be substantially achieved by our construction. With simulation-based proof, the security of our scheme is elaborated. All constructions proposed in this thesis are formally proven according to their corresponding security definitions and requirements. In addition, for each cryptographic primitive designed in this thesis, concrete schemes are initiated to demonstrate the availability and practicality of our proposal

Practical Isolated Searchable Encryption in a Trusted Computing Environment

Cloud computing has become a standard computational paradigm due its numerous advantages, including high availability, elasticity, and ubiquity. Both individual users and companies are adopting more of its services, but not without loss of privacy and control. Outsourcing data and computations to a remote server implies trusting its owners, a problem many end-users are aware. Recent news have proven data stored on Cloud servers is susceptible to leaks from the provider, third-party attackers, or even from government surveillance programs, exposing users’ private data. Different approaches to tackle these problems have surfaced throughout the years. Naïve solutions involve storing data encrypted on the server, decrypting it only on the client-side. Yet, this imposes a high overhead on the client, rendering such schemes impractical. Searchable Symmetric Encryption (SSE) has emerged as a novel research topic in recent years, allowing efficient querying and updating over encrypted datastores in Cloud servers, while retaining privacy guarantees. Still, despite relevant recent advances, existing SSE schemes still make a critical trade-off between efficiency, security, and query expressiveness, thus limiting their adoption as a viable technology, particularly in large-scale scenarios. New technologies providing Isolated Execution Environments (IEEs) may help improve SSE literature. These technologies allow applications to be run remotely with privacy guarantees, in isolation from other, possibly privileged, processes inside the CPU, such as the operating system kernel. Prominent example technologies are Intel SGX and ARM TrustZone, which are being made available in today’s commodity CPUs. In this thesis we study these new trusted hardware technologies in depth, while exploring their application to the problem of searching over encrypted data, primarily focusing in SGX. In more detail, we study the application of IEEs in SSE schemes, improving their efficiency, security, and query expressiveness. We design, implement, and evaluate three new SSE schemes for different query types, namely Boolean queries over text, similarity queries over image datastores, and multimodal queries over text and images. These schemes can support queries combining different media formats simultaneously, envisaging applications such as privacy-enhanced medical diagnosis and management of electronic-healthcare records, or confidential photograph catalogues, running without the danger of privacy breaks in Cloud-based provisioned services

MSIGT: Most Significant Index Generation Technique for cloud environment

Cloud Computing is a computing paradigm for delivering computational power, storage and applications as services via Internet on a pay-as-you-go basis to consumers. The data owner outsources local data to the public cloud server to reduce the cost of the data management. Critical data has to be encrypted to ensure privacy before outsourcing. The state-of-the-art SSE schemes search only over encrypted data through keywords, hence they do not provide effective data utilisation for large dataset files in cloud. We propose a Most Significant Index Generation Technique (MSIGT), that supports secure and efficient index generation time using a Most Significant Digit (MSD) radix sort. MSD radix sort is simple and faster in sorting array strings. A mathematical model is developed to encrypt the indexed keywords for secure index generation without the overhead of learning from the attacker/cloud provider. It is seen that the MSIGT scheme can reduce the cost of data on owner side to O(NT × 3) with a score calculation of O(NT). The proposed scheme is effective and efficient in comparison with the existing algorithms