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

A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage

Security has become a significant concern with the increased popularity of cloud storage services. It comes with the vulnerability of being accessed by third parties. Security is one of the major hurdles in the cloud server for the user when the user data that reside in local storage is outsourced to the cloud. It has given rise to security concerns involved in data confidentiality even after the deletion of data from cloud storage. Though, it raises a serious problem when the encrypted data needs to be shared with more people than the data owner initially designated. However, searching on encrypted data is a fundamental issue in cloud storage. The method of searching over encrypted data represents a significant challenge in the cloud. Searchable encryption allows a cloud server to conduct a search over encrypted data on behalf of the data users without learning the underlying plaintexts. While many academic SE schemes show provable security, they usually expose some query information, making them less practical, weak in usability, and challenging to deploy. Also, sharing encrypted data with other authorized users must provide each document's secret key. However, this way has many limitations due to the difficulty of key management and distribution. We have designed the system using the existing cryptographic approaches, ensuring the search on encrypted data over the cloud. The primary focus of our proposed model is to ensure user privacy and security through a less computationally intensive, user-friendly system with a trusted third party entity. To demonstrate our proposed model, we have implemented a web application called CryptoSearch as an overlay system on top of a well-known cloud storage domain. It exhibits secure search on encrypted data with no compromise to the user-friendliness and the scheme's functional performance in real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table

Privacy-preserving query processing on health data

Due to the huge volume of digital data and the underlying complexity of data management, people and companies are motivated to outsource their computational requirements to the cloud. A significant portion of these productions are used in health applications. While popular cloud computing platforms provide flexible and low-priced solutions, unfortunately, they do so with little support for data security and privacy. This shortcoming clearly threatens sensitive data in cloud platforms. This is especially true for health information, which should always be adequately secured via encryption. Providing secure storage and access to health information that is generated by systems or used in applications, is the main challenge in today’s health care systems. As a result, owners of sensitive information may hesitate in purchasing such services, given the risks associated with the unauthorized access to their data. Considering this problem, researchers have recommended applying encryption algorithms. Data owners never disclose encryption keys in order to keep their encrypted data secure. Because cloud platforms can not search in data which is encrypted with regular encryption algorithms, it is supposed that data owners conceal their secrets with searchable encryption algorithms. Searchable encryption is a family of cryptographic protocols that facilitate private keyword searches directly on encrypted data. These protocols allow data owners to upload their encrypted data to the cloud, while retaining the ability to query over uploaded data. In this project, we focus on symmetric searchable encryption schemes, as well as apply an efficient searchable encryption scheme which supports multi-keyword searches to provide a privacy preserving keyword search framework for health data. Our framework applies a recent secure searchable encryption scheme and employs an inverted indexing structure in order to process queries in a privacy-preserving manner

Privacy-Enhanced Query Processing in a Cloud-Based Encrypted DBaaS (Database as a Service)

In this dissertation, we researched techniques to support trustable and privacy enhanced solutions for on-line applications accessing to “always encrypted” data in remote DBaaS (data-base-as-a-service) or Cloud SQL-enabled backend solutions. Although solutions for SQL-querying of encrypted databases have been proposed in recent research, they fail in providing: (i) flexible multimodal query facilities includ ing online image searching and retrieval as extended queries to conventional SQL-based searches, (ii) searchable cryptographic constructions for image-indexing, searching and retrieving operations, (iii) reusable client-appliances for transparent integration of multi modal applications, and (iv) lack of performance and effectiveness validations for Cloud based DBaaS integrated deployments. At the same time, the study of partial homomorphic encryption and multimodal searchable encryption constructions is yet an ongoing research field. In this research direction, the need for a study and practical evaluations of such cryptographic is essential, to evaluate those cryptographic methods and techniques towards the materialization of effective solutions for practical applications. The objective of the dissertation is to design, implement and perform experimental evaluation of a security middleware solution, implementing a client/client-proxy/server appliance software architecture, to support the execution of applications requiring on line multimodal queries on “always encrypted” data maintained in outsourced cloud DBaaS backends. In this objective we include the support for SQL-based text-queries enhanced with searchable encrypted image-retrieval capabilities. We implemented a prototype of the proposed solution and we conducted an experimental benchmarking evaluation, to observe the effectiveness, latency and performance conditions in support ing those queries. The dissertation addressed the envisaged security middleware solution, as an experimental and usable solution that can be extended for future experimental testbench evaluations using different real cloud DBaaS deployments, as offered by well known cloud-providers.Nesta dissertação foram investigadas técnicas para suportar soluções com garantias de privacidade para aplicações que acedem on-line a dados que são mantidos sempre cifrados em nuvens que disponibilizam serviços de armazenamento de dados, nomeadamente soluções do tipo bases de dados interrogáveis por SQL. Embora soluções para suportar interrogações SQL em bases de dados cifradas tenham sido propostas anteriormente, estas falham em providenciar: (i) capacidade de efectuar pesquisas multimodais que possam incluir pesquisa combinada de texto e imagem com obtenção de imagens online, (ii) suporte de privacidade com base em construções criptograficas que permitam operações de indexacao, pesquisa e obtenção de imagens como dados cifrados pesquisáveis, (iii) suporte de integração para aplicações de gestão de dados em contexto multimodal, e (iv) ausência de validações experimentais com benchmarking dobre desempenho e eficiência em soluções DBaaS em que os dados sejam armazenados e manipulados na sua forma cifrada. A pesquisa de soluções de privacidade baseada em primitivas de cifras homomórficas parciais, tem sido vista como uma possível solução prática para interrogação de dados e bases de dados cifradas. No entanto, este é ainda um campo de investigação em desenvolvimento. Nesta direção de investigação, a necessidade de estudar e efectuar avaliações experimentais destas primitivas em bibliotecas de cifras homomórficas, reutilizáveis em diferentes contextos de aplicação e como solução efetiva para uso prático mais generalizado, é um aspeto essencial. O objectivo da dissertação e desenhar, implementar e efectuar avalições experimentais de uma proposta de solução middleware para suportar pesquisas multimodais em bases de dados mantidas cifradas em soluções de nuvens de armazenamento. Esta proposta visa a concepção e implementação de uma arquitectura de software client/client-proxy/server appliance para suportar execução eficiente de interrogações online sobre dados cifrados, suportando operações multimodais sobre dados mantidos protegidos em serviços de nuvens de armazenamento. Neste objectivo incluímos o suporte para interrogações estendidas de SQL, com capacidade para pesquisa e obtenção de dados cifrados que podem incluir texto e pesquisa de imagens por similaridade. Foi implementado um prototipo da solução proposta e foi efectuada uma avaliação experimental do mesmo, para observar as condições de eficiencia, latencia e desempenho do suporte dessas interrogações. Nesta avaliação incluímos a análise experimental da eficiência e impacto de diferentes construções criptográficas para pesquisas cifradas (searchable encryption) e cifras parcialmente homomórficas e que são usadas como componentes da solução proposta. A dissertaçao aborda a soluçao de seguranca projectada, como uma solução experimental que pode ser estendida e utilizavel para futuras aplcações e respetivas avaliações experimentais. Estas podem vir a adoptar soluções do tipo DBaaS, oferecidos como serviços na nuvem, por parte de diversos provedores ou fornecedores

The Secure Link Prediction Problem

Link Prediction is an important and well-studied problem for social networks. Given a snapshot of a graph, the link prediction problem predicts which new interactions between members are most likely to occur in the near future. As networks grow in size, data owners are forced to store the data in remote cloud servers which reveals sensitive information about the network. The graphs are therefore stored in encrypted form. We study the link prediction problem on encrypted graphs. To the best of our knowledge, this secure link prediction problem has not been studied before. We use the number of common neighbors for prediction. We present three algorithms for the secure link prediction problem. We design prototypes of the schemes and formally prove their security. We execute our algorithms in real-life datasets.Comment: This has been accepted for publication in Advances in Mathematics of Communications (AMC) journa

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

Do not tell me what I cannot do! (The constrained device shouted under the cover of the fog): Implementing Symmetric Searchable Encryption on Constrained Devices (Extended Version)

Symmetric Searchable Encryption (SSE) allows the outsourcing of encrypted data to possible untrusted third party services while simultaneously giving the opportunity to users to search over the encrypted data in a secure and privacy-preserving way. Currently, the majority of SSE schemes have been designed to fit a typical cloud service scenario where users (clients) encrypt their data locally and upload them securely to a remote location. While this scenario fits squarely the cloud paradigm, it cannot apply to the emerging field of Internet of Things (IoT). This is due to the fact that the performance of most of the existing SSE schemes has been tested using powerful machines and not the constrained devices used in IoT services. The focus of this paper is to prove that SSE schemes can, under certain circumstances, work on constrained devices and eventually be adopted by IoT services. To this end, we designed and implemented a forward private dynamic SSE scheme that can run smoothly on resource-constrained devices. To do so, we adopted a fog node scenario where edge (constrained) devices sense data, encrypt them locally and use the capabilities of fog nodes to store sensed data in a remote location (the cloud). Consequently, end users can search for specific keywords over the stored ciphertexts without revealing anything about their content. Our scheme achieves efficient computational operations and supports the multi-client model. The performance of the scheme is evaluated by conducting extensive experiments. Finally, the security of the scheme is proven through a theoretical analysis that considers the existence of a malicious adversary

MUSES: Efficient Multi-User Searchable Encrypted Database

Searchable encrypted systems enable privacy-preserving keyword search on encrypted data. Symmetric Searchable Encryption (SSE) achieves high security (e.g., forward privacy) and efficiency (i.e., sublinear search), but it only supports single-user. Public Key Searchable Encryption (PEKS) supports multi-user settings, however, it suffers from inherent security limitations such as being vulnerable to keyword-guessing attacks and the lack of forward privacy. Recent work has combined SSE and PEKS to achieve the best of both worlds: support multi-user settings, provide forward privacy while having sublinear complexity. However, despite their elegant design, the existing hybrid scheme inherits some of the security limitations of the underlying paradigms (e.g., patterns leakage, keyword-guessing) and might not be suitable for certain applications due to costly public-key operations (e.g., bilinear pairing). In this paper, we propose MUSES, a new multi-user encrypted search scheme that addresses the limitations in the existing hybrid design, while offering user efficiency. Specifically, MUSES permits multi-user functionalities (reader/writer separation, permission revocation), prevents keyword-guessing attacks, protects search/result patterns, achieves forward/backward privacy, and features minimal user overhead. In MUSES, we demonstrate a unique incorporation of various state-of-the-art distributed cryptographic protocols including Distributed Point Function, Distributed PRF, and Secret-Shared Shuffle. We also introduce a new oblivious shuffle protocol for the general -party setting with dishonest majority, which can be of independent interest. Our experimental results indicated that the keyword search in our scheme is two orders of magnitude faster with 13× lower user bandwidth overhead than the state-of-the-art