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

Still Wrong Use of Pairings in Cryptography

Several pairing-based cryptographic protocols are recently proposed with a wide variety of new novel applications including the ones in emerging technologies like cloud computing, internet of things (IoT), e-health systems and wearable technologies. There have been however a wide range of incorrect use of these primitives. The paper of Galbraith, Paterson, and Smart (2006) pointed out most of the issues related to the incorrect use of pairing-based cryptography. However, we noticed that some recently proposed applications still do not use these primitives correctly. This leads to unrealizable, insecure or too inefficient designs of pairing-based protocols. We observed that one reason is not being aware of the recent advancements on solving the discrete logarithm problems in some groups. The main purpose of this article is to give an understandable, informative, and the most up-to-date criteria for the correct use of pairing-based cryptography. We thereby deliberately avoid most of the technical details and rather give special emphasis on the importance of the correct use of bilinear maps by realizing secure cryptographic protocols. We list a collection of some recent papers having wrong security assumptions or realizability/efficiency issues. Finally, we give a compact and an up-to-date recipe of the correct use of pairings.Comment: 25 page

Cryptographic Techniques for Securing Data in the Cloud

El paradigma de la computació al núvol proporciona accés remot a potents infraestructures a cost reduït. Tot i que l’adopció del núvol ofereix nombrosos beneficis, la migració de dades sol requerir un alt nivell de confiança en el proveïdor de serveis i introdueix problemes de privacitat. En aquesta tesi es dissenyen tècniques per a permetre a usuaris del núvol protegir un conjunt de dades externalitzades. Les solucions proposades emanen del projecte H2020 de la Comissió Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Els problemes explorats són la cerca sobre dades xifrades, la delegació de càlculs d’interpolació, els esquemes de compartició de secrets i la partició de dades. Primerament, s’estudia el problema de la cerca sobre dades xifrades mitjançant els esquemes de xifrat cercable simètric (SSE), i es desenvolupen tècniques que permeten consultes per rangs dos-dimensionals a SSE. També es tracta el mateix problema utilitzant esquemes de xifrat cercable de clau pública (PEKS), i es presenten esquemes PEKS que permeten consultes conjuntives i de subconjunt. En aquesta tesi també s’aborda la delegació privada de computacions Kriging. Kriging és un algoritme d’interpolació espaial dissenyat per a aplicacions geo-estadístiques. Es descriu un mètode per a delegar interpolacions Kriging de forma privada utilitzant xifrat homomòrfic. Els esquemes de compartició de secrets són una primitiva fonamental en criptografia, utilitzada a diverses solucions orientades al núvol. Una de les mesures d’eficiència relacionades més importants és la taxa d’informació òptima. Atès que calcular aquesta taxa és generalment difícil, s’obtenen propietats que faciliten la seva descripció. Finalment, es tracta el camp de la partició de dades per a la protecció de la privacitat. Aquesta tècnica protegeix la privacitat de les dades emmagatzemant diversos fragments a diferents ubicacions. Aquí s’analitza aquest problema des d’un punt de vista combinatori, fitant el nombre de fragments i proposant diversos algoritmes.El paradigma de la computación en la nube proporciona acceso remoto a potentes infraestructuras a coste reducido. Aunque la adopción de la nube ofrece numerosos beneficios, la migración de datos suele requerir un alto nivel de confianza en el proveedor de servicios e introduce problemas de privacidad. En esta tesis se diseñan técnicas para permitir a usuarios de la nube proteger un conjunto de datos externalizados. Las soluciones propuestas emanan del proyecto H2020 de la Comisión Europea “CLARUS: User-Centered Privacy and Security in the Cloud”. Los problemas explorados son la búsqueda sobre datos cifrados, la delegación de cálculos de interpolación, los esquemas de compartición de secretos y la partición de datos. Primeramente, se estudia el problema de la búsqueda sobre datos cifrados mediante los esquemas de cifrado simétrico buscable (SSE), y se desarrollan técnicas para permitir consultas por rangos dos-dimensionales en SSE. También se trata el mismo problema utilizando esquemas de cifrado buscable de llave pública (PEKS), y se presentan esquemas que permiten consultas conyuntivas y de subconjunto. Adicionalmente, se aborda la delegación privada de computaciones Kriging. Kriging es un algoritmo de interpolación espacial diseñado para aplicaciones geo-estadísticas. Se describe un método para delegar interpolaciones Kriging privadamente utilizando técnicas de cifrado homomórfico. Los esquemas de compartición de secretos son una primitiva fundamental en criptografía, utilizada en varias soluciones orientadas a la nube. Una de las medidas de eficiencia más importantes es la tasa de información óptima. Dado que calcular esta tasa es generalmente difícil, se obtienen propiedades que facilitan su descripción. Por último, se trata el campo de la partición de datos para la protección de la privacidad. Esta técnica protege la privacidad de los datos almacenando varios fragmentos en distintas ubicaciones. Analizamos este problema desde un punto de vista combinatorio, acotando el número de fragmentos y proponiendo varios algoritmos.The cloud computing paradigm provides users with remote access to scalable and powerful infrastructures at a very low cost. While the adoption of cloud computing yields a wide array of benefits, the act of migrating to the cloud usually requires a high level of trust in the cloud service provider and introduces several security and privacy concerns. This thesis aims at designing user-centered techniques to secure an outsourced data set in cloud computing. The proposed solutions stem from the European Commission H2020 project “CLARUS: User-Centered Privacy and Security in the Cloud”. The explored problems are searching over encrypted data, outsourcing Kriging interpolation computations, secret sharing and data splitting. Firstly, the problem of searching over encrypted data is studied using symmetric searchable encryption (SSE) schemes, and techniques are developed to enable efficient two-dimensional range queries in SSE. This problem is also studied through public key encryption with keyword search (PEKS) schemes, efficient PEKS schemes achieving conjunctive and subset queries are proposed. This thesis also aims at securely outsourcing Kriging computations. Kriging is a spatial interpolation algorithm designed for geo-statistical applications. A method to privately outsource Kriging interpolation is presented, based in homomorphic encryption. Secret sharing is a fundamental primitive in cryptography, used in many cloud-oriented techniques. One of the most important efficiency measures in secret sharing is the optimal information ratio. Since computing the optimal information ratio of an access structure is generally hard, properties are obtained to facilitate its description. Finally, this thesis tackles the privacy-preserving data splitting technique, which aims at protecting data privacy by storing different fragments of data at different locations. Here, the data splitting problem is analyzed from a combinatorial point of view, bounding the number of fragments and proposing various algorithms to split the data