Enabling Secure Database as a Service using Fully Homomorphic Encryption: Challenges and Opportunities

The database community, at least for the last decade, has been grappling with querying encrypted data, which would enable secure database as a service solutions. A recent breakthrough in the cryptographic community (in 2009) related to fully homomorphic encryption (FHE) showed that arbitrary computation on encrypted data is possible. Successful adoption of FHE for query processing is, however, still a distant dream, and numerous challenges have to be addressed. One challenge is how to perform algebraic query processing of encrypted data, where we produce encrypted intermediate results and operations on encrypted data can be composed. In this paper, we describe our solution for algebraic query processing of encrypted data, and also outline several other challenges that need to be addressed, while also describing the lessons that can be learnt from a decade of work by the database community in querying encrypted data

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

Fast Keyword Search With Encryption

Paillier� Method is used in research and cloud protected outsourcing as well as privacy-preserving computation. In this paper we implement Pallier Method for providing security. Fast Keyword Search Perform on encrypted Data not directly on plain text, hence Security is given to database. In Multi-writer scenario Data sources upload Data on Different Resources .Data owner is responsible for generating tokens and encrypt data. Data owner and query source perform queries through a query processor. Data originated by data sources in which personal data and public data include, personal data search only authorized personal and public data search anyone who create their data source registration successfully. Cipher text length is created in between 16 digits to 256 digits, if data source search similar data on multiple time then every time query is encrypted using different numbers. Data in database stored using number of attribute. We focused on security in Pallier method

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

Systemunterstützung für moderne Speichertechnologien

Trust and scalability are the two significant factors which impede the dissemination of clouds. The possibility of privileged access to customer data by a cloud provider limits the usage of clouds for processing security-sensitive data. Low latency cloud services rely on in-memory computations, and thus, are limited by several characteristics of Dynamic RAM (DRAM) such as capacity, density, energy consumption, for example. Two technological areas address these factors. Mainstream server platforms, such as Intel Software Guard eXtensions (SGX) und AMD Secure Encrypted Virtualisation (SEV) offer extensions for trusted execution in untrusted environments. Various technologies of Non-Volatile RAM (NV-RAM) have better capacity and density compared to DRAM and thus can be considered as DRAM alternatives in the future. However, these technologies and extensions require new programming approaches and system support since they add features to the system architecture: new system components (Intel SGX) and data persistence (NV-RAM). This thesis is devoted to the programming and architectural aspects of persistent and trusted systems. For trusted systems, an in-depth analysis of new architectural extensions was performed. A novel framework named EActors and a database engine named STANlite were developed to effectively use the capabilities of trusted~execution. For persistent systems, an in-depth analysis of prospective memory technologies, their features and the possible impact on system architecture was performed. A new persistence model, called the hypervisor-based model of persistence, was developed and evaluated by the NV-Hypervisor. This offers transparent persistence for legacy and proprietary software, and supports virtualisation of persistent memory.Vertrauenswürdigkeit und Skalierbarkeit sind die beiden maßgeblichen Faktoren, die die Verbreitung von Clouds behindern. Die Möglichkeit privilegierter Zugriffe auf Kundendaten durch einen Cloudanbieter schränkt die Nutzung von Clouds bei der Verarbeitung von sicherheitskritischen und vertraulichen Informationen ein. Clouddienste mit niedriger Latenz erfordern die Durchführungen von Berechnungen im Hauptspeicher und sind daher an Charakteristika von Dynamic RAM (DRAM) wie Kapazität, Dichte, Energieverbrauch und andere Aspekte gebunden. Zwei technologische Bereiche befassen sich mit diesen Faktoren: Etablierte Server Plattformen wie Intel Software Guard eXtensions (SGX) und AMD Secure Encrypted Virtualisation (SEV) stellen Erweiterungen für vertrauenswürdige Ausführung in nicht vertrauenswürdigen Umgebungen bereit. Verschiedene Technologien von nicht flüchtigem Speicher bieten bessere Kapazität und Speicherdichte verglichen mit DRAM, und können daher in Zukunft als Alternative zu DRAM herangezogen werden. Jedoch benötigen diese Technologien und Erweiterungen neuartige Ansätze und Systemunterstützung bei der Programmierung, da diese der Systemarchitektur neue Funktionalität hinzufügen: Systemkomponenten (Intel SGX) und Persistenz (nicht-flüchtiger Speicher). Diese Dissertation widmet sich der Programmierung und den Architekturaspekten von persistenten und vertrauenswürdigen Systemen. Für vertrauenswürdige Systeme wurde eine detaillierte Analyse der neuen Architekturerweiterungen durchgeführt. Außerdem wurden das neuartige EActors Framework und die STANlite Datenbank entwickelt, um die neuen Möglichkeiten von vertrauenswürdiger Ausführung effektiv zu nutzen. Darüber hinaus wurde für persistente Systeme eine detaillierte Analyse zukünftiger Speichertechnologien, deren Merkmale und mögliche Auswirkungen auf die Systemarchitektur durchgeführt. Ferner wurde das neue Hypervisor-basierte Persistenzmodell entwickelt und mittels NV-Hypervisor ausgewertet, welches transparente Persistenz für alte und proprietäre Software, sowie Virtualisierung von persistentem Speicher ermöglicht

Secure Abstractions for Trusted Cloud Computation

Cloud computing is adopted by most organizations due to its characteristics, namely offering on-demand resources and services that can quickly be provisioned with minimal management effort and maintenance expenses for its users. However it still suffers from security incidents which have lead to many data security concerns and reluctance in further adherence. With the advent of these incidents, cryptographic technologies such as homomorphic and searchable encryption schemes were leveraged to provide solutions that mitigated data security concerns. The goal of this thesis is to provide a set of secure abstractions to serve as a tool for programmers to develop their own distributed applications. Furthermore, these abstractions can also be used to support trusted cloud computations in the context of NoSQL data stores. For this purpose we leveraged conflict-free replicated data types (CRDTs) as they provide a mechanism to ensure data consistency when replicated that has no need for synchronization, which aligns well with the distributed and replicated nature of the cloud, and the aforementioned cryptographic technologies to comply with the security requirements. The main challenge of this thesis consisted in combining the cryptographic technologies with the CRDTs in such way that it was possible to support all of the data structures functionalities over ciphertext while striving to attain the best security and performance possible. To evaluate our abstractions we conducted an experiment to compare each secure abstraction with their non secure counterpart performance wise. Additionally, we also analysed the security level provided by each of the structures in light of the cryptographic scheme used to support it. The results of our experiment shows that our abstractions provide the intended data security with an acceptable performance overhead, showing that it has potential to be used to build solutions for trusted cloud computation

Privacy-Enhanced Dependable and Searchable Storage in a Cloud-of-Clouds

In this dissertation we will propose a solution for a trustable and privacy-enhanced storage architecture based on a multi-cloud approach. The solution provides the necessary support for multi modal on-line searching operation on data that is always maintained encrypted on used cloud-services. We implemented a system prototype, conducting an experimental evaluation. Our results show that the proposal offers security and privacy guarantees, and provides efficient information retrieval capabilities without sacrificing precision and recall properties on the supported search operations. There is a constant increase in the demand of cloud services, particularly cloud-based storage services. These services are currently used by different applications as outsourced storage services, with some interesting advantages. Most personal and mobile applications also offer the user the choice to use the cloud to store their data, transparently and sometimes without entire user awareness and privacy-conditions, to overcome local storage limitations. Companies might also find that it is cheaper to outsource databases and keyvalue stores, instead of relying on storage solutions in private data-centers. This raises the concern about data privacy guarantees and data leakage danger. A cloud system administrator can easily access unprotected data and she/he could also forge, modify or delete data, violating privacy, integrity, availability and authenticity conditions. A possible solution to solve those problems would be to encrypt and add authenticity and integrity proofs in all data, before being sent to the cloud, and decrypting and verifying authenticity or integrity on data downloads. However this solution can be used only for backup purposes or when big data is not involved, and might not be very practical for online searching requirements over large amounts of cloud stored data that must be searched, accessed and retrieved in a dynamic way. Those solutions also impose high-latency and high amount of cloud inbound/outbound traffic, increasing the operational costs. Moreover, in the case of mobile or embedded devices, the power, computation and communication constraints cannot be ignored, since indexing, encrypting/decrypting and signing/verifying all data will be computationally expensive. To overcome the previous drawbacks, in this dissertation we propose a solution for a trustable and privacy-enhanced storage architecture based on a multi-cloud approach, providing privacy-enhanced, dependable and searchable support. Our solution provides the necessary support for dependable cloud storage and multi modal on-line searching operations over always-encrypted data in a cloud-of-clouds. We implemented a system prototype, conducting an experimental evaluation of the proposed solution, involving the use of conventional storage clouds, as well as, a high-speed in-memory cloud-storage backend. Our results show that the proposal offers the required dependability properties and privacy guarantees, providing efficient information retrieval capabilities without sacrificing precision and recall properties in the supported indexing and search operations