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

Efficient integrity checks for join queries in the cloud

Cloud computing is receiving massive interest from users and companies for its convenient support of scalable access to data and services. The variety and diversification of offers by cloud providers allow users to selectively adopt storage and computational services as they best suit their needs, including cost saving considerations. In such an open context, security remains a major concern, as confidentiality and integrity of data and queries over them can be at risk. In this paper, we present efficient techniques to verify the integrity of join queries computed by potentially untrusted cloud providers, while also protecting data and computation confidentiality. Our techniques support joins among multiple data sources and introduce a limited overhead in query computation, enabling also economical savings, as the ability to assess integrity increases the spectrum of offers that can be considered for performing the computation. Formal analysis and experimental evaluations confirm the effectiveness and efficiency of our solutions

Exécutions de requêtes respectueuses de la vie privée par utilisation de composants matériels sécurisés

Current applications, from complex sensor systems (e.g. quantified self) to online e-markets acquire vast quantities of personal information which usually end-up on central servers. This massive amount of personal data, the new oil, represents an unprecedented potential for applications and business. However, centralizing and processing all one's data in a single server, where they are exposed to prying eyes, poses a major problem with regards to privacy concern.Conversely, decentralized architectures helping individuals keep full control of their data, but they complexify global treatments and queries, impeding the development of innovative services.In this thesis, we aim at reconciling individual's privacy on one side and global benefits for the community and business perspectives on the other side. It promotes the idea of pushing the security to secure hardware devices controlling the data at the place of their acquisition. Thanks to these tangible physical elements of trust, secure distributed querying protocols can reestablish the capacity to perform global computations, such as SQL aggregates, without revealing any sensitive information to central servers.This thesis studies the subset of SQL queries without external joins and shows how to secure their execution in the presence of honest-but-curious attackers. It also discusses how the resulting querying protocols can be integrated in a concrete decentralized architecture. Cost models and experiments on SQL/AA, our distributed prototype running on real tamper-resistant hardware, demonstrate that this approach can scale to nationwide applications.Les applications actuelles, des systèmes de capteurs complexes (par exemple auto quantifiée) aux applications de e-commerce, acquièrent de grandes quantités d'informations personnelles qui sont habituellement stockées sur des serveurs centraux. Cette quantité massive de données personnelles, considéré comme le nouveau pétrole, représente un important potentiel pour les applications et les entreprises. Cependant, la centralisation et le traitement de toutes les données sur un serveur unique, où elles sont exposées aux indiscrétions de son gestionnaire, posent un problème majeur en ce qui concerne la vie privée.Inversement, les architectures décentralisées aident les individus à conserver le plein de contrôle sur leurs données, toutefois leurs traitements en particulier le calcul de requêtes globales deviennent complexes.Dans cette thèse, nous visons à concilier la vie privée de l'individu et l'exploitation de ces données, qui présentent des avantages manifestes pour la communauté (comme des études statistiques) ou encore des perspectives d'affaires. Nous promouvons l'idée de sécuriser l'acquisition des données par l'utilisation de matériel sécurisé. Grâce à ces éléments matériels tangibles de confiance, sécuriser des protocoles d'interrogation distribués permet d'effectuer des calculs globaux, tels que les agrégats SQL, sans révéler d'informations sensibles à des serveurs centraux.Cette thèse étudie le sous-groupe de requêtes SQL sans jointures et montre comment sécuriser leur exécution en présence d'attaquants honnêtes-mais-curieux. Cette thèse explique également comment les protocoles d'interrogation qui en résultent peuvent être intégrés concrètement dans une architecture décentralisée. Nous démontrons que notre approche est viable et peut passer à l'échelle d'applications de la taille d'un pays par un modèle de coût et des expériences réelles sur notre prototype, SQL/AA

Distributed Differential Privacy and Applications

Recent growth in the size and scope of databases has resulted in more research into making productive use of this data. Unfortunately, a significant stumbling block which remains is protecting the privacy of the individuals that populate these datasets. As people spend more time connected to the Internet, and conduct more of their daily lives online, privacy becomes a more important consideration, just as the data becomes more useful for researchers, companies, and individuals. As a result, plenty of important information remains locked down and unavailable to honest researchers today, due to fears that data leakages will harm individuals. Recent research in differential privacy opens a promising pathway to guarantee individual privacy while simultaneously making use of the data to answer useful queries. Differential privacy is a theory that provides provable information theoretic guarantees on what any answer may reveal about any single individual in the database. This approach has resulted in a flurry of recent research, presenting novel algorithms that can compute a rich class of computations in this setting. In this dissertation, we focus on some real world challenges that arise when trying to provide differential privacy guarantees in the real world. We design and build runtimes that achieve the mathematical differential privacy guarantee in the face of three real world challenges: securing the runtimes against adversaries, enabling readers to verify that the answers are accurate, and dealing with data distributed across multiple domains

BALANCING PRIVACY, PRECISION AND PERFORMANCE IN DISTRIBUTED SYSTEMS

Privacy, Precision, and Performance (3Ps) are three fundamental design objectives in distributed systems. However, these properties tend to compete with one another and are not considered absolute properties or functions. They must be defined and justified in terms of a system, its resources, stakeholder concerns, and the security threat model. To date, distributed systems research has only considered the trade-offs of balancing privacy, precision, and performance in a pairwise fashion. However, this dissertation formally explores the space of trade-offs among all 3Ps by examining three representative classes of distributed systems, namely Wireless Sensor Networks (WSNs), cloud systems, and Data Stream Management Systems (DSMSs). These representative systems support large part of the modern and mission-critical distributed systems. WSNs are real-time systems characterized by unreliable network interconnections and highly constrained computational and power resources. The dissertation proposes a privacy-preserving in-network aggregation protocol for WSNs demonstrating that the 3Ps could be navigated by adopting the appropriate algorithms and cryptographic techniques that are not prohibitively expensive. Next, the dissertation highlights the privacy and precision issues that arise in cloud databases due to the eventual consistency models of the cloud. To address these issues, consistency enforcement techniques across cloud servers are proposed and the trade-offs between 3Ps are discussed to help guide cloud database users on how to balance these properties. Lastly, the 3Ps properties are examined in DSMSs which are characterized by high volumes of unbounded input data streams and strict real-time processing constraints. Within this system, the 3Ps are balanced through a proposed simple and efficient technique that applies access control policies over shared operator networks to achieve privacy and precision without sacrificing the systems performance. Despite that in this dissertation, it was shown that, with the right set of protocols and algorithms, the desirable 3P properties can co-exist in a balanced way in well-established distributed systems, this dissertation is promoting the use of the new 3Ps-by-design concept. This concept is meant to encourage distributed systems designers to proactively consider the interplay among the 3Ps from the initial stages of the systems design lifecycle rather than identifying them as add-on properties to systems

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

Secure Schemes for Semi-Trusted Environment

In recent years, two distributed system technologies have emerged: Peer-to-Peer (P2P) and cloud computing. For the former, the computers at the edge of networks share their resources, i.e., computing power, data, and network bandwidth, and obtain resources from other peers in the same community. Although this technology enables efficiency, scalability, and availability at low cost of ownership and maintenance, peers defined as ``like each other'' are not wholly controlled by one another or by the same authority. In addition, resources and functionality in P2P systems depend on peer contribution, i.e., storing, computing, routing, etc. These specific aspects raise security concerns and attacks that many researchers try to address. Most solutions proposed by researchers rely on public-key certificates from an external Certificate Authority (CA) or a centralized Public Key Infrastructure (PKI). However, both CA and PKI are contradictory to fully decentralized P2P systems that are self-organizing and infrastructureless. To avoid this contradiction, this thesis concerns the provisioning of public-key certificates in P2P communities, which is a crucial foundation for securing P2P functionalities and applications. We create a framework, named the Self-Organizing and Self-Healing CA group (SOHCG), that can provide certificates without a centralized Trusted Third Party (TTP). In our framework, a CA group is initialized in a Content Addressable Network (CAN) by trusted bootstrap nodes and then grows to a mature state by itself. Based on our group management policies and predefined parameters, the membership in a CA group is dynamic and has a uniform distribution over the P2P community; the size of a CA group is kept to a level that balances performance and acceptable security. The muticast group over an underlying CA group is constructed to reduce communication and computation overhead from collaboration among CA members. To maintain the quality of the CA group, the honest majority of members is maintained by a Byzantine agreement algorithm, and all shares are refreshed gradually and continuously. Our CA framework has been designed to meet all design goals, being self-organizing, self-healing, scalable, resilient, and efficient. A security analysis shows that the framework enables key registration and certificate issue with resistance to external attacks, i.e., node impersonation, man-in-the-middle (MITM), Sybil, and a specific form of DoS, as well as internal attacks, i.e., CA functionality interference and CA group subversion. Cloud computing is the most recent evolution of distributed systems that enable shared resources like P2P systems. Unlike P2P systems, cloud entities are asymmetric in roles like client-server models, i.e., end-users collaborate with Cloud Service Providers (CSPs) through Web interfaces or Web portals. Cloud computing is a combination of technologies, e.g., SOA services, virtualization, grid computing, clustering, P2P overlay networks, management automation, and the Internet, etc. With these technologies, cloud computing can deliver services with specific properties: on-demand self-service, broad network access, resource pooling, rapid elasticity, measured services. However, theses core technologies have their own intrinsic vulnerabilities, so they induce specific attacks to cloud computing. Furthermore, since public clouds are a form of outsourcing, the security of users' resources must rely on CSPs' administration. This situation raises two crucial security concerns for users: locking data into a single CSP and losing control of resources. Providing inter-operations between Application Service Providers (ASPs) and untrusted cloud storage is a countermeasure that can protect users from lock-in with a vendor and losing control of their data. To meet the above challenge, this thesis proposed a new authorization scheme, named OAuth and ABE based authorization (AAuth), that is built on the OAuth standard and leverages Ciphertext-Policy Attribute Based Encryption (CP-ABE) and ElGamal-like masks to construct ABE-based tokens. The ABE-tokens can facilitate a user-centric approach, end-to-end encryption and end-to-end authorization in semi-trusted clouds. With these facilities, owners can take control of their data resting in semi-untrusted clouds and safely use services from unknown ASPs. To this end, our scheme divides the attribute universe into two disjointed sets: confined attributes defined by owners to limit the lifetime and scope of tokens and descriptive attributes defined by authority(s) to certify the characteristic of ASPs. Security analysis shows that AAuth maintains the same security level as the original CP-ABE scheme and protects users from exposing their credentials to ASP, as OAuth does. Moreover, AAuth can resist both external and internal attacks, including untrusted cloud storage. Since most cryptographic functions are delegated from owners to CSPs, AAuth gains computing power from clouds. In our extensive simulation, AAuth's greater overhead was balanced by greater security than OAuth's. Furthermore, our scheme works seamlessly with storage providers by retaining the providers' APIs in the usual way

Privacy-preserving queries on encrypted databases

In today's Internet, with the advent of cloud computing, there is a natural desire for enterprises, organizations, and end users to outsource increasingly large amounts of data to a cloud provider. Therefore, ensuring security and privacy is becoming a significant challenge for cloud computing, especially for users with sensitive and valuable data. Recently, many efficient and scalable query processing methods over encrypted data have been proposed. Despite that, numerous challenges remain to be addressed due to the high complexity of many important queries on encrypted large-scale datasets. This thesis studies the problem of privacy-preserving database query processing on structured data (e.g., relational and graph databases). In particular, this thesis proposes several practical and provable secure structured encryption schemes that allow the data owner to encrypt data without losing the ability to query and retrieve it efficiently for authorized clients. This thesis includes two parts. The first part investigates graph encryption schemes. This thesis proposes a graph encryption scheme for approximate shortest distance queries. Such scheme allows the client to query the shortest distance between two nodes in an encrypted graph securely and efficiently. Moreover, this thesis also explores how the techniques can be applied to other graph queries. The second part of this thesis proposes secure top-k query processing schemes on encrypted relational databases. Furthermore, the thesis develops a scheme for the top-k join queries over multiple encrypted relations. Finally, this thesis demonstrates the practicality of the proposed encryption schemes by prototyping the encryption systems to perform queries on real-world encrypted datasets