Hiding query access patterns in range queries using private information retrieval and oblivious ram

This work addresses the problem of hiding query access patterns in privacypreserving range queries while guaranteeing data and query con dentiality. We propose two methods, which are based on Private Information Retrieval (PIR) and Oblivious RAM (ORAM) techniques, respectively. For the PIR based search operation, we introduce a new scheme based on Lipmaa's computationally-private information retrieval (CPIR) method. We reduce the computation cost of CPIR by reducing the number of modular exponentiation operations, employing shallow trees and utilizing multi-exponentiation techniques. Furthermore, we improved the performance of CPIR by applying parallel algorithms. For the ORAM based method, we adapted Stefanov's Path ORAM method to the privacy-preserving range search. Our analyses show that, in terms of communication cost, CPIR provides better bandwidth usage especially in large database sizes, while in computational cost, Path ORAM based method performs better due to the negligible cost of server operations. The results imply that, despite some advantageous qualitative aspects of CPIR and its highly parallel implementation, it is still an expensive scheme in terms of computation complexity in comparison with Path ORAM for hiding query access patterns in privacy preserving range queries

A practical privacy-preserving public key repository

Internet and mobile users have been using financial institutions' alternative channels for their financial transactions with an increasing rate. In order to avoid frauds, the financial institutions make use of second factor authentication tokens such as one-time passwords sent to mobile phones as text. Another trend of such transaction verification is utilizing fully cryptographic protocols, in which the transactions are signed by the users. In the implementation of such an approach, in order to provide end-to-end security between the financial institution and its client, each client must have a public-private key pair. In some cases, especially for small-scale institutions, such a transaction verification system is fully outsourced as a Cloud service including clients' public keys. However, even in this outsourced model, the institutions need to access their clients' public keys for end-to-end security. In such a case, in order to provide privacy of the clients against the outsourced database, we need a privacy-preserving public key repository. In this thesis, we developed such a privacy-preserving public key repository based on Path ORAM mechanism. We have developed adaptation layers for Path ORAM so that the queries are performed via regular SQL queries and the data is stored in a regular relational database, rather than Path ORAM's non-standard data structure. In this way, the non-standard features are hidden from both the financial institutions and the Cloud provider. We analyzed the performance of our system under different database sizes, network connection models and query types. We conclude that such a Path ORAM based system is feasible to be used in a practical system since even with a regular computer used as a server, the computational overhead is at marginal level

Cryptography with anonymity in mind

Advances in information technologies gave a rise to powerful ubiquitous com- puting devices, and digital networks have enabled new ways of fast communication, which immediately found tons of applications and resulted in large amounts of data being transmitted. For decades, cryptographic schemes and privacy-preserving protocols have been studied and researched in order to offer end users privacy of their data and implement useful functionalities at the same time, often trading security properties for cryptographic assumptions and efficiency. In this plethora of cryptographic constructions, anonymity properties play a special role, as they are important in many real-life scenarios. However, many useful cryptographic primitives lack anonymity properties or imply prohibitive costs to achieve them. In this thesis, we expand the territory of cryptographic primitives with anonymity in mind. First, we define Anonymous RAM, a generalization of a single- user Oblivious RAM to multiple mistrusted users, and present two constructions thereof with different trade-offs between assumptions and efficiency. Second, we define an encryption scheme that allows to establish chains of ciphertexts anony- mously and verify their integrity. Furthermore, the aggregatable version of the scheme allows to build a Parallel Anonymous RAM, which enhances Anonymous RAM by supporting concurrent users. Third, we show our technique for construct- ing efficient non-interactive zero-knowledge proofs for statements that consist of both algebraic and arithmetic statements. Finally, we show our framework for constructing efficient single secret leader election protocols, which have been recently identified as an important component in proof-of-stake cryptocurrencies.Fortschritte in der Informationstechnik haben leistungsstarke allgegenwärtige Rechner hervorgerufen, während uns digitale Netzwerke neue Wege für die schnelle Kommunikation ermöglicht haben. Durch die Vielzahl von Anwendungen führte dies zur Übertragung von riesigen Datenvolumen. Seit Jahrzehnten wurden bereits verschiedene kryptographische Verfahren und Technologien zum Datenschutz erforscht und analysiert. Das Ziel ist die Privatsphäre der Benutzer zu schützen und gleichzeitig nützliche Funktionalität anzubieten, was oft mit einem Kompromiss zwischen Sicherheitseigenschaften, kryptographischen Annahmen und Effizienz verbunden ist. In einer Fülle von kryptographischen Konstruktionen spielen Anonymitätseigenschaften eine besondere Rolle, da sie in vielen realistischen Szenarien sehr wichtig sind. Allerdings fehlen vielen kryptographischen Primitive Anonymitätseigenschaften oder sie stehen im Zusammenhang mit erheblichen Kosten. In dieser Dissertation erweitern wir den Bereich von kryptographischen Prim- itiven mit einem Fokus auf Anonymität. Erstens definieren wir Anonymous RAM, eine Verallgemeinerung von Einzelbenutzer-Oblivious RAM für mehrere misstraute Benutzer, und stellen dazu zwei Konstruktionen mit verschiedenen Kompromissen zwischen Annahmen und Effizienz vor. Zweitens definieren wir ein Verschlüsselungsverfahren, das es erlaubt anonym eine Verbindung zwischen Geheimtexten herzustellen und deren Integrität zu überprüfen. Darüber hinaus bietet die aggregierbare Variante von diesem Verfahren an, Parallel Anonymous RAM zu bauen. Dieses verbessert Anonymous RAM, indem es mehrere Benutzer in einer parallelen Ausführung unterstützen kann. Drittens zeigen wir eine Meth- ode für das Konstruieren effizienter Zero-Knowledge-Protokolle, die gleichzeitig aus algebraischen und arithmetischen Teilen bestehen. Zuletzt zeigen wir ein Framework für das Konstruieren effizienter Single-Leader-Election-Protokolle, was kürzlich als ein wichtiger Bestandteil in den Proof-of-Stake Kryptowährungen erkannt worden ist

BurnBox: Self-Revocable Encryption in a World of Compelled Access

Dissidents, journalists, and others require technical means to protect their privacy in the face of compelled access to their digital devices (smartphones, laptops, tablets, etc.). For example, authorities increasingly force disclosure of all secrets, including passwords, to search devices upon national border crossings. We therefore present the design, implementation, and evaluation of a new system to help victims of compelled searches. Our system, called BurnBox, provides self-revocable encryption: the user can temporarily disable their access to specific files stored remotely, without revealing which files were revoked during compelled searches, even if the adversary also compromises the cloud storage service. They can later restore access. We formalize the threat model and provide a construction that uses an erasable index, secure erasure of keys, and standard cryptographic tools in order to provide security supported by our formal analysis. We report on a prototype implementation, which showcases the practicality of BurnBox

Forward and Backward Private Searchable Encryption from Constrained Cryptographic Primitives

Using dynamic Searchable Symmetric Encryption, a user with limited storage resources can securely outsource a database to an untrusted server, in such a way that the database can still be searched and updated efficiently. For these schemes, it would be desirable that updates do not reveal any information a priori about the modifications they carry out, and that deleted results remain inaccessible to the server a posteriori. If the first property, called forward privacy, has been the main motivation of recent works, the second one, backward privacy, has been overlooked. In this paper, we study for the first time the notion of backward privacy for searchable encryption. After giving formal definitions for different flavors of backward privacy, we present several schemes achieving both forward and backward privacy, with various efficiency trade-offs. Our constructions crucially rely on primitives such as constrained pseudo-random functions and puncturable encryption schemes. Using these advanced cryptographic primitives allows for a fine-grained control of the power of the adversary, preventing her from evaluating functions on selected inputs, or decrypting specific ciphertexts. In turn, this high degree of control allows our SSE constructions to achieve the stronger forms of privacy outlined above. As an example, we present a framework to construct forward-private schemes from range-constrained pseudo-random functions. Finally, we provide experimental results for implementations of our schemes, and study their practical efficiency

Privacy-preserving ranked search over encrypted cloud data

Search over encrypted data recently became a critical operation that raised a considerable amount of interest in both academia and industry, especially as outsourcing sensitive data to cloud proves to be a strong trend to benefit from the unmatched storage and computing capacities thereof. Indeed, privacy-preserving search over encrypted data, an apt term to address privacy related issues concomitant in outsourcing sensitive data, has been widely investigated in the literature under different models and assumptions. Although its benefits are welcomed, privacy is still a remaining concern that needs to be addressed. Some of those privacy issues can be summarized as: submitted search terms and their frequencies, returned responses and their relevancy to the query, and retrieved data items may all contain sensitive information about the users. In this thesis, we propose two di erent multi-keyword search schemes that ensure users' privacy against both external adversaries including other authorized users and cloud server itself. The proposed schemes use cryptographic techniques as well as query and response randomization. Provided that the security and randomization parameters are appropriately chosen, both the search terms in the queries and the returned responses are protected against privacy violations. The scheme implements strict security and privacy requirements that essentially can hide similarities between the queries that include the same keywords. One of the main advantages of all the proposed methods in this work is the capability of multi-keyword search in a single query. We also incorporate effective ranking capabilities in the proposed schemes that enable user to retrieve only the top matching results. Our comprehensive analytical study and extensive experiments using both real and synthetic data sets demonstrate that the proposed schemes are privacy-preserving, effective, and highly efficient

Enabling Data Security and Privacy for Database Services in the Cloud

Substantial advances in cloud technologies have made outsourcing data to the cloud highly beneficial today (e.g., costs savings, scalability, provisioning time). However, strong concerns from private companies and public institutions about the security of the outsourced data still hamper the adoption of cloud solutions. This reluctance is fed by frequent massive data breaches either caused by external attacks against cloud service providers or by negligent or opaque practices from the service provider itself. For broader adoption of cloud services, this dissertation addresses the data security and privacy concerns in the cloud setting. The goal is to ensure security and privacy of outsourced data while maintaining the ability to execute queries efficiently. Security/privacy comes at a cost of functionality/performance. Therefore, we seek for a proper balance in the space of security, privacy, functionality, and performance. This dissertation works the problems of range query execution over encrypted data, privacy preserving data mining in the context of environmental sustainability studies, and access privacy in the cloud. To enable efficient and secure range query processing over traditional databases, we introduce PINED-RQ, a highly efficient and differentially private range query execution framework that constructs a novel differentially private index over an outsourced database. Second, this dissertation presents a comprehensive study of the environmental sustainability metrics. Our contributions in this context are twofold: 1) to better evaluate the environmental impacts of the industrial processes privately, we formally define privacy preserving certification paradigm and develop a framework that enables untrusted third party to certify parties based on a well agreed upon set of criteria. 2) to explore the privacy concerns over publicizing the industrial activities in the form of life cycle assessment (LCA) computations, which is a standard way of evaluating an impact of a product and service. This dissertation initiates a study to explore privacy and security challenges that prevent organizations from making public disclosures about their activities. Finally, this dissertation explores access privacy in the cloud setting. We design and develop TaoStore, a highly efficient and practical cloud data store, which secures data confidentiality and hides access patterns from adversaries. Additionally, we propose a new ORAM security model, called aaob-security, which considers completely asynchronous network communication and concurrent processing of requests. This dissertation shows that it is possible to deliver practical and high-performance data services in the cloud without sacrificing securityand privacy if the requirements of each application are analyzed correctly and a correct balance is found in the space of security, privacy, functionality, and performance

UC Updatable Databases and Applications

We define an ideal functionality \Functionality_{\UD} and a construction \mathrm{\Pi_{\UD}} for an updatable database (\UD). \UD is a two-party protocol between an updater and a reader. The updater sets the database and updates it at any time throughout the protocol execution. The reader computes zero-knowledge (ZK) proofs of knowledge of database entries. These proofs prove that a value is stored at a certain position in the database, without revealing the position or the value. (Non-)updatable databases are implicitly used as building block in priced oblivious transfer, privacy-preserving billing and other privacy-preserving protocols. Typically, in those protocols the updater signs each database entry, and the reader proves knowledge of a signature on a database entry. Updating the database requires a revocation mechanism to revoke signatures on outdated database entries. Our construction \mathrm{\Pi_{\UD}} uses a non-hiding vector commitment (NHVC) scheme. The updater maps the database to a vector and commits to the database. This commitment can be updated efficiently at any time without needing a revocation mechanism. ZK proofs for reading a database entry have communication and amortized computation cost independent of the database size. Therefore, \mathrm{\Pi_{\UD}} is suitable for large databases. We implement \mathrm{\Pi_{\UD}} and our timings show that it is practical. In existing privacy-preserving protocols, a ZK proof of a database entry is intertwined with other tasks, e.g., proving further statements about the value read from the database or the position where it is stored. \Functionality_{\UD} allows us to improve modularity in protocol design by separating those tasks. We show how to use \Functionality_{\UD} as building block of a hybrid protocol along with other functionalities

Privacy-Preserving Minimum Spanning Trees through Oblivious Parallel RAM for Secure Multiparty Computation

In this paper, we describe efficient protocols to perform in parallel many reads and writes in private arrays according to private indices. The protocol is implemented on top of the Arithmetic Black Box (ABB) and can be freely composed to build larger privacy-preserving applications. For a large class of secure multiparty computation (SMC) protocols, we believe our technique to have better practical and asymptotic performance than any previous ORAM technique that has been adapted for use in SMC. Our ORAM technique opens up a large class of parallel algorithms for adoption to run on SMC platforms. In this paper, we demonstrate how the minimum spanning tree (MST) finding algorithm by Awerbuch and Shiloach can be executed without revealing any details about the underlying graph (beside its size). The data accesses of this algorithm heavily depend on the location and weight of edges (which are private) and our ORAM technique is instrumental in their execution. Our implementation is probably the first-ever realization of a privacy-preserving MST algorithm