Succinct Predicate and Online-Offline Multi-Input Inner Product Encryptions under Standard Static Assumptions

This paper presents expressive predicate encryption (PE) systems, namely non-zero inner-product-predicate encryption (NIPPE) and attribute-based encryption (ABE) supporting monotone span programs achieving best known parameters among existing similar schemes under well-studied static complexity assumptions. Both the constructions are built in composite order bilinear group setting and involve only 2 group elements in the ciphertexts. More interestingly, our NIPPE scheme, which additionally features only 1 group element in the decryption keys, is the first to attain succinct ciphertexts and decryption keys simultaneously. For proving selective security of these constructions under the Subgroup Decision assumptions, which are the most standard static assumptions in composite order bilinear group setting, we apply the extended version of the elegant D´ej`a Q framework, which was originally proposed as a general technique for reducing the q-type complexity assumptions to their static counter parts. Our work thus demonstrates the power of this framework in overcoming the need of q-type assumptions, which are vulnerable to serious practical attacks, for deriving security of highly expressive PE systems with compact parameters. We further introduce the concept of online-offline multi-input functional encryption (OO-MIFE), which is a crucial advancement towards realizing this highly promising but computationally intensive cryptographic primitive in resource bounded and power constrained devices. We also instantiate our notion of OO-MIFE by constructing such a scheme for the multi-input analog of the inner product functionality, which has a wide range of application in practice. Our OO-MIFE scheme for multiinput inner products is built in asymmetric bilinear groups of prime order and is proven selectively secure under the well-studied k-Linear (k-LIN) assumption

Advances in Functional Encryption

Functional encryption is a novel paradigm for public-key encryption that enables both fine-grained access control and selective computation on encrypted data, as is necessary to protect big, complex data in the cloud. In this thesis, I provide a brief introduction to functional encryption, and an overview of my contributions to the area

VeriVoting: A decentralized, verifiable and privacy-preserving scheme for weighted voting

Decentralization, verifiability, and privacy-preserving are three fundamental properties of modern e-voting. In this paper, we conduct extensive investigations into them and present a novel e-voting scheme, VeriVoting, which is the first to satisfy these properties. More specifically, decentralization is realized through blockchain technology and the distribution of decryption power among competing entities, such as candidates. Furthermore, verifiability is satisfied when the public verifies the ballots and decryption keys. And finally, bidirectional unlinkability is achieved to help preserve privacy by decoupling voter identity from ballot content. Following the ideas above, we first leverage linear homomorphic encryption schemes and non-interactive zero-knowledge argument systems to construct a voting primitive, SemiVoting, which meets decentralization, decryption-key verifiability, and ballot privacy. To further achieve ballot ciphertext verifiability and anonymity, we extend this primitive with blockchain and verifiable computation to finally arrive at VeriVoting. Through security analysis and per-formance evaluations, VeriVoting offers a new trade-off between security and efficiency that differs from all previous e-voting schemes and provides a radically novel practical ap-proach to large-scale elections

Design and analysis of a distributed ECDSA signing service

We present and analyze a new protocol that provides a distributed ECDSA signing service, with the following properties: * it works in an asynchronous communication model; * it works with $n$ parties with up to $f < n/3$ Byzantine corruptions; * it provides guaranteed output delivery; * it provides a very efficient, non-interactive online signing phase; * it supports additive key derivation according to the BIP32 standard. While there has been a flurry of recent research on distributed ECDSA signing protocols, none of these newly designed protocols provides guaranteed output delivery over an asynchronous communication network; moreover, the performance of our protocol (in terms of asymptotic communication and computational complexity) meets or beats the performance of any of these other protocols. This service is being implemented and integrated into the architecture of the Internet Computer, enabling smart contracts running on the Internet Computer to securely hold and spend Bitcoin and other cryptocurrencies. Along the way, we present some results of independent interest: * a new asynchronous verifiable secret sharing (AVSS) scheme that is simple and efficient; * a new scheme for multi-recipient encryption that is simple and efficient

Secure and practical computation on encrypted data

Because of the importance of computing on data with privacy protections, the cryptographic community has developed both theoretical and practical solutions to compute on encrypted data. On the one hand, theoretical schemes, such as fully homomorphic encryption and functional encryption, are secure but extremely inefficient. On the other hand, practical schemes, such as property-preserving encryption, gain efficiency by accepting significant reductions in security. In this thesis, we first study the security of popular property-preserving encryption schemes that are being used by companies such as Microsoft and Google. We show that such schemes are unacceptably insecure for key target applications such as electronic medical records. Second, we propose new models to compute on encrypted data and develop efficient constructions and systems. We propose a new cryptographic primitive called Blind Storage and show how it can be used to realize symmetric searchable encryption, which is much more secure than property-preserving encryption. Finally, we propose a new cryptographic model called Controlled Functional Encryption and develop two efficient schemes in this model

Keeping your Friends Secret: Improving the Security, Effciency and Usability of Private Set Intersection

Private set intersection (PSI) allows two parties, who each hold a set of items, to compute the intersection of those sets without revealing anything about other items. Recent advances in PSI have significantly improved its performance for the case of semi-honest security, making semi-honest PSI a practical alternative to insecure methods for computing intersections. However, these protocols have two major drawbacks: 1) the amount of data required to be communicated can be orders of magnitude larger than an insecure solution and 2) when in the presence of malicious parties the security of these protocols breaks down. In this work, four malicious secure PSI protocols are introduced along with three semi-honest protocols which have sublinear communication. These protocols are based on a combination of fast symmetric-key primitives and fully homomorphic encryption. Three of these protocols represent the current state of the art for their respective settings. The practicality of these protocols are demonstrated with prototype implementations. To securely compute the intersection of two sets of size 2²⁰ in the malicious setting requires only 13 seconds, which is ~ 450x faster than the previous best malicious-secure protocol (De Cristofaro et al, Asiacrypt 2010), and only 3x slower than the best semi-honest protocol (Kolesnikov et al., CCS 2016). Alternatively, when computing the intersection between set sizes of 2¹⁰ and 2²⁸, our fastest protocol require just 6 seconds and 5MB of communication

Malleable zero-knowledge proofs and applications

In recent years, the field of privacy-preserving technologies has experienced considerable expansion, with zero-knowledge proofs (ZKPs) playing one of the most prominent roles. Although ZKPs have been a well-established theoretical construct for three decades, recent efficiency improvements and novel privacy applications within decentralized finance have become the main drivers behind the surge of interest and investment in this area. This momentum has subsequently sparked unprecedented technical advances. Non-interactive ZKPs (NIZKs) are now regularly implemented across a variety of domains, encompassing, but not limited to, privacy-enabling cryptocurrencies, credential systems, voting, mixing, secure multi-party computation, and other cryptographic protocols. This thesis, although covering several areas of ZKP technologies and their application, focuses on one important aspect of NIZKs, namely their malleability. Malleability is a quality of a proof system that describes the potential for altering an already generated proof. Different properties may be desired in different application contexts. On the one end of the spectrum, non-malleability ensures proof immutability, an important requirement in scenarios such as prevention of replay attacks in anonymous cryptocurrencies. At the other end, some NIZKs enable proof updatability, recursively and directly, a feature that is integral for a variety of contexts, such as private smart contracts, compact blockchains, ZK rollups, ZK virtual machines, and MPC protocols generally. This work starts with a detailed analysis of the malleability and overarching security of a popular NIZK, known as Groth16. Here we adopt a more definitional approach, studying certain properties of the proof system, and its setup ceremony, that are crucial for its precise modelling within bigger systems. Subsequently, the work explores the malleability of transactions within a private cryptocurrency variant, where we show that relaxing non-malleability assumptions enables a functionality, specifically an atomic asset swap, that is useful for cryptocurrency applications. The work culminates with a study of a less general, algebraic NIZK, and particularly its updatability properties, whose applicability we present within the context of ensuring privacy for regulatory compliance purposes

Declarative design and enforcement for secure cloud applications

The growing demands of users and industry have led to an increase in both size and complexity of deployed software in recent years. This tendency mainly stems from a growing number of interconnected mobile devices and from the huge amounts of data that is collected every day by a growing number of sensors and interfaces. Such increase in complexity imposes various challenges -- not only in terms of software correctness, but also with respect to security. This thesis addresses three complementary approaches to cope with the challenges: (i) appropriate high-level abstractions and verifiable translation methods to executable applications in order to guarantee flawless implementations, (ii) strong cryptographic mechanisms in order to realize the desired security goals, and (iii) convenient methods in order to incentivize the correct usage of existing techniques and tools. In more detail, the thesis presents two frameworks for the declarative specification of functionality and security, together with advanced compilers for the verifiable translation to executable applications. Moreover, the thesis presents two cryptographic primitives for the enforcement of cloud-based security properties: homomorphic message authentication codes ensure the correctness of evaluating functions over data outsourced to unreliable cloud servers; and efficiently verifiable non-interactive zero-knowledge proofs convince verifiers of computation results without the verifiers having access to the computation input.Die wachsenden Anforderungen von Seiten der Industrie und der Endbenutzer verlangen nach immer komplexeren Softwaresystemen -- größtenteils begründet durch die stetig wachsende Zahl mobiler Geräte und die damit wachsende Zahl an Sensoren und erfassten Daten. Mit wachsender Software-Komplexität steigen auch die Herausforderungen an Korrektheit und Sicherheit. Die vorliegende Arbeit widmet sich diesen Herausforderungen in Form dreier komplementärer Ansätze: (i) geeignete Abstraktionen und verifizierbare Übersetzungsmethoden zu ausführbaren Anwendungen, die fehlerfreie Implementierungen garantieren, (ii) starke kryptographische Mechanismen, um die spezifizierten Sicherheitsanforderungen effizient und korrekt umzusetzen, und (iii) zweckmäßige Methoden, die eine korrekte Benutzung existierender Werkzeuge und Techniken begünstigen. Diese Arbeit stellt zwei neuartige Abläufe vor, die verifizierbare Übersetzungen von deklarativen Spezifikationen funktionaler und sicherheitsrelevanter Ziele zu ausführbaren Cloud-Anwendungen ermöglichen. Darüber hinaus präsentiert diese Arbeit zwei kryptographische Primitive für sichere Berechnungen in unzuverlässigen Cloud-Umgebungen. Obwohl die Eingabedaten der Berechnungen zuvor in die Cloud ausgelagert wurden und zur Verifikation der Berechnungen nicht mehr zur Verfügung stehen, ist es möglich, die Korrektheit der Ergebnisse in effizienter Weise zu überprüfen

Secure and efficient processing of outsourced data structures using trusted execution environments

In recent years, more and more companies make use of cloud computing; in other words, they outsource data storage and data processing to a third party, the cloud provider. From cloud computing, the companies expect, for example, cost reductions, fast deployment time, and improved security. However, security also presents a significant challenge as demonstrated by many cloud computing–related data breaches. Whether it is due to failing security measures, government interventions, or internal attackers, data leakages can have severe consequences, e.g., revenue loss, damage to brand reputation, and loss of intellectual property. A valid strategy to mitigate these consequences is data encryption during storage, transport, and processing. Nevertheless, the outsourced data processing should combine the following three properties: strong security, high efficiency, and arbitrary processing capabilities. Many approaches for outsourced data processing based purely on cryptography are available. For instance, encrypted storage of outsourced data, property-preserving encryption, fully homomorphic encryption, searchable encryption, and functional encryption. However, all of these approaches fail in at least one of the three mentioned properties. Besides approaches purely based on cryptography, some approaches use a trusted execution environment (TEE) to process data at a cloud provider. TEEs provide an isolated processing environment for user-defined code and data, i.e., the confidentiality and integrity of code and data processed in this environment are protected against other software and physical accesses. Additionally, TEEs promise efficient data processing. Various research papers use TEEs to protect objects at different levels of granularity. On the one end of the range, TEEs can protect entire (legacy) applications. This approach facilitates the development effort for protected applications as it requires only minor changes. However, the downsides of this approach are that the attack surface is large, it is difficult to capture the exact leakage, and it might not even be possible as the isolated environment of commercially available TEEs is limited. On the other end of the range, TEEs can protect individual, stateless operations, which are called from otherwise unchanged applications. This approach does not suffer from the problems stated before, but it leaks the (encrypted) result of each operation and the detailed control flow through the application. It is difficult to capture the leakage of this approach, because it depends on the processed operation and the operation’s location in the code. In this dissertation, we propose a trade-off between both approaches: the TEE-based processing of data structures. In this approach, otherwise unchanged applications call a TEE for self-contained data structure operations and receive encrypted results. We examine three data structures: TEE-protected B+-trees, TEE-protected database dictionaries, and TEE-protected file systems. Using these data structures, we design three secure and efficient systems: an outsourced system for index searches; an outsourced, dictionary-encoding–based, column-oriented, in-memory database supporting analytic queries on large datasets; and an outsourced system for group file sharing supporting large and dynamic groups. Due to our approach, the systems have a small attack surface, a low likelihood of security-relevant bugs, and a data owner can easily perform a (formal) code verification of the sensitive code. At the same time, we prevent low-level leakage of individual operation results. For all systems, we present a thorough security evaluation showing lower bounds of security. Additionally, we use prototype implementations to present upper bounds on performance. For our implementations, we use a widely available TEE that has a limited isolated environment—Intel Software Guard Extensions. By comparing our systems to related work, we show that they provide a favorable trade-off regarding security and efficiency