Reusable garbled gates for new fully homomorphic encryption service

In this paper, we propose a novel way to provide a fully homomorphic encryption service, namely by using garbled circuits. From a high level perspective, garbled circuits and fully homomorphic encryption, both aim at implementing complex computation on ciphertexts. We define a new cryptographic primitive named reusable garbled gate, which comes from the area of garbled circuits, then based on this new primitive we show that it is very easy to construct a fully homomorphic encryption. However, the instantiation of reusable garbled gates is rather difficult, in fact, we can only instantiate this new primitive based on indistinguishable obfuscation. Furthermore, reusable garbled gates can be a core component for constructing the reusable garbled circuits, which can reduce the communication complexity of them from O(n) to O(1). We believe that reusable garbled gates promise a new way to provide fully homomorphic encryption and reusable garbled circuits service fast.Peer ReviewedPostprint (author's final draft

Raziel: Private and Verifiable Smart Contracts on Blockchains

Raziel combines secure multi-party computation and proof-carrying code to provide privacy, correctness and verifiability guarantees for smart contracts on blockchains. Effectively solving DAO and Gyges attacks, this paper describes an implementation and presents examples to demonstrate its practical viability (e.g., private and verifiable crowdfundings and investment funds). Additionally, we show how to use Zero-Knowledge Proofs of Proofs (i.e., Proof-Carrying Code certificates) to prove the validity of smart contracts to third parties before their execution without revealing anything else. Finally, we show how miners could get rewarded for generating pre-processing data for secure multi-party computation.Comment: Support: cothority/ByzCoin/OmniLedge

Cryptography

The Oberwolfach workshop Cryptography brought together scientists from cryptography with mathematicians specializing in the algorithmic problems underlying cryptographic security. The goal of the workshop was to stimulate interaction and collaboration that enables a holistic approach to designing cryptography from the mathematical foundations to practical applications. The workshop covered basic computational problems such as factoring and computing discrete logarithms and short vectors. It addressed fundamental research results leading to innovative cryptography for protecting security and privacy in cloud applications. It also covered some practical applications

Towards compact bandwidth and efficient privacy-preserving computation

In traditional cryptographic applications, cryptographic mechanisms are employed to ensure the security and integrity of communication or storage. In these scenarios, the primary threat is usually an external adversary trying to intercept or tamper with the communication between two parties. On the other hand, in the context of privacy-preserving computation or secure computation, the cryptographic techniques are developed with a different goal in mind: to protect the privacy of the participants involved in a computation from each other. Specifically, privacy-preserving computation allows multiple parties to jointly compute a function without revealing their inputs and it has numerous applications in various fields, including finance, healthcare, and data analysis. It allows for collaboration and data sharing without compromising the privacy of sensitive data, which is becoming increasingly important in today's digital age. While privacy-preserving computation has gained significant attention in recent times due to its strong security and numerous potential applications, its efficiency remains its Achilles' heel. Privacy-preserving protocols require significantly higher computational overhead and bandwidth when compared to baseline (i.e., insecure) protocols. Therefore, finding ways to minimize the overhead, whether it be in terms of computation or communication, asymptotically or concretely, while maintaining security in a reasonable manner remains an exciting problem to work on. This thesis is centred around enhancing efficiency and reducing the costs of communication and computation for commonly used privacy-preserving primitives, including private set intersection, oblivious transfer, and stealth signatures. Our primary focus is on optimizing the performance of these primitives.Im Gegensatz zu traditionellen kryptografischen Aufgaben, bei denen Kryptografie verwendet wird, um die Sicherheit und Integrität von Kommunikation oder Speicherung zu gewährleisten und der Gegner typischerweise ein Außenstehender ist, der versucht, die Kommunikation zwischen Sender und Empfänger abzuhören, ist die Kryptografie, die in der datenschutzbewahrenden Berechnung (oder sicheren Berechnung) verwendet wird, darauf ausgelegt, die Privatsphäre der Teilnehmer voreinander zu schützen. Insbesondere ermöglicht die datenschutzbewahrende Berechnung es mehreren Parteien, gemeinsam eine Funktion zu berechnen, ohne ihre Eingaben zu offenbaren. Sie findet zahlreiche Anwendungen in verschiedenen Bereichen, einschließlich Finanzen, Gesundheitswesen und Datenanalyse. Sie ermöglicht eine Zusammenarbeit und Datenaustausch, ohne die Privatsphäre sensibler Daten zu kompromittieren, was in der heutigen digitalen Ära immer wichtiger wird. Obwohl datenschutzbewahrende Berechnung aufgrund ihrer starken Sicherheit und zahlreichen potenziellen Anwendungen in jüngster Zeit erhebliche Aufmerksamkeit erregt hat, bleibt ihre Effizienz ihre Achillesferse. Datenschutzbewahrende Protokolle erfordern deutlich höhere Rechenkosten und Kommunikationsbandbreite im Vergleich zu Baseline-Protokollen (d.h. unsicheren Protokollen). Daher bleibt es eine spannende Aufgabe, Möglichkeiten zu finden, um den Overhead zu minimieren (sei es in Bezug auf Rechen- oder Kommunikationsleistung, asymptotisch oder konkret), während die Sicherheit auf eine angemessene Weise gewährleistet bleibt. Diese Arbeit konzentriert sich auf die Verbesserung der Effizienz und Reduzierung der Kosten für Kommunikation und Berechnung für gängige datenschutzbewahrende Primitiven, einschließlich private Schnittmenge, vergesslicher Transfer und Stealth-Signaturen. Unser Hauptaugenmerk liegt auf der Optimierung der Leistung dieser Primitiven

Efficient and secure schemes for private function evaluation

Development of computing devices with the proliferation of the Internet has prompted enormous opportunities for cooperative computation. These computations could occur between trusted or partially trusted partners, or even between competitors. Secure multi-party computation (MPC) protocols allow two or more parties to collaborate and compute a public functionality using their private inputs without the need for a trusted third-party. However, the generic solutions for MPC are not adequate for some particular cases where the function itself is also sensitive and required to be kept private. Private function evaluation (PFE) is a special case of MPC, where the function to be computed is known by only one party. PFE is useful in several real-life applications where an algorithm or a function itself needs to remain secret for reasons such as protecting intellectual property or security classification level. Recently, designing efficient PFE protocols have been a challenging and attractive task for cryptography researchers. iv In this dissertation, we mainly focus on improving two-party private function evaluation (2PFE) schemes. Our primary goal is enhancing the state-of-the-art by designing secure and cost-efficient 2PFE protocols for both symmetric and asymmetric cryptography based solutions. In this respect, we first aim to improve 2PFE protocols based on (mostly) symmetric cryptographic primitives. We look back at the seminal PFE framework presented by Mohassel and Sadeghian at Eurocrypt'13. We show how to adapt and utilize the well-known half gates garbling technique (Zahur et al., Eurocrypt'15) to their constant round 2PFE scheme. Compared to their scheme, our resulting optimization significantly improves both underlying oblivious extended permutation (OEP) and secure 2-party computation (2PC) protocols, and yields a more than 40% reduction in overall communication cost. We next propose a novel and highly efficient 2PFE scheme based on the decisional Di e-Hellman (DDH) assumption. Our scheme consists of two protocols, one is utilized in the initial execution, and the other is in the subsequent runs. One of the novelties of our scheme over the state-of-the-art is that it results in a significant cost reduction when the same private function is evaluated more than once between the same or varying parties. To the best of our knowledge, this is the most efficient and the first 2PFE scheme that enjoys reusability feature. Our protocols achieve linear communication and computation complexities, and a constant number of rounds which is at most three (depending on the size of the inputs of the party that holds the function)

Controlled Functional Encryption

3École polytechnique fédérale de Lausanne Motivated by privacy and usability requirements in various sce-narios where existing cryptographic tools (like secure multi-party computation and functional encryption) are not adequate, we in-troduce a new cryptographic tool called Controlled Functional En-cryption (C-FE). As in functional encryption, C-FE allows a user (client) to learn only certain functions of encrypted data, using keys obtained from an authority. However, we allow (and require) the client to send a fresh key request to the authority every time it wants to evaluate a function on a ciphertext. We obtain efficient solu-tions by carefully combining CCA2 secure public-key encryption (or rerandomizable RCCA secure public-key encryption, depend-ing on the nature of security desired) with Yao’s garbled circuit. Our main contributions in this work include developing and for-mally defining the notion of C-FE; designing theoretical and prac-tical constructions of C-FE schemes achieving these definitions for specific and general classes of functions; and evaluating the perfor-mance of our constructions on various application scenarios

Garbled RAM Revisited, Part I

The notion of *garbled random-access machines* (garbled RAMs) was introduced by Lu and Ostrovsky (Eurocrypt 2013). It can be seen as an analogue of Yao\u27s garbled circuits, that allows a user to garble a RAM program directly, without performing the expensive step of converting it into a circuit. In particular, the size of the garbled program and the time it takes to create and evaluate it are only proportional to its running time on a RAM rather than its circuit size. Lu and Ostrovsky gave a candidate construction of this primitive based on pseudo-random functions (PRFs). The starting point of this work is a subtle yet difficult-to-overcome issue with the Lu-Ostrovsky construction, that prevents a proof of security from going through. Specifically, the construction requires a complex circular use of Yao garbled circuits and PRFs. As our main result, we show how to remove this circularity and get a provably secure solution using *identity-based encryption* (IBE). We also abstract out, simplify and generalize the main ideas behind the Lu-Ostrovsky construction, making them easier to understand and analyze. In a companion work to ours (Part II), Lu and Ostrovsky show an alternative approach to solving the circularity problem. Their approach relies only on the existence of one-way functions, at the price of higher overhead. Specifically, our construction has overhead \poly(k)\polylog(n) (with $k$ the security parameter and $n$ the data size), while the Lu-Ostrovsky approach can achieve overhead \poly(k)n^\eps for any constant \eps>0. It remains as an open problem to achieve an overhead of \poly(k)\polylog(n) assuming only the existence of one-way functions

On the Leakage of Fuzzy Matchers

In a biometric recognition system, the matcher compares an old and a fresh template to decide if it is a match or not. Beyond the binary output (`yes' or `no'), more information is computed. This paper provides an in-depth analysis of information leakage during distance evaluation, with an emphasis on threshold-based obfuscated distance (\textit{i.e.}, Fuzzy Matcher). Leakage can occur due to a malware infection or the use of a weakly privacy-preserving matcher, exemplified by side channel attacks or partially obfuscated designs. We provide an exhaustive catalog of information leakage scenarios as well as their impacts on the security concerning data privacy. Each of the scenarios leads to generic attacks whose impacts are expressed in terms of computational costs, hence allowing the establishment of upper bounds on the security level.Comment: Minor correction