Adaptively Secure Garbled Circuits from One-Way Functions

A garbling scheme is used to garble a circuit $C$ and an input $x$ in a way that reveals the output $C(x)$ but hides everything else. In many settings, the circuit can be garbled off-line without strict efficiency constraints, but the input must be garbled very efficiently on-line, with much lower complexity than evaluating the circuit. Yao\u27s scheme has essentially optimal on-line complexity, but only achieves selective security, where the adversary must choose the input $x$ prior to seeing the garbled circuit. It has remained an open problem to achieve adaptive security, where the adversary can choose $x$ after seeing the garbled circuit, while preserving on-line efficiency. In this work, we modify Yao\u27s scheme in a way that allows us to prove adaptive security under one-way functions. As our main instantiation, we get a scheme where the on-line complexity is only proportional to the width $w$ of the circuit, which corresponds to the space complexity of the computation, but is independent of the circuit\u27s depth $d$. Alternately, we can also get an instantiation where the on-line complexity is only proportional to the input/output size and the depth $d$ of the circuit but independent of its width $w$, albeit in this case we incur a $2^{O(d)}$ security loss in our reduction. More broadly, we relate the on-line complexity of adaptively secure garbling schemes in our framework to a certain type of pebble complexity of the circuit. As our main tool, of independent interest, we develop a new notion of somewhere equivocal encryption, which allows us to efficiently equivocate on a small subset of the message bits

A Framework for Efficient Signatures, Ring Signatures and Identity Based Encryption in the Standard Model

In this work, we present a generic framework for constructing efficient signature schemes, ring signature schemes, and identity based encryption schemes, all in the standard model (without relying on random oracles). We start by abstracting the recent work of Hohenberger and Waters (Crypto 2009), and specifically their ``prefix method\u27\u27. We show a transformation taking a signature scheme with a very weak security guarantee (a notion that we call a-priori-message unforgeability under static chosen message attack) and producing a fully secure signature scheme (i.e., existentially unforgeable under adaptive chosen message attack). Our transformation uses the notion of chameleon hash functions, defined by Krawczyk and Rabin (NDSS 2000) and the ``prefix method\u27\u27. Constructing such weakly secure schemes seems to be significantly easier than constructing fully secure ones, and we present {\em simple} constructions based on the RSA assumption, the {\em short integer solution} (SIS) assumption, and the {\em computational Diffie-Hellman} (CDH) assumption over bilinear groups. Next, we observe that this general transformation also applies to the regime of ring signatures. Using this observation, we construct new (provably secure) ring signature schemes: one is based on the {\em short integer solution} (SIS) assumption, and the other is based on the CDH assumption over bilinear groups. As a building block for these constructions, we define a primitive that we call \emph{ring trapdoor functions}. We show that ring trapdoor functions imply ring signatures under a weak definition, which enables us to apply our transformation to achieve full security. Finally, we show a connection between ring signature schemes and identity based encryption (IBE) schemes. Using this connection, and using our new constructions of ring signature schemes, we obtain two IBE schemes: The first is based on the {\em learning with error} (LWE) assumption, and is similar to the recently introduced IBE scheme of Cash-Hofheinz-Kiltz-Peikert; The second is based on the $d$-linear assumption over bilinear groups

Universal Location Referencing and Homomorphic Evaluation of Geospatial Query

Location data is an important piece of contextual information in location-driven features for geosocial and pervasive computing applications. In this paper, we propose to geo-hash locations using space-filling curves, which are dimension reduction techniques that preserve locality. The proposed location referencing method is agnostic to specific maps or precoded location models and can effectively preserve users’ location privacy based on user preferences. We employ post-quantum-secure encryption on location data and privacy preferences to minimize the risk of data leakage. We also design three algorithms to homomorphically compute geospatial queries on the encrypted location data without revealing either user locations or user preferences. One of the three proposed algorithms reduces the multiplicative depth by more than half; thus, significantly speeding up homomorphic computations. We then present a prototype of the proposed system and algorithms using a somewhat homomorphic encryption scheme and our optimization techniques. A systematic evaluation of the prototype demonstrates its utility in spatial cloaking

IST Austria Thesis

Many security definitions come in two flavors: a stronger “adaptive” flavor, where the adversary can arbitrarily make various choices during the course of the attack, and a weaker “selective” flavor where the adversary must commit to some or all of their choices a-priori. For example, in the context of identity-based encryption, selective security requires the adversary to decide on the identity of the attacked party at the very beginning of the game whereas adaptive security allows the attacker to first see the master public key and some secret keys before making this choice. Often, it appears to be much easier to achieve selective security than it is to achieve adaptive security. A series of several recent works shows how to cleverly achieve adaptive security in several such scenarios including generalized selective decryption [Pan07][FJP15], constrained PRFs [FKPR14], and Yao’s garbled circuits [JW16]. Although the above works expressed vague intuition that they share a common technique, the connection was never made precise. In this work we present a new framework (published at Crypto ’17 [JKK+17a]) that connects all of these works and allows us to present them in a unified and simplified fashion. Having the framework in place, we show how to achieve adaptive security for proxy re-encryption schemes (published at PKC ’19 [FKKP19]) and provide the first adaptive security proofs for continuous group key agreement protocols (published at S&P ’21 [KPW+21]). Questioning optimality of our framework, we then show that currently used proof techniques cannot lead to significantly better security guarantees for "graph-building" games (published at TCC ’21 [KKPW21a]). These games cover generalized selective decryption, as well as the security of prominent constructions for constrained PRFs, continuous group key agreement, and proxy re-encryption. Finally, we revisit the adaptive security of Yao’s garbled circuits and extend the analysis of Jafargholi and Wichs in two directions: While they prove adaptive security only for a modified construction with increased online complexity, we provide the first positive results for the original construction by Yao (published at TCC ’21 [KKP21a]). On the negative side, we prove that the results of Jafargholi and Wichs are essentially optimal by showing that no black-box reduction can provide a significantly better security bound (published at Crypto ’21 [KKPW21c])

Secure Multiparty Computation with Identifiable Abort from Vindicating Release

In the dishonest-majority setting, generic secure multiparty computation (MPC) protocols are fundamentally vulnerable to attacks in which malicious participants learn their outputs and then force the protocol to abort before outputs are delivered to the honest participants. In other words, generic MPC protocols typically guarantee security with abort. This flavor of security permits denial-of-service attacks in many applications, unless the cheating participants who cause aborts are identified. At present, there is a substantial performance gap between the best known protocols that are secure with non-identifiable abort, and the best known protocols that achieve security with identifiable abort (IA). Known constructions with IA rely on generic zero-knowledge proofs, adaptively secure oblivious transfer (OT) protocols, or homomorphic primitives. We present a novel approach for realizing functionalities with a weak form of input-revealing IA, which is based on delicate and selective revealing of committed input values. We refer to this new approach as vindicating release. When our approach is applied to several well-known protocols---including a variant of PVW OT, Softspoken OT extension, DKLs multiplication, and MASCOT generic MPC---the resulting protocols can be combined to realize any sampling functionality with (standard) IA. Such a realization is statistically secure given a variant of statically-corruptable ideal OT, and it differs minimally in terms of cost, techniques, and analysis from the equivalent realization (using the same well-known protocols, unmodified) that lacks identifiability. Using our protocol to sample the correlated randomness of the IOZ compiler reduces the compiler\u27s requirements from an adaptively secure OT protocol to a variant of statically-corruptable ideal OT

Geo-tagging and privacy-preservation in mobile cloud computing

With the emerge of the cloud computing service and the explosive growth of the mobile devices and applications, mobile computing technologies and cloud computing technologies have been drawing significant attentions. Mobile cloud computing, with the synergy between the cloud and mobile technologies, has brought us new opportunities to develop novel and practical systems such as mobile multimedia systems and cloud systems that provide collaborative data-mining services for data from disparate owners (e.g., mobile users). However, it also creates new challenges, e.g., the algorithms deployed in the computationally weak mobile device require higher efficiency, and introduces new problems such as the privacy concern when the private data is shared in the cloud for collaborative data-mining. The main objectives of this dissertation are: 1. to develop practical systems based on the unique features of mobile devices (i.e., all-in-one computing platform and sensors) and the powerful computing capability of the cloud; 2. to propose solutions protecting the data privacy when the data from disparate owners are shared in the cloud for collaborative data-mining. We first propose a mobile geo-tagging system. It is a novel, accurate and efficient image and video based remote target localization and tracking system using the Android smartphone. To cope with the smartphones' computational limitation, we design light-weight image/video processing algorithms to achieve a good balance between estimation accuracy and computational complexity. Our system is first of its kind and we provide first hand real-world experimental results, which demonstrate that our system is feasible and practicable. To address the privacy concern when data from disparate owners are shared in the cloud for collaborative data-mining, we then propose a generic compressive sensing (CS) based secure multiparty computation (MPC) framework for privacy-preserving collaborative data-mining in which data mining is performed in the CS domain. We perform the CS transformation and reconstruction processes with MPC protocols. We modify the original orthogonal matching pursuit algorithm and develop new MPC protocols so that the CS reconstruction process can be implemented using MPC. Our analysis and experimental results show that our generic framework is capable of enabling privacy preserving collaborative data-mining. The proposed framework can be applied to many privacy preserving collaborative data-mining and signal processing applications in the cloud. We identify an application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We further propose a privacy preserving storage and secure watermark detection framework by adopting our generic framework to address such a requirement. In our secure watermark detection framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a compressive sensing domain to protect the privacy. We also give mathematical and statistical analysis to derive the expected watermark detection performance in the compressive sensing domain, based on the target image, watermark pattern and the size of the compressive sensing matrix (but without the actual CS matrix), which means that the watermark detection performance in the CS domain can be estimated during the watermark embedding process. The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the compressive sensing domain is feasible. By taking advantage of our mobile geo-tagging system and compressive sensing based privacy preserving data-mining framework, we develop a mobile privacy preserving collaborative filtering system. In our system, mobile users can share their personal data with each other in the cloud and get daily activity recommendations based on the data-mining results generated by the cloud, without leaking the privacy and secrecy of the data to other parties. Experimental results demonstrate that the proposed system is effective in enabling efficient mobile privacy preserving collaborative filtering services.Includes bibliographical references (pages 126-133)

Frontiers in Lattice Cryptography and Program Obfuscation

In this dissertation, we explore the frontiers of theory of cryptography along two lines. In the first direction, we explore Lattice Cryptography, which is the primary sub-area of post-quantum cryptographic research. Our first contribution is the construction of a deniable attribute-based encryption scheme from lattices. A deniable encryption scheme is secure against not only eavesdropping attacks as required by semantic security, but also stronger coercion attacks performed after the fact. An attribute-based encryption scheme allows ``fine-grained'' access to ciphertexts, allowing for a decryption access policy to be embedded in ciphertexts and keys. We achieve both properties simultaneously for the first time from lattices. Our second contribution is the construction of a digital signature scheme that enjoys both short signatures and a completely tight security reduction from lattices. As a matter of independent interest, we give an improved method of randomized inversion of the G gadget matrix, which reduces the noise growth rate in homomorphic evaluations performed in a large number of lattice-based cryptographic schemes, without incurring the high cost of sampling discrete Gaussians. In the second direction, we explore Cryptographic Program Obfuscation. A program obfuscator is a type of cryptographic software compiler that outputs executable code with the guarantee that ``whatever can be hidden about the internal workings of program code, is hidden.'' Indeed, program obfuscation can be viewed as a ``universal and cryptographically-complete'' tool. Our third contribution is the first, full-scale implementation of secure program obfuscation in software. Our toolchain takes code written in a C-like programming language, specialized for cryptography, and produces secure, obfuscated software. Our fourth contribution is a new cryptanalytic attack against a variety of ``early'' program obfuscation candidates. We provide a general, efficiently-testable property for any two branching programs, called partial inequivalence, which we show is sufficient for launching an ``annihilation attack'' against several obfuscation candidates based on Garg-Gentry-Halevi multilinear maps

On Foundations of Protecting Computations

Information technology systems have become indispensable to uphold our way of living, our economy and our safety. Failure of these systems can have devastating effects. Consequently, securing these systems against malicious intentions deserves our utmost attention. Cryptography provides the necessary foundations for that purpose. In particular, it provides a set of building blocks which allow to secure larger information systems. Furthermore, cryptography develops concepts and tech- niques towards realizing these building blocks. The protection of computations is one invaluable concept for cryptography which paves the way towards realizing a multitude of cryptographic tools. In this thesis, we contribute to this concept of protecting computations in several ways. Protecting computations of probabilistic programs. An indis- tinguishability obfuscator (IO) compiles (deterministic) code such that it becomes provably unintelligible. This can be viewed as the ultimate way to protect (deterministic) computations. Due to very recent research, such obfuscators enjoy plausible candidate constructions. In certain settings, however, it is necessary to protect probabilistic com- putations. The only known construction of an obfuscator for probabilistic programs is due to Canetti, Lin, Tessaro, and Vaikuntanathan, TCC, 2015 and requires an indistinguishability obfuscator which satisfies extreme security guarantees. We improve this construction and thereby reduce the require- ments on the security of the underlying indistinguishability obfuscator. (Agrikola, Couteau, and Hofheinz, PKC, 2020) Protecting computations in cryptographic groups. To facilitate the analysis of building blocks which are based on cryptographic groups, these groups are often overidealized such that computations in the group are protected from the outside. Using such overidealizations allows to prove building blocks secure which are sometimes beyond the reach of standard model techniques. However, these overidealizations are subject to certain impossibility results. Recently, Fuchsbauer, Kiltz, and Loss, CRYPTO, 2018 introduced the algebraic group model (AGM) as a relaxation which is closer to the standard model but in several aspects preserves the power of said overidealizations. However, their model still suffers from implausibilities. We develop a framework which allows to transport several security proofs from the AGM into the standard model, thereby evading the above implausi- bility results, and instantiate this framework using an indistinguishability obfuscator. (Agrikola, Hofheinz, and Kastner, EUROCRYPT, 2020) Protecting computations using compression. Perfect compression algorithms admit the property that the compressed distribution is truly random leaving no room for any further compression. This property is invaluable for several cryptographic applications such as “honey encryption” or password-authenticated key exchange. However, perfect compression algorithms only exist for a very small number of distributions. We relax the notion of compression and rigorously study the resulting notion which we call “pseudorandom encodings”. As a result, we identify various surprising connections between seemingly unrelated areas of cryptography. Particularly, we derive novel results for adaptively secure multi-party computation which allows for protecting computations in distributed settings. Furthermore, we instantiate the weakest version of pseudorandom encodings which suffices for adaptively secure multi-party computation using an indistinguishability obfuscator. (Agrikola, Couteau, Ishai, Jarecki, and Sahai, TCC, 2020

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control