Universally composable privacy preserving finite automata execution with low online and offline complexity

In this paper, we propose efficient protocols to obliviously execute non-deterministic and deterministic finite automata (NFA and DFA) in the arithmetic black box (ABB) model. In contrast to previous approaches, our protocols do not use expensive public-key operations, relying instead only on computation with secret-shared values. Additionally, the complexity of our protocols is largely offline. In particular, if the DFA is available during the precomputation phase, then the online complexity of evaluating it on an input string requires a small constant number of operations per character. This makes our protocols highly suitable for certain outsourcing applications

Privacy-Preserving Regular Expression Matching using Nondeterministic Finite Automata

Motivated by the privacy requirements in network intrusion detection and DNS policy checking, we have developed a suite of protocols and algorithms for regular expression matching with enhanced privacy: - A new regular expression matching algorithm that is oblivious to the input strings, of which the complexity is only $O(mn)$ where $m$ and $n$ are the length of strings and the regular expression respectively. It is achieved by exploiting the structure of the Thompson nondeterministic automata. - A zero-knowledge proof of regular expression pattern matching in which a prover generates a proof to demonstrate that a public regular expression matches her input string without revealing the string itself. -Two secure-regex protocols that ensure the privacy of both the string and regular expression. The first protocol is based on the oblivious stack and reduces the complexity of the state-of-the-art from $O(mn^2)$ to $O(mn\log n)$. The second protocol relies on the oblivious transfer and performs better empirically when the size of regular expressions is smaller than $2^{12}$. We also evaluated our protocols in the context of encrypted DNS policy checking and intrusion detection and achieved 4.5X improvements over the state-of-the-art. These results also indicate the practicality of our approach in real-world applications

The Theory and Application of Privacy-preserving Computation

Privacy is a growing concern in the digital world as more information becomes digital every day. Often the implications of how this information could be exploited for nefarious purposes are not explored until after the fact. The public is becoming more concerned about this. This dissertation introduces a new paradigm for tackling the problem, namely, transferable multiparty computation (T-MPC). T-MPC builds upon existing multiparty computation work yet allows some additional flexibility in the set of participants. T-MPC is orders of magnitude more efficient for certain applications. This greatly increases the scalability of the sizes of networks supported for privacy-preserving computation

Cryptographic protocol design

In this work, we investigate the security of interactive computations. The main emphasis is on the mathematical methodology that is needed to formalise and analyse various security properties. Differently from many classical treatments of secure multi-party computations, we always quantify security in exact terms. Although working with concrete time bounds and success probabilities is technically more demanding, it also has several advantages. As all security guarantees are quantitative, we can always compare different protocol designs. Moreover, these security guarantees also have a clear economical interpretation and it is possible to compare cryptographic and non-cryptographic solutions. The latter is extremely important in practice, since cryptographic techniques are just one possibility to achieve practical security. Also, working with exact bounds makes reasoning errors more apparent, as security proofs are less abstract and it is easier to locate false claims. The choice of topics covered in this thesis was guided by two principles. Firstly, we wanted to give a coherent overview of the secure multi-party computation that is based on exact quantification of security guarantees. Secondly, we focused on topics that emerged from the author's own research. In that sense, the thesis generalises many methodological discoveries made by the author. As surprising as it may seem, security definitions and proofs mostly utilise principles of hypothesis testing and analysis of stochastic algorithms. Thus, we start our treatment with hypothesis testing and its generalisations. In particular, we show how to quantify various security properties, using security games as tools. Next, we review basic proof techniques and explain how to structure complex proofs so they become easily verifiable. In a nutshell, we describe how to represent a proof as a game tree, where each edge corresponds to an elementary proof step. As a result, one can first verify the overall structure of a proof by looking at the syntactic changes in the game tree and only then verify all individual proof steps corresponding to the edges. The remaining part of the thesis is dedicated to various aspects of protocol design. Firstly, we discuss how to formalise various security goals, such as input-privacy, output-consistency and complete security, and how to choose a security goal that is appropriate for a specific setting. Secondly, we also explore alternatives to exact security. More precisely, we analyse connections between exact and asymptotic security models and rigorously formalise a notion of subjective security. Thirdly, we study in which conditions protocols preserve their security guarantees and how to safely combine several protocols. Although composability results are common knowledge, we look at them from a slightly different angle. Namely, it is irrational to design universally composable protocols at any cost; instead, we should design computationally efficient protocols with minimal usage restrictions. Thus, we propose a three-stage design procedure that leads to modular security proofs and minimises usage restrictions

Phoenix: Secure Computation in an Unstable Network with Dropouts and Comebacks

We consider the task of designing secure computation protocols in an unstable network where honest parties can drop out at any time, according to a schedule provided by the adversary. This type of setting, where even honest parties are prone to failures, is more realistic than traditional models, and has therefore gained a lot of attention recently. Our model, Phoenix, enables a new approach to secure multiparty computation with dropouts, allowing parties to drop out and re-enter the computation on an adversarially-chosen schedule and without assuming that these parties receive the messages that were sent to them while being offline - features that are not available in the existing models of Sleepy MPC (Guo et al., CRYPTO \u2719), Fluid MPC (Choudhuri et al., CRYPTO \u2721 ) and YOSO (Gentry et al. CRYPTO \u2721). Phoenix does assume an upper bound on the number of rounds that an honest party can be off-line---otherwise protocols in this setting cannot guarantee termination within a bounded number of rounds; however, if one settles for a weaker notion, namely guaranteed output delivery only for honest parties who stay on-line long enough, this requirement is not necessary. In this work, we study the settings of perfect, statistical and computational security and design MPC protocols in each of these scenarios. We assume that the intersection of online-and-honest parties from one round to the next is at least $2t+1$, $t+1$ and $1$ respectively, where $t$ is the number of (actively) corrupt parties. We show the intersection requirements to be optimal. Our (positive) results are obtained in a way that may be of independent interest: we implement a traditional stable network on top of the unstable one, which allows us to plug in \emph{any} MPC protocol on top. This approach adds a necessary overhead to the round count of the protocols, which is related to the maximal number of rounds an honest party can be offline. We also present a novel, perfectly secure MPC protocol in the preprocessing model that avoids this overhead by following a more direct approach rather than first building a stable network and then using existing protocols. We introduce our network model in the UC-framework, show that the composition theorem still holds, and prove the security of our protocols within this setting

A Comprehensive Protocol Suite for Secure Two-Party Computation

Turvaline ühisarvutus võimaldab üksteist mitte usaldavatel osapooltel teha arvutusi tundlikel andmetel nii, et kellegi privaatsed andmed ei leki teistele osapooltele. Sharemind on kaua arenduses olnud turvalise ühisarvutuse platvorm, mis jagab tundlikke andmeid ühissalastuse abil kolme serveri vahel. Sharemindi kolme osapoolega protokolle on kasutatud suuremahuliste rakenduste loomisel. Igapäevaelus leidub rakendusi, mille puhul kahe osapoolega juurustusmudel on kolme osapoolega variandist sobivam majanduslikel või organisatoorsetel põhjustel. Selles töös kirjeldame ja teostame täieliku protokollistiku kahe osapoolega turvaliste arvutuste jaoks. Loodud protokollistiku eesmärk on pakkuda kolme osapoolega juurutusmudelile võrdväärne alternatiiv, mis on ka jõudluses võrreldaval tasemel. Kahe osapoole vahelised turvalise aritmeetika protokollid tuginevad peamiselt Beaveri kolmikute ette arvutamisele. Selleks, et saavutada vajalikku jõudlust, oleme välja töötanud tõhusad ette arvutamise meetodid, mis kasutavad uudsel viisil N-sõnumi pimeedastuse pikendamise protokolle. Meie meetodite eeliseks on alternatiividest väiksem võrgusuhtluse maht. Töös käsitleme ka insenertehnilisi väljakutseid, mis selliste meetodite teostamisel ette tulid. Töös esitame kirjeldatud konstruktsioonide turvalisuse ja korrektsuse tõestused. Selleks kasutame vähem eelduseid, kui tüüpilised teaduskirjanduses leiduvad tõestused. Üheks peamiseks saavutuseks on juhusliku oraakli mudeli vätimine. Meie kirjeldatud ja teostatud täisarvuaritmeetika ja andmetüüpide vaheliste teisendusprotokollide jõudlustulemused on võrreldavad kolme osapoole protokollide jõudlusega. Meie töö tulemusena saab Sharemindi platvormil teostada kahe osapoolega turvalisi ühisarvutusi.Secure multi-party computation allows a number of distrusting parties to collaborate in extracting new knowledge from their joint private data, without any party learning the other participants' secrets in the process. The efficient and mature Sharemind secure computation platform has relied on a three-party suite of protocols based on secret sharing for supporting large real-world applications. However, in some scenarios, a two-party model is a better fit when no natural third party is involved in the application. In this work, we design and implement a full protocol suite for two-party computations on Sharemind, providing an alternative and viable solution in such cases. We aim foremost for efficiency that is on par with the existing three-party protocols. To this end, we introduce more efficient techniques for the precomputation of Beaver triples using oblivious transfer extension, as the two-party protocols for arithmetic fundamentally rely on efficient triple generation. We reduce communication costs compared to existing methods by using 1-out-of-N oblivious transfer extension in a novel way, and provide insights into engineering challenges for efficiently implementing these methods. Furthermore, we show security of our constructions using strictly weaker assumptions than have been previously required by avoiding the random oracle model. We describe and implement a large amount of integer operations and data conversion protocols that are competitive with the existing three-party protocols, providing an overall solid foundation for two-party computations on Sharemind

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure

Anonymous Point Collection - Improved Models and Security Definitions

This work is a comprehensive, formal treatment of anonymous point collection. The proposed definition does not only provide a strong notion of security and privacy, but also covers features which are important for practical use. An efficient realization is presented and proven to fulfill the proposed definition. The resulting building block is the first one that allows for anonymous two-way transactions, has semi-offline capabilities, yields constant storage size, and is provably secure