Efficient multiparty computation secure against covert and active adversaries
Kuupäev
2017-05-12
Autorid
Ajakirja pealkiri
Ajakirja ISSN
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Kirjastaja
Abstrakt
Turvaline ühisarvutus on tänapäevase krüptograafia üks tähtsamaid kasutusviise, mis koondab elegantsed matemaatilised lahendused praktiliste rakenduste ehitamiseks, võimaldades mitmel erineval andmeomanikul sooritada oma andmetega suvalisi ühiseid arvutusi, ilma neid andmeid üksteisele avaldamata.
Passiivse ründaja vastu turvalised protokollid eeldavad, et kõik osapooled käituvad ausalt. Aktiivse ründaja vastu turvalised protokollid ei lekita privaatseid andmeid sõltumata ründaja käitumisest. Käesolevas töös esitatakse üldine meetod, mis teisendab passiivse ründaja vastu turvalised ühisarvutusprotokollid turvaliseks aktiivse ründaja vastu. Meetod on optimeeritud kolme osapoolega arvutusteks üle algebraliste ringide; praktikas on see väga efektiivne mudel, mis teeb reaalse maailma rakendused teostatavateks. Meetod lisab esialgsele arvutusprotokollile täitmisjärgse verifitseerimisfaasi, mis muudab valesti käitunud osapooltel vahelejäämise vältimise tõenäosuse kaduvväikseks, säilitades esialgse protokolli turvagarantiid.
Lisaks uurib käesolev töö rünnete uut eesmärki, mis seisneb mingi ausa osapoole vaate manipuleerimises sellisel viisil, et ta saaks midagi teada teise ausa osapoole privaatsete andmete kohta. Ründaja ise ei tarvitse seda infot üldse teada saada. Sellised ründed on olulised, sest need kohustavad ausat osapoolt tühjendama oma süsteemi teiste osapoolte andmetest, kuid see ülesanne võib olla päris mittetriviaalne. Eelnevalt pakutud verifitseerimismehhanisme täiendatakse nii, et privaatsed andmed oleksid kaitstud ka ausate osapoolte eest.
Paljud ühisarvutusplatvormid on varustatud programmeerimiskeelega, mis võimaldab kirjutada privaatsust säilitavaid rakendusi ilma allolevale krüptograafiale mõtlemata. Juhul, kui programm sisaldab tingimuslauseid, kus arvutusharu valik sõltub privaatsetest andmetest, ei tohi ükski osapool haru valikust midagi teada, nii et üldjuhul peavad osapooled täitma kõik harud. Harude suure arvu kor-ral võib arvutuslik lisakulu olla ülisuur, sest enamik vahetulemustest visatakse ära. Käesolevas töös pakutakse selliseid lisakulusid vähendavat optimeerimist.
Secure multiparty computation is one of the most important employments of modern cryptography, bringing together elegant mathematical solutions to build up useful practical applications. It allows several distinct data owners to perform arbitrary collaborative computation on their private data without leaking any information to each other. Passively secure protocols assume that all parties follow the protocol rules. Actively secure protocols do not leak private data regardless of the attacker’s behaviour. This thesis presents a generic method for turning passively secure multiparty protocols to actively secure ones. The method is optimized for three party computation over algebraic rings, which has proven to be quite an efficient model, making large real-world applications feasible. Our method adds to the protocol a post-execution verification phase that allows a misbehaving party to escape detection only with negligible probability. It preserves the privacy guarantees of the original protocol. In this thesis, we also study a new adversarial goal in multiparty protocols. The goal is to manipulate the view of some honest party in such a way, that this honest party learns the private data of some other honest party. The adversary itself might not learn this data at all. Such attacks are significant because they create a liability to the first honest party to clean its systems from the second honest party’s data, which may be a highly non-trivial task in practice. We check the security of our verification mechanism in this new model, and we propose some minor modifications that ensure data protection also from the honest parties. Many secure multiparty computation platforms come with a programming language that allows the developer to write privacy-preserving applications without thinking of the underlying cryptography. If a program contains conditional statements where the choice of the computational branch depends on private data, then no party should know which branch has been executed, so in general the parties need to execute all of them. If the number of branches is large, the computational overhead may be enormous, as most of the intermediate results are just discarded. In this thesis, we propose an automatic optimization that reduces this overhead.
Secure multiparty computation is one of the most important employments of modern cryptography, bringing together elegant mathematical solutions to build up useful practical applications. It allows several distinct data owners to perform arbitrary collaborative computation on their private data without leaking any information to each other. Passively secure protocols assume that all parties follow the protocol rules. Actively secure protocols do not leak private data regardless of the attacker’s behaviour. This thesis presents a generic method for turning passively secure multiparty protocols to actively secure ones. The method is optimized for three party computation over algebraic rings, which has proven to be quite an efficient model, making large real-world applications feasible. Our method adds to the protocol a post-execution verification phase that allows a misbehaving party to escape detection only with negligible probability. It preserves the privacy guarantees of the original protocol. In this thesis, we also study a new adversarial goal in multiparty protocols. The goal is to manipulate the view of some honest party in such a way, that this honest party learns the private data of some other honest party. The adversary itself might not learn this data at all. Such attacks are significant because they create a liability to the first honest party to clean its systems from the second honest party’s data, which may be a highly non-trivial task in practice. We check the security of our verification mechanism in this new model, and we propose some minor modifications that ensure data protection also from the honest parties. Many secure multiparty computation platforms come with a programming language that allows the developer to write privacy-preserving applications without thinking of the underlying cryptography. If a program contains conditional statements where the choice of the computational branch depends on private data, then no party should know which branch has been executed, so in general the parties need to execute all of them. If the number of branches is large, the computational overhead may be enormous, as most of the intermediate results are just discarded. In this thesis, we propose an automatic optimization that reduces this overhead.
Kirjeldus
Märksõnad
turvalised ühisarvutused, krüptograafia, cryptography, secure multi-party computation