162 research outputs found
Applications of Secure Multiparty Computation
We generate and gather a lot of data about ourselves and others, some of it highly confidential. The collection, storage and use of this data is strictly regulated by laws, but restricting the use of data often limits the benefits which could be obtained from its analysis. Secure multi-party computation (SMC), a cryptographic technology, makes it possible to execute specific programs on confidential data while ensuring that no other sensitive information from the data is leaked. SMC has been the subject of academic study for more than 30 years, but first attempts to use it for actual computations in the early 2000s – although theoretically efficient – were initially not practicable. However, improvements in the situation have made possible the secure solving of even relatively large computational tasks. This book describes how many different computational tasks can be solved securely, yet efficiently. It describes how protocols can be combined to larger applications, and how the security-efficiency trade-offs of different components of an SMC application should be chosen. Many of the results described in this book were achieved as part of the project Usable and Efficient Secure Multi-party Computation (UaESMC), which was funded by the European Commission. The book will be of interest to all those whose work involves the secure analysis of confidential data
Information-Theoretic Secure Outsourced Computation in Distributed Systems
Secure multi-party computation (secure MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. One of the earliest secure MPC primitives is the Shamir\u27s secret sharing (SSS) scheme. SSS has many advantages over other popular secure MPC primitives like garbled circuits (GC) -- it provides information-theoretic security guarantee, requires no complex long-integer operations, and often leads to more efficient protocols. Nonetheless, SSS receives less attention in the signal processing community because SSS requires a larger number of honest participants, making it prone to collusion attacks. In this dissertation, I propose an agent-based computing framework using SSS to protect privacy in distributed signal processing. There are three main contributions to this dissertation. First, the proposed computing framework is shown to be significantly more efficient than GC. Second, a novel game-theoretical framework is proposed to analyze different types of collusion attacks. Third, using the proposed game-theoretical framework, specific mechanism designs are developed to deter collusion attacks in a fully distributed manner. Specifically, for a collusion attack with known detectors, I analyze it as games between secret owners and show that the attack can be effectively deterred by an explicit retaliation mechanism. For a general attack without detectors, I expand the scope of the game to include the computing agents and provide deterrence through deceptive collusion requests. The correctness and privacy of the protocols are proved under a covert adversarial model. Our experimental results demonstrate the efficiency of SSS-based protocols and the validity of our mechanism design
Tight Bounds for Protocols with Hybrid Security
We consider broadcast and multi-party computation (MPC) in the setting where a digital signature scheme and a respective public-key infrastructure (PKI) are given among the players. However, neither the signature scheme nor the PKI are fully trusted. The goal is to achieve unconditional (PKI- and signature-independent) security up to a certain threshold, and security beyond this threshold under stronger assumptions, namely, that the forgery of signatures is impossible and/or that the given PKI is not under adversarial control. We give protocols for broadcast and MPC that achieve an optimal trade-off between these different levels of security
On security and privacy of consensus-based protocols in blockchain and smart grid
In recent times, distributed consensus protocols have received widespread attention in the area of blockchain and smart grid. Consensus algorithms aim to solve an agreement problem among a set of nodes in a distributed environment. Participants in a blockchain use consensus algorithms to agree on data blocks containing an ordered set of transactions. Similarly, agents in the smart grid employ consensus to agree on specific values (e.g., energy output, market-clearing price, control parameters) in distributed energy management protocols.
This thesis focuses on the security and privacy aspects of a few popular consensus-based protocols in blockchain and smart grid. In the blockchain area, we analyze the consensus protocol of one of the most popular payment systems: Ripple. We show how the parameters chosen by the Ripple designers do not prevent the occurrence of forks in the system. Furthermore, we provide the conditions to prevent any fork in the Ripple network. In the smart grid area, we discuss the privacy issues in the Economic Dispatch (ED) optimization problem and some of its recent solutions using distributed consensus-based approaches. We analyze two state of the art consensus-based ED protocols from Yang et al. (2013) and Binetti et al. (2014). We show how these protocols leak private information about the participants. We propose privacy-preserving versions of these consensus-based ED protocols. In some cases, we also improve upon the communication cost
Practical and Foundational Aspects of Secure Computation
Il y a des problemes qui semblent impossible a resoudre sans l'utilisation d'un tiers parti
honnete. Comment est-ce que deux millionnaires peuvent savoir qui est le plus riche sans dire a l'autre la valeur de ses biens ? Que peut-on faire pour prevenir les collisions de satellites quand
les trajectoires sont secretes ? Comment est-ce que les chercheurs peuvent apprendre les liens
entre des medicaments et des maladies sans compromettre les droits prives du patient ? Comment
est-ce qu'une organisation peut ecmpecher le gouvernement d'abuser de l'information
dont il dispose en sachant que l'organisation doit n'avoir aucun acces a cette information ?
Le Calcul multiparti, une branche de la cryptographie, etudie comment creer des protocoles
pour realiser de telles taches sans l'utilisation d'un tiers parti honnete.
Les protocoles doivent etre prives, corrects, efficaces et robustes. Un protocole est prive
si un adversaire n'apprend rien de plus que ce que lui donnerait un tiers parti honnete. Un
protocole est correct si un joueur honnete recoit ce que lui donnerait un tiers parti honnete.
Un protocole devrait bien sur etre efficace. Etre robuste correspond au fait qu'un protocole
marche meme si un petit ensemble des joueurs triche. On demontre que sous l'hypothese d'un
canal de diusion simultane on peut echanger la robustesse pour la validite et le fait d'etre
prive contre certains ensembles d'adversaires.
Le calcul multiparti a quatre outils de base : le transfert inconscient, la mise en gage, le
partage de secret et le brouillage de circuit. Les protocoles du calcul multiparti peuvent etre
construits avec uniquements ces outils. On peut aussi construire les protocoles a partir d'hypoth
eses calculatoires. Les protocoles construits a partir de ces outils sont souples et peuvent
resister aux changements technologiques et a des ameliorations algorithmiques. Nous nous
demandons si l'efficacite necessite des hypotheses de calcul. Nous demontrons que ce n'est
pas le cas en construisant des protocoles efficaces a partir de ces outils de base.
Cette these est constitue de quatre articles rediges en collaboration avec d'autres chercheurs.
Ceci constitue la partie mature de ma recherche et sont mes contributions principales
au cours de cette periode de temps. Dans le premier ouvrage presente dans cette these, nous
etudions la capacite de mise en gage des canaux bruites. Nous demontrons tout d'abord une
limite inferieure stricte qui implique que contrairement au transfert inconscient, il n'existe
aucun protocole de taux constant pour les mises en gage de bit. Nous demontrons ensuite que,
en limitant la facon dont les engagements peuvent etre ouverts, nous pouvons faire mieux et
meme un taux constant dans certains cas. Ceci est fait en exploitant la notion de cover-free
families . Dans le second article, nous demontrons que pour certains problemes, il existe un
echange entre robustesse, la validite et le prive. Il s'effectue en utilisant le partage de secret
veriable, une preuve a divulgation nulle, le concept de fantomes et une technique que nous
appelons les balles et les bacs. Dans notre troisieme contribution, nous demontrons qu'un
grand nombre de protocoles dans la litterature basee sur des hypotheses de calcul peuvent
etre instancies a partir d'une primitive appelee Transfert Inconscient Veriable, via le concept
de Transfert Inconscient Generalise. Le protocole utilise le partage de secret comme outils de
base. Dans la derniere publication, nous counstruisons un protocole efficace avec un nombre
constant de rondes pour le calcul a deux parties. L'efficacite du protocole derive du fait qu'on
remplace le coeur d'un protocole standard par une primitive qui fonctionne plus ou moins
bien mais qui est tres peu couteux. On protege le protocole contre les defauts en utilisant le
concept de privacy amplication .There are seemingly impossible problems to solve without a trusted third-party. How can
two millionaires learn who is the richest when neither is willing to tell the other how rich
he is? How can satellite collisions be prevented when the trajectories are secret? How can
researchers establish correlations between diseases and medication while respecting patient
confidentiality? How can an organization insure that the government does not abuse the
knowledge that it possesses even though such an organization would be unable to control
that information? Secure computation, a branch of cryptography, is a eld that studies how
to generate protocols for realizing such tasks without the use of a trusted third party. There
are certain goals that such protocols should achieve. The rst concern is privacy: players
should learn no more information than what a trusted third party would give them. The
second main goal is correctness: players should only receive what a trusted third party would
give them. The protocols should also be efficient. Another important property is robustness,
the protocols should not abort even if a small set of players is cheating.
Secure computation has four basic building blocks : Oblivious Transfer, secret sharing,
commitment schemes, and garbled circuits. Protocols can be built based only on these building
blocks or alternatively, they can be constructed from specific computational assumptions.
Protocols constructed solely from these primitives are
flexible and are not as vulnerable to
technological or algorithmic improvements. Many protocols are nevertheless based on computational
assumptions. It is important to ask if efficiency requires computational assumptions.
We show that this is not the case by building efficient protocols from these primitives. It is
the conclusion of this thesis that building protocols from black-box primitives can also lead
to e cient protocols.
This thesis is a collection of four articles written in collaboration with other researchers.
This constitutes the mature part of my investigation and is my main contributions to the
field during that period of time. In the first work presented in this thesis we study the commitment
capacity of noisy channels. We first show a tight lower bound that implies that in
contrast to Oblivious Transfer, there exists no constant rate protocol for bit commitments.
We then demonstrate that by restricting the way the commitments can be opened, we can
achieve better efficiency and in particular cases, a constant rate. This is done by exploiting
the notion of cover-free families. In the second article, we show that for certain problems,
there exists a trade-off between robustness, correctness and privacy. This is done by using
verifiable secret sharing, zero-knowledge, the concept of ghosts and a technique which we call
\balls and bins". In our third contribution, we show that many protocols in the literature
based on specific computational assumptions can be instantiated from a primitive known as
Verifiable Oblivious Transfer, via the concept of Generalized Oblivious Transfer. The protocol
uses secret sharing as its foundation. In the last included publication, we construct a
constant-round protocol for secure two-party computation that is very efficient and only uses
black-box primitives. The remarkable efficiency of the protocol is achieved by replacing the
core of a standard protocol by a faulty but very efficient primitive. The fault is then dealt
with by a non-trivial use of privacy amplification
A Privacy Preserving Approach to Collaborative Systemic Risk Identification : the Use-case of Supply Chain Network
Globalization, and outsourcing are two main factors which are leading to higher complexity of supply chain networks.
Due to the strategic importance of having a sustainable network it is necessary to have an enhanced supply chain
network risk management. In a supply chain network many firms depend directly or indirectly on a specific supplier.
In this regard, unknown risks of network’s structure can endanger the whole supply chain network’s robustness. In
spite of the importance of risk identification of supply chain network, firms are not willing to exchange the structural information of their network. Firms are concerned about risking their strategic positioning or established connections in the network. The paper proposes to combine secure multiparty computation cryptography methods with risk
identification algorithms from social network analysis to address this challenge. The combination enables structural
risk identification of supply chain networks without endangering firms’ competitive advantage
Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges
In recent years, blockchain has gained widespread attention as an emerging
technology for decentralization, transparency, and immutability in advancing
online activities over public networks. As an essential market process,
auctions have been well studied and applied in many business fields due to
their efficiency and contributions to fair trade. Complementary features
between blockchain and auction models trigger a great potential for research
and innovation. On the one hand, the decentralized nature of blockchain can
provide a trustworthy, secure, and cost-effective mechanism to manage the
auction process; on the other hand, auction models can be utilized to design
incentive and consensus protocols in blockchain architectures. These
opportunities have attracted enormous research and innovation activities in
both academia and industry; however, there is a lack of an in-depth review of
existing solutions and achievements. In this paper, we conduct a comprehensive
state-of-the-art survey of these two research topics. We review the existing
solutions for integrating blockchain and auction models, with some
application-oriented taxonomies generated. Additionally, we highlight some open
research challenges and future directions towards integrated blockchain-auction
models
Scalable and Robust Distributed Algorithms for Privacy-Preserving Applications
We live in an era when political and commercial entities are increasingly engaging in sophisticated cyber attacks to damage, disrupt, or censor information content and to conduct mass surveillance. By compiling various patterns from user data over time, untrusted parties could create an intimate picture of sensitive personal information such as political and religious beliefs, health status, and so forth. In this dissertation, we study scalable and robust distributed algorithms that guarantee user privacy when communicating with other parties to either solely exchange information or participate in multi-party computations. We consider scalability and robustness requirements in three privacy-preserving areas: secure multi-party computation (MPC), anonymous broadcast, and blocking-resistant Tor bridge distribution. We propose decentralized algorithms for MPC that, unlike most previous work, scale well with the number of parties and tolerate malicious faults from a large fraction of the parties. Our algorithms do not require any trusted party and are fully load-balanced. Anonymity is an essential tool for achieving privacy; it enables individuals to communicate with each other without being identified as the sender or the receiver of the information being exchanged. We show that our MPC algorithms can be effectively used to design a scalable anonymous broadcast protocol. We do this by developing a multi-party shuffling protocol that can efficiently anonymize a sequence of messages in the presence of many faulty nodes. Our final approach for preserving user privacy in cyberspace is to improve Tor; the most popular anonymity network in the Internet. A current challenge with Tor is that colluding corrupt users inside a censorship territory can completely block user\u27s access to Tor by obtaining information about a large fraction of Tor bridges; a type of relay nodes used as the Tor\u27s primary mechanism for blocking-resistance. We describe a randomized bridge distribution algorithm, where all honest users are guaranteed to connect to Tor in the presence of an adversary corrupting an unknown number of users. Our simulations suggest that, with minimal resource costs, our algorithm can guarantee Tor access for all honest users after a small (logarithmic) number of rounds
- …