Brief Announcement: Optimally-Resilient Unconditionally-Secure Asynchronous Multi-Party Computation Revisited

In this paper, we present an optimally-resilient, unconditionally-secure asynchronous multi-party computation (AMPC) protocol for n parties, tolerating a computationally unbounded adversary, capable of corrupting up to t < n/3 parties. Our protocol needs a communication of ?(n?) field elements per multiplication gate. This is to be compared with previous best AMPC protocol (Patra et al, ICITS 2009) in the same setting, which needs a communication of ?(n?) field elements per multiplication gate. To design our protocol, we present a simple and highly efficient asynchronous verifiable secret-sharing (AVSS) protocol, which is of independent interest

The Crypto-democracy and the Trustworthy

In the current architecture of the Internet, there is a strong asymmetry in terms of power between the entities that gather and process personal data (e.g., major Internet companies, telecom operators, cloud providers, ...) and the individuals from which this personal data is issued. In particular, individuals have no choice but to blindly trust that these entities will respect their privacy and protect their personal data. In this position paper, we address this issue by proposing an utopian crypto-democracy model based on existing scientific achievements from the field of cryptography. More precisely, our main objective is to show that cryptographic primitives, including in particular secure multiparty computation, offer a practical solution to protect privacy while minimizing the trust assumptions. In the crypto-democracy envisioned, individuals do not have to trust a single physical entity with their personal data but rather their data is distributed among several institutions. Together these institutions form a virtual entity called the Trustworthy that is responsible for the storage of this data but which can also compute on it (provided first that all the institutions agree on this). Finally, we also propose a realistic proof-of-concept of the Trustworthy, in which the roles of institutions are played by universities. This proof-of-concept would have an important impact in demonstrating the possibilities offered by the crypto-democracy paradigm.Comment: DPM 201

Resource-Efficient and Robust Distributed Computing

There has been a tremendous growth in the size of distributed systems in the past three decades. Today, distributed systems, such as the Internet, have become so large that they require highly scalable algorithms; algorithms that have asymptotically-small communication, computation, and latency costs with respect to the network size. Moreover, systems with thousands or even millions of parties distributed throughout the world is likely in danger of faults from untrusted parties. In this dissertation, we study scalable and secure distributed algorithms that can tolerate faults from untrusted parties. Throughout this work, we balance two important and often conflicting characteristics of distributed protocols: security and efficiency. Our first result is a protocol that solves the MPC problem in polylogarithmic communication and computation cost and is secure against an adversary than can corrupt a third of the parties. We adapted our synchronous MPC protocol to the asynchronous setting when the fraction of the corrupted parties are less than 1/8. Next, we presented a scalable protocol that solves the secret sharing problem between rational parties in polylogarithmic communication and computation cost. Furthermore, we presented a protocol that can solve the interactive communication problem over a noisy channel when the noise rate in unknown. In this problem, we have focused on the cost of the protocol in the resource-competitive analysis model. Unlike classic models, resource-competitive models consider the cost that the adversary must pay to succeed in corrupting the protocol

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

Network Agnostic MPC with Statistical Security

We initiate the study of the network agnostic MPC protocols with statistical security. Network agnostic protocols give the best possible security guarantees irrespective of the underlying network type. We consider the general-adversary model, where the adversary is characterized by an adversary structure which enumerates all possible candidate subsets of corrupt parties. The $\mathcal{Q}^{(k)}$ condition enforces that the union of no $k$ subsets from the adversary structure covers the party set. Given an unconditionally-secure PKI setup, known statistically-secure synchronous MPC protocols are secure against adversary structures satisfying the $\mathcal{Q}^{(2)}$ condition. Known statistically-secure asynchronous MPC protocols can tolerate $\mathcal{Q}^{(3)}$ adversary structures. Fix a set of $n$ parties $\mathcal{P} = \{P_1, ... ,P_n\}$ and adversary structures $\mathcal{Z}_s$ and $\mathcal{Z}_a$, satisfying the $\mathcal{Q}^{(2)}$ and $\mathcal{Q}^{(3)}$ conditions respectively, where $\mathcal{Z}_a \subset \mathcal{Z}_s$. Then, given an unconditionally-secure PKI, we ask whether it is possible to design a statistically-secure MPC protocol resilient against $\mathcal{Z}_s$ and $\mathcal{Z}_a$ in a synchronous and an asynchronous network respectively if the parties in $\mathcal{P}$ are unaware of the network type. We show that it is possible iff $\mathcal{Z}_s$ and $\mathcal{Z}_a$ satisfy the $\mathcal{Q}^{(2,1)}$ condition, meaning that the union of any two subsets from $\mathcal{Z}_s$ and any one subset from $\mathcal{Z}_a$ is a proper subset of $\mathcal{P}$. We design several important network agnostic building blocks with the $\mathcal{Q}^{(2,1)}$ condition, such as Byzantine broadcast, Byzantine agreement, information checking protocol, verifiable secret-sharing and secure multiplication protocol, whose complexity is polynomial in $n$ and $|\mathcal{Z}_s|$

Secure Multi-Party Computation in Large Networks

We describe scalable protocols for solving the secure multi-party computation (MPC) problem among a significant number of parties. We consider both the synchronous and the asynchronous communication models. In the synchronous setting, our protocol is secure against a static malicious adversary corrupting less than a $1/3$ fraction of the parties. In the asynchronous environment, we allow the adversary to corrupt less than a $1/8$ fraction of parties. For any deterministic function that can be computed by an arithmetic circuit with $m$ gates, both of our protocols require each party to send a number of messages and perform an amount of computation that is $\tilde{O}(m/n + \sqrt n)$. We also show that our protocols provide statistical and universally-composable security. To achieve our asynchronous MPC result, we define the threshold counting problem and present a distributed protocol to solve it in the asynchronous setting. This protocol is load balanced, with computation, communication and latency complexity of $O(\log{n})$, and can also be used for designing other load-balanced applications in the asynchronous communication model