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

The Bottleneck Complexity of Secure Multiparty Computation

In this work, we initiate the study of bottleneck complexity as a new communication efficiency measure for secure multiparty computation (MPC). Roughly, the bottleneck complexity of an MPC protocol is defined as the maximum communication complexity required by any party within the protocol execution. We observe that even without security, bottleneck communication complexity is an interesting measure of communication complexity for (distributed) functions and propose it as a fundamental area to explore. While achieving O(n) bottleneck complexity (where n is the number of parties) is straightforward, we show that: (1) achieving sublinear bottleneck complexity is not always possible, even when no security is required. (2) On the other hand, several useful classes of functions do have o(n) bottleneck complexity, when no security is required. Our main positive result is a compiler that transforms any (possibly insecure) efficient protocol with fixed communication-pattern for computing any functionality into a secure MPC protocol while preserving the bottleneck complexity of the underlying protocol (up to security parameter overhead). Given our compiler, an efficient protocol for any function f with sublinear bottleneck complexity can be transformed into an MPC protocol for f with the same bottleneck complexity. Along the way, we build cryptographic primitives - incremental fully-homomorphic encryption, succinct non-interactive arguments of knowledge with ID-based simulation-extractability property and verifiable protocol execution - that may be of independent interest

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 Oblivious Transfer

Motivated by the goal of improving the concrete efficiency of secure multiparty computation (MPC), we study the possibility of implementing an infrastructure for MPC. We propose an infrastructure based on oblivious transfer (OT), which would consist of OT channels between some pairs of parties in the network. We devise information-theoretically secure protocols that allow additional pairs of parties to establish secure OT correlations using the help of other parties in the network in the presence of a dishonest majority. Our main technical contribution is an upper bound that matches a lower bound of Harnik, Ishai, and Kushilevitz (Crypto 2007), who studied the number of OT channels necessary and sufficient for MPC. In particular, we characterize which n-party OT graphs G allow t-secure computation of OT correlations between all pairs of parties, showing that this is possible if and only if the complement of G does not contain the complete bipartite graph K_{n-t,n-t} as a subgraph

Optimal Load-Balanced Scalable Distributed Agreement

We consider the fundamental problem of designing classical consensus-related distributed abstractions for large-scale networks, where the number of parties can be huge. Specifically, we consider tasks such as Byzantine Agreement, Broadcast, and Committee Election, and our goal is to design scalable protocols in the sense that each honest party processes and sends a number of bits which is sub-linear in $n$, the total number of parties. In this work, we construct the first such scalable protocols for all of the above tasks. In our protocols, each party processes and sends $\tilde O (\sqrt n)$ bits throughout $\tilde O (1)$ rounds of communication, and correctness is guaranteed for at most $1/3-\epsilon$ fraction of static byzantine corruptions for every constant $\epsilon>0$ (in the full information model). All previous protocols for the considered agreement tasks were non-scalable, either because the communication complexity was linear or because the computational complexity was super polynomial. We complement our result with a matching lower bound showing that any Byzantine Agreement protocol must have $\Omega(\sqrt n)$ complexity in our model. Previously, the state of the art was the well-known $\tilde\Omega(\sqrt[3]{n})$ lower bound of Holtby, Kapron, and King (Distributed Computing, 2008)