Secure Datastructures based on Multiparty Computation

The problem of secure multiparty computation -- performing some computation based on distributed, private inputs -- has been studied intensively for more than twenty years. This work includes both ``one shot\u27\u27 applications as well as reactive tasks, where the exact computation is not known in advance. We extend this line of work by asking whether it is possible to \emph{efficiently} both update and query secret data. A clearer formulation is, perhaps, to ask whether is it possible to construct efficient datastructures based on secure multiparty computation primitives. It is possible to construct arbitrary secure datastructures based on an oblivious RAM (ORAM). However, current state of the art information theoretically secure solutions incur a poly-logarithmic overhead on both secure computation and memory. The overhead is much smaller when considering computationally secure solutions, however, this requires secure evaluation of a one-way function as a primitive, which may reintroduce a considerable overhead. By constructing a secure priority queue we show that practical datastructures are possible. The ideas are radically different than those used in any ORAM implementation: The present solution accesses data in a \emph{deterministic} manner, whereas all ORAMs \emph{randomize} the access pattern in order to hide it. The priority queue operations -- insertion into the structure and deletion of the minimal element contained therein -- both require \bigo(\log^2 n) invocations of the cryptographic primitives (secure arithmetic and comparison) amortized in $O(1)$ rounds amortized, where $n$ is the overall number of operations performed

From usability to secure computing and back again

Secure multi-party computation (MPC) allows multiple parties to jointly compute the output of a function while preserving the privacy of any individual party’s inputs to that function. As MPC protocols transition from research prototypes to realworld applications, the usability of MPC-enabled applications is increasingly critical to their successful deployment and widespread adoption. Our Web-MPC platform, designed with a focus on usability, has been deployed for privacy-preserving data aggregation initiatives with the City of Boston and the Greater Boston Chamber of Commerce. After building and deploying an initial version of the platform, we conducted a heuristic evaluation to identify usability improvements and implemented corresponding application enhancements. However, it is difficult to gauge the effectiveness of these changes within the context of real-world deployments using traditional web analytics tools without compromising the security guarantees of the platform. This work consists of two contributions that address this challenge: (1) the Web-MPC platform has been extended with the capability to collect web analytics using existing MPC protocols, and (2) as a test of this feature and a way to inform future work, this capability has been leveraged to conduct a usability study comparing the two versions ofWeb-MPC. While many efforts have focused on ways to enhance the usability of privacy-preserving technologies, this study serves as a model for using a privacy-preserving data-driven approach to evaluate and enhance the usability of privacy-preserving websites and applications deployed in realworld scenarios. Data collected in this study yields insights into the relationship between usability and security; these can help inform future implementations of MPC solutions.Published versio

Hybrid Session Verification through Endpoint API Generation

© Springer-Verlag Berlin Heidelberg 2016.This paper proposes a new hybrid session verification methodology for applying session types directly to mainstream languages, based on generating protocol-specific endpoint APIs from multiparty session types. The API generation promotes static type checking of the behavioural aspect of the source protocol by mapping the state space of an endpoint in the protocol to a family of channel types in the target language. This is supplemented by very light run-time checks in the generated API that enforce a linear usage discipline on instances of the channel types. The resulting hybrid verification guarantees the absence of protocol violation errors during the execution of the session. We implement our methodology for Java as an extension to the Scribble framework, and use it to specify and implement compliant clients and servers for real-world protocols such as HTTP and SMTP

Hybrid session veri cation through endpoint API generation

This paper proposes a new hybrid session veri cation method- ology for applying session types directly to mainstream languages, based on generating protocol-speci c endpoint APIs from multiparty session types. The API generation promotes static type checking of the be- havioural aspect of the source protocol by mapping the state space of an endpoint in the protocol to a family of channel types in the tar- get language. This is supplemented by very light run-time checks in the generated API that enforce a linear usage discipline on instances of the channel types. The resulting hybrid veri cation guarantees the absence of protocol violation errors during the execution of the session. We have implemented our methodology for Java as an extension to the Scrib- ble framework, and used it to implement compliant clients and servers for real-world protocols such as HTTP and SMTP. The API genera- tion methodology additionally provides a platform for applying further features from session type theory: our implementation supports choice subtyping through branch interface generation, and safe permutation of I/O actions and a ne inputs through input future generation

Secure and Distributed Assessment of Privacy-Preserving Releases of GWAS

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed algorithms for a federation of genome data holders that spans multiple institutional and legislative domains to securely compute GWAS results. However, these algorithms have limited applicability, since they still require a centralized instance to decide whether GWAS results can be safely disclosed, which is in violation to privacy regulations, such as GDPR. In this work, we introduce GenDPR, a distributed middleware that leverages Trusted Execution Environments (TEEs) to securely determine a subset of the potential GWAS statistics that can be safely released. GenDPR achieves the same accuracy as centralized solutions, but requires transferring significantly less data because TEEs only exchange intermediary results but no genomes. Additionally, GenDPR can be configured to tolerate all-but-one honest-but-curious federation members colluding with the aim to expose genomes of correct members

Private set intersection: A systematic literature review

Secure Multi-party Computation (SMPC) is a family of protocols which allow some parties to compute a function on their private inputs, obtaining the output at the end and nothing more. In this work, we focus on a particular SMPC problem named Private Set Intersection (PSI). The challenge in PSI is how two or more parties can compute the intersection of their private input sets, while the elements that are not in the intersection remain private. This problem has attracted the attention of many researchers because of its wide variety of applications, contributing to the proliferation of many different approaches. Despite that, current PSI protocols still require heavy cryptographic assumptions that may be unrealistic in some scenarios. In this paper, we perform a Systematic Literature Review of PSI solutions, with the objective of analyzing the main scenarios where PSI has been studied and giving the reader a general taxonomy of the problem together with a general understanding of the most common tools used to solve it. We also analyze the performance using different metrics, trying to determine if PSI is mature enough to be used in realistic scenarios, identifying the pros and cons of each protocol and the remaining open problems.This work has been partially supported by the projects: BIGPrivDATA (UMA20-FEDERJA-082) from the FEDER Andalucía 2014– 2020 Program and SecTwin 5.0 funded by the Ministry of Science and Innovation, Spain, and the European Union (Next Generation EU) (TED2021-129830B-I00). The first author has been funded by the Spanish Ministry of Education under the National F.P.U. Program (FPU19/01118). Funding for open access charge: Universidad de Málaga/CBU

High-Performance Asynchronous Byzantine Fault Tolerance Consensus Protocol

In response to new and innovating blockchain-based systems with Internet of Things (IoT), there is a need for consensus mechanisms that can provide high transaction throughput and security, despite varying network quality. Honeybadger was the first practical, asynchronous Byzantine Fault Tolerance (BFT) consensus protocol, achieving high scalability and robustness without making any timing assumptions regarding the network. To improve the current asynchronous consensus protocols, we designed Asynchronous Byzantine Fault Tolerance (ABFT) consensus protocol through integrating threshold Elliptic Curve Digital Signature Algorithm (ECDSA) signatures and optimization of erasure coding parameters, as well as additional implementation-level optimizations. We implement a prototype of ABFT, and evaluate its performance at scale in a global WAN network and a network affected by asymmetric network degradation. Our results show that ABFT provides considerably higher performance, significantly lower computational overhead, and greater scalability than its predecessors. ABFT can reach up to 38.700 transactions per second in throughput. Furthermore, we empirically show that ABFT is unaffected by asymmetric network degradation within the fault threshold.acceptedVersio

Fast and Secure Oblivious Stable Matching over Arithmetic Circuits

The classic stable matching algorithm of Gale and Shapley (American Mathematical Monthly \u2769) and subsequent variants such as those by Roth (Mathematics of Operations Research \u2782) and Abdulkadiroglu et al. (American Economic Review \u2705) have been used successfully in a number of real-world scenarios, including the assignment of medical-school graduates to residency programs, New York City teenagers to high schools, and Norwegian and Singaporean students to schools and universities. However, all of these suffer from one shortcoming: in order to avoid strategic manipulation, they require all participants to submit their preferences to a trusted third party who performs the computation. In some sensitive application scenarios, there is no appropriate (or cost-effective) trusted party. This makes stable matching a natural candidate for secure computation. Several approaches have been proposed to overcome this, based on secure multiparty computation (MPC), fully homomorphic encryption, etc.; many of these protocols are slow and impractical for real-world use. We propose a novel primitive for privacy-preserving stable matching using MPC (i.e., arithmetic circuits, for any number of parties). Specifically, we discuss two variants of oblivious stable matching and describe an improved oblivious stable matching on the random memory access model based on lookup tables. To explore and showcase the practicality of our proposed primitive, we present detailed benchmarks (at various problem sizes) of our constructions using two popular frameworks: SCALE-MAMBA and MP-SPDZ

General-Purpose Secure Conflict-free Replicated Data Types

Conflict-free Replicated Data Types (CRDTs) are a very popular class of distributed data structures that strike a compromise between strong and eventual consistency. Ensuring the protection of data stored within a CRDT, however, cannot be done trivially using standard encryption techniques, as secure CRDT protocols would require replica-side computation. This paper proposes an approach to lift general-purpose implementations of CRDTs to secure variants using secure multiparty computation (MPC). Each replica within the system is realized by a group of MPC parties that compute its functionality. Our results include: i) an extension of current formal models used for reasoning over the security of CRDT solutions to the MPC setting; ii) a MPC language and type system to enable the construction of secure versions of CRDTs and; iii) a proof of security that relates the security of CRDT constructions designed under said semantics to the underlying MPC library. We provide an open-source system implementation with an extensive evaluation, which compares different designs with their baseline throughput and latency