Multi-party computation (MPC) enables a set of mutually n distrusting parties to compute any function on their private inputs. Mainly, MPC facilitates agreement on the function's output while preserving the secrecy of honest inputs, even against a subset of t parties controlled by an adversary. With applications spanning from anonymous broadcast to private auctions, MPC is considered a cornerstone of distributed cryptography, and significant research efforts have been aimed at making MPC practical in the last decade. However, most libraries either make strong assumptions like the network being bounded synchronous, or incur high computation overhead from the extensive use of expensive public-key operations that prevent them from scaling beyond a few dozen parties. This work presents Velox, an asynchronous MPC protocol that offers fairness against an optimal adversary corrupting up to t < n/3 parties. Velox significantly enhances practicality by leveraging lightweight cryptographic primitives-such as symmetric-key encryption and hash functions-which are 2-3 orders of magnitude faster than public-key operations, resulting in substantial computational efficiency. Moreover, Velox is highly communication-efficient, with linear amortized communication relative to circuit size and only O(n3) field elements of additive overhead. Concretely, Velox requires just 9.33 field elements per party per multiplication gate, more than 10× reduction compared to the state of the art. Moreover, Velox also offers Post-Quantum Security as lightweight cryptographic primitives retain their security against a quantum adversary. We implement Velox comprehensively, covering both offline and online phases, and evaluate its performance on a geographically distributed testbed through a real-world application: anonymous broadcast. Our implementation securely shuffles a batch of k = 256 messages in 4 seconds with n = 16 parties and 18 seconds with n = 64 parties, a 36× and 28.6× reduction in latency compared to the prior best work. At scale with n = 112 parties, Velox is able to shuffle the same batch of messages in under 50 seconds from end to end, illustrating its effectiveness and scalability. Overall, our work removes significant barriers faced by prior asynchronous MPC solutions, making asynchronous MPC practical and efficient for large-scale deployments involving 100s of parties.

Regular access to unpredictable and bias-resistant randomness is important for applications such as blockchains, voting, and secure distributed computing. Distributed random beacon protocols address this need by distributing trust across multiple nodes, with the majority of them assumed to be honest. Numerous applications across the blockchain space have led to the proposal of several distributed random beacon protocols, with some already implemented. However, many current random beacon systems rely on threshold cryptographic setups or exhibit high computational costs, while others expect the network to be partial or bounded synchronous. To overcome these limitations, we propose HashRand, a computation and communication-efficient asynchronous random beacon protocol that only demands secure hash and pairwise secure channels to generate beacons. HashRand has a per-node amortized communication complexity of O (λn log(n)) bits per beacon. The computational efficiency of HashRand is attributed to the two orders of magnitude lower time of a one-way Hash computation compared to discrete log exponentiation. Interestingly, besides reduced overhead, HashRand achieves Post-Quantum security by leveraging the secure Hash function against quantum adversaries, setting it apart from other random beacon protocols that use discrete log cryptography. In a geo-distributed testbed of n = 136 nodes, HashRand produces 78 beacons per minute, which is at least 5× higher than Spurt [IEEE S&P'22]. We also demonstrate the practical utility of HashRand by implementing a Post-Quantum secure Asynchronous SMR protocol, which has a response rate of over 135k transactions per second at a latency of 2.3 seconds over a WAN for n = 16 nodes.

Agreement protocols are crucial in various emerging applications, spanning from distributed (blockchains) oracles to fault-tolerant cyber-physical systems. In scenarios where sensor/oracle nodes measure a common source, maintaining output within the convex range of correct inputs, known as convex validity, is imperative. Present asynchronous convex agreement protocols employ either randomization, incurring substantial computation overhead, or approximate agreement techniques, leading to high$\tilde{\mathcal{O}(n^{3})}$communication for an$n$-node system. This paper introduces Delphi, a deterministic protocol with$\tilde{\mathcal{O}(n^{2})}$communication and minimal computation overhead. Delphi assumes that honest inputs are bounded, except with negligible probability, and integrates agreement primitives from literature with a novel weighted averaging technique. Experimental results highlight Delphi's superior performance, showcasing a significantly lower latency compared to state-of-the-art protocols. Specifically, for an$n$= 160-node system, Delphi achieves an 8x and 3x improvement in latency within CPS and AWS environments, respectively.

The target localization primitive is used for detecting and locating an adverse event called a target in a geographic area. This versatile primitive is applicable in the physical security domain (e.g., detecting intruders in an area) or for disaster preemption, such as detecting ignition events of forest fires. Prior systems implemented this primitive over large areas by deploying a network of sensor devices, which detect changes in a specific physical parameter like pressure or temperature induced by a target. However, these systems are not designed for use in adverse environments where one or more sensors can behave in a faulty manner. While many algorithms in the distributed systems literature can be naively used to implement target localization in a fault-tolerant manner, these approaches are energy-intensive as they use computationally expensive cryptographic operations not appropriate for resource-constrained sensors. We present SENSORBFT, an energy-efficient, fault-tolerant approach for target localization. SENSORBFT uses a novel asynchronous approximate agreement protocol that enables correct sensors to achieve an approximate consensus in the presence of faulty sensors. Sensors fulfill their energy budgets by tuning the precision and accuracy of localization, where precision is the difference between honest sensors' outputs and accuracy is the difference between an honest sensor's output and the target's true location. In optimal scenarios, this protocol reduces communication from$O$($n$3) to$O$($n$2) messages per round, where$n$is the number of sensors sharing coverage over a piece of area. In a sensor testbed with$n$= 19 sensors, SENSORBFT consumes 2/5 th the energy consumed by existing solutions for a minor 2% loss in accuracy, significantly enhancing efficiency and coverage.

Modern Byzantine Fault-Tolerant State Machine Replication (BFT-SMR) solutions focus on reducing communication complexity, improving throughput, or lowering latency. This work explores the energy efficiency of BFT-SMR protocols. First, we propose a novel SMR protocol that optimizes for the steady state, i.e., when the leader is correct. This is done by reducing the number of required signatures per consensus unit and the communication complexity by order of the number of nodes n compared to the state-of-the-art BFT-SMR solutions. Concretely, we employ the idea that a quorum (collection) of signatures on a proposed value is avoidable during the failure-free runs. Second, we model and analyze the energy efficiency of protocols and argue why the steady-state needs to be optimized. Third, we present an application in the cyber-physical system (CPS) setting, where we consider a partially connected system by optionally leveraging wireless multicasts among neighbors. We analytically determine the parameter ranges for when our proposed protocol offers better energy efficiency than communicating with a baseline protocol utilizing an external trusted node. We present a hypergraph-based network model and generalize previous fault tolerance results to the model. Finally, we demonstrate our approach's practicality by analyzing our protocol's energy efficiency through experiments on a CPS test bed. In particular, we observe as high as 64% energy savings when compared to the state-of-the-art SMR solution for n = 10 settings using BLE.