Related papers: Proteus: Append-Only Ledgers for (Mostly) Trusted …
Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively train a machine learning model without having them share their private data. Recent…
The pervasive need to safely share and store information between devices calls for the replacement of centralized trust architectures with the decentralized ones. Distributed Ledger Technologies (DLTs) are seen as the most promising enabler…
This paper considers the use of novel technologies for mitigating attacks that aim at compromising intrusion detection systems (IDSs). Solutions based on collaborative intrusion detection networks (CIDNs) could increase the resilience…
Consensus mechanisms used by popular distributed ledgers are highly scalable but notoriously inefficient. Byzantine fault tolerance (BFT) protocols are efficient but far less scalable. Speculative BFT protocols such as Zyzzyva and Zyzzyva5…
Federated learning (FL) is a promising paradigm for training a global model over data distributed across multiple data owners without centralizing clients' raw data. However, sharing of local model updates can also reveal information of…
Byzantine Fault-Tolerant (BFT) protocols have recently been extensively used by decentralized data management systems with non-trustworthy infrastructures, e.g., permissioned blockchains. BFT protocols cover a broad spectrum of design…
Federated Learning (FL) is a distributed machine learning approach that has emerged as an effective way to address recent privacy concerns. However, FL introduces the need for additional security measures as FL alone is still subject to…
We present ezBFT, a novel leaderless, distributed consensus protocol capable of tolerating byzantine faults. ezBFT's main goal is to minimize the client-side latency in WAN deployments. It achieves this by (i) having no designated primary…
This paper proposes Consensus-Before-Talk (CBT), a spectrum etiquette architecture leveraged by distributed ledger technology (DLT). In CBT, secondary users' spectrum access requests reach a consensus in a distributed way, thereby enabling…
Low latency is one of the desired properties for partially synchronous Byzantine consensus protocols. Previous protocols have achieved consensus with just two communication steps either by reducing the bound on the number of faults the…
Leader election serves a well-defined role in leader-based Byzantine Fault Tolerant (BFT) protocols. Existing reputation-based leader election frameworks for partially synchronous BFTs suffer from either protocol-specific proofs, narrow…
Byzantine Fault-Tolerant (BFT) protocols play an important role in blockchains. As the deployment of such systems extends to wide-area networks, the scalability of BFT protocols becomes a critical concern. Optimizations that assign specific…
Ensuring the correctness of distributed system implementations remains a challenging and largely unaddressed problem. In this paper we present a protocol that can be used to certify the safety of consensus implementations. Our proposed…
Federated learning has arisen as a mechanism to allow multiple participants to collaboratively train a model without sharing their data. In these settings, participants (workers) may not trust each other fully; for instance, a set of…
Blockchain technology provides an auditable and tamper-proof distributed storage infrastructure for information records. This can be leveraged to support distributed workflow management. Compared to proof-of-work consensus, popularized by…
The privacy vulnerabilities of the federated learning (FL) paradigm, primarily caused by gradient leakage, have prompted the development of various defensive measures. Nonetheless, these solutions have predominantly been crafted for and…
Remote Attestation (RA) enables the integrity and authenticity of applications in Trusted Execution Environment (TEE) to be verified. Existing TEE RA designs employ a centralized trust model where they rely on a single provisioned secret…
Production LLM deployments serve diverse workloads where cost and quality requirements vary by customer tier, time of day, and query criticality. Model serving systems accept latency SLOs directly. LLM routers do not. They force operators…
Cryptocurrencies are poised to revolutionize the modern economy by democratizing commerce. These currencies operate on top of blockchain-based distributed ledgers. Existing permissionless blockchain-based protocols offer unparalleled…
SAFE is a data-centric platform for building multi-domain networked systems, i.e., systems whose participants are controlled by different principals. Participants make trust decisions by issuing local queries over logic content exchanged in…