Related papers: One For All: Formally Verifying Protocols which us…

Signcryption is a cryptographic primitive which performs encryption and signature in a single logical step. In conventional signcryption only receiver of the signcrypted text can verify the authenticity of the origin i.e. signature of the…

This paper introduces Flamingo, a system for secure aggregation of data across a large set of clients. In secure aggregation, a server sums up the private inputs of clients and obtains the result without learning anything about the…

This paper formalizes the proves the security of the Bridgeless protocol, a protocol able to bridge tokens between various chains. The Bridgeless protocol is run by a set of validators, responsible for verifying deposit transactions on the…

Federated learning (FL) is emerging as a sought-after distributed machine learning architecture, offering the advantage of model training without direct exposure of raw data. With advancements in network infrastructure, FL has been…

A long-standing research problem in security protocol design is how to efficiently verify security protocols with tamper-resistant global states. In this paper, we address this problem by first proposing a protocol specification framework,…

With the rise of cryptocurrencies, many new applications built on decentralized blockchains have emerged. Blockchains are full-stack distributed systems where multiple sub-systems interact. While many deployed blockchains and decentralized…

Earth System Models (ESMs) are critical for understanding past climates and projecting future scenarios. However, the complexity of these models, which include large code bases, a wide community of developers, and diverse computational…

Using an algorithm due to Safra for distributed termination detection as a running example, we present the main tools for verifying specifications written in TLA+. Examining their complementary strengths and weaknesses, we suggest a…

Transparency protocols are protocols whose actions can be publicly monitored by observers (such observers may include regulators, rights advocacy groups, or the general public). The observed actions are typically usages of private keys such…

The use of codes defined by sparse characteristic matrices, like QC-LDPC and QC-MDPC codes, has become an established solution to design secure and efficient code-based public-key encryption schemes, as also witnessed by the ongoing NIST…

Secure federated learning enables collaborative model training across decentralized users while preserving data privacy. A key component is secure aggregation, which keeps individual updates hidden from both the server and users, while also…

Federated learning enables the collaborative learning of a global model on diverse data, preserving data locality and eliminating the need to transfer user data to a central server. However, data privacy remains vulnerable, as attacks can…

Blockchain is a decentralized network to increase trust, integrity, and transparency of transactions. With the exponential growth of transactions in the realm of Blockchain, especially in Bitcoin, Blockchain size increases as all…

We consider a cross-silo federated learning (FL) setting where a machine learning model with a fully connected first layer is trained between different clients and a central server using FedAvg, and where the aggregation step can be…

This paper introduces Generalized Quantum-assisted Digital Signature (GQaDS), an improved version of a recently proposed scheme whose information theoretic security is inherited by adopting QKD keys for digital signature purposes. Its…

Verifiable Secret-Sharing (VSS) is a fundamental primitive in secure distributed computing. It is used as a building block in several distributed computing tasks, such as Byzantine agreement and secure multi-party computation. In this…

Considering the world's IoT development and market, it is necessary to guarantee the security of the developed IoT applications as well as the privacy of their end users. In this sense, Federated Identity Management (FIdM) systems can be of…

Online signature verification technologies, such as those available in banks and post offices, rely on dedicated digital devices such as tablets or smart pens to capture, analyze and verify signatures. In this paper, we suggest a novel…

Current cloud and network infrastructures do not employ privacy-preserving methods to protect their assets. Anonymous credential schemes are a cryptographic building block that enables the certification of data structures and prove…

Secure federated learning is a privacy-preserving framework to improve machine learning models by training over large volumes of data collected by mobile users. This is achieved through an iterative process where, at each iteration, users…