Related papers: DEFenD: A Secure and Privacy-Preserving Decentrali…
When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are…
Decentralized optimization has become a standard paradigm for solving large-scale decision-making problems and training large machine learning models without centralizing data. However, this paradigm introduces new privacy and security…
Federated learning has been rapidly evolving and gaining popularity in recent years due to its privacy-preserving features, among other advantages. Nevertheless, the exchange of model updates and gradients in this architecture provides new…
This paper presents DESTinE Block, a blockchain-based data storage framework designed for power systems and optimized for resource-constrained environments, including grid-edge devices such as single-board computers. The proposed…
Distributed model predictive control (MPC) has been proven a successful method in regulating the operation of large-scale networks of constrained dynamical systems. This paper is concerned with cooperative distributed MPC in which the…
The exponential growth of collected, processed, and shared microdata has given rise to concerns about individuals' privacy. As a result, laws and regulations have emerged to control what organisations do with microdata and how they protect…
Modern distributed data management systems face a new challenge: how can autonomous, mutually-distrusting parties cooperate safely and effectively? Addressing this challenge brings up questions familiar from classical distributed systems:…
Nowadays, high-volume and privacy-sensitive data are generated by mobile devices, which are better to be preserved on devices and queried on demand. However, data analysts still lack a uniform way to harness such distributed on-device data.…
Digitisation is often viewed as beneficial to a user. Whereas traditionally, people would physically have to identify to a service, pay for a ticket in cash, or go into a library to access a book, people can now achieve all of this through…
Decentralized applications (dApps) in Decentralized Finance (DeFi) face a fundamental tension between regulatory compliance requirements like Know Your Customer (KYC) and maintaining decentralization and privacy. Existing permissioned DeFi…
SPEEDEX is a decentralized exchange (DEX) that lets participants securely trade assets without giving any single party undue control over the market. SPEEDEX offers several advantages over prior DEXes. It achieves high throughput -- over…
A distributed and transparent ledger system is considered for various e-commerce products including health medicines, electronics, security appliances, food products and many more to ensure technological and e-commerce sustainability. This…
Smart contracts have been a topic of interest in blockchain research and are a key enabling technology for Connected Autonomous Vehicles (CAVs) in the era of Web 3.0. These contracts enable trustless interactions without the need for…
Decentralized multi-agent systems have shown promise in enabling autonomous collaboration among LLM-based agents. While AgentNet demonstrated the feasibility of fully decentralized coordination through dynamic DAG topologies, several…
Edge computing provides resources for IoT workloads at the network edge. Monitoring systems are vital for efficiently managing resources and application workloads by collecting, storing, and providing relevant information about the state of…
Recording entry and exit records for a country, with properties such as confidentiality, integrity, and auditability, is increasingly important due to rising international mobility and security requirements. Traditional border control…
Privacy protection and nonconvexity are two challenging problems in decentralized optimization and learning involving sensitive data. Despite some recent advances addressing each of the two problems separately, no results have been reported…
In recent years, the advancement in modern technologies has experienced an explosion of huge data sets being captured and recorded in different fields, but also given rise to concerns the security and protection of data storage,…
The security of cryptographic communication protocols that use X.509 certificates depends on the correctness of those certificates. This paper proposes a system that helps to ensure the correct operation of an X.509 certification authority…
Homomorphic encryption is a very useful gradient protection technique used in privacy preserving federated learning. However, existing encrypted federated learning systems need a trusted third party to generate and distribute key pairs to…