相关论文: Analysis of Models for Decentralized and Collabora…
This paper presents a novel collaborative generative modeling (CGM) framework that incentivizes collaboration among self-interested parties to contribute data to a pool for training a generative model (e.g., GAN), from which synthetic data…
Decentralized applications rely on non-centralized technical infrastructures and coordination principles. Without trusted third parties, their execution is not controlled by entities exercising centralized coordination but is instead…
The recent rapid development of artificial intelligence (AI, mainly driven by machine learning research, especially deep learning) has achieved phenomenal success in various applications. However, to further apply AI technologies in…
Large scale power systems are comprised of regional utilities with assets that stream sensor readings in real time. In order to detect cyberattacks, the globally acquired, real time sensor data needs to be analyzed in a centralized fashion.…
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement based on blockchain mining. Yet the…
Blockchain technology, beyond cryptocurrencies, is called to be the new information exchange ecosystem due to its unique properties, such as immutability and transparency. The main objective of this work is to introduce the design of a…
Traditional smart grid energy auctions cannot directly be integrated in blockchain due to its decentralized nature. Therefore, research works are being carried out to propose efficient decentralized auctions for energy trading. Since,…
Bitcoin is the first implementation of what has become known as a 'public permissionless' blockchain. Guaranteeing security and protocol conformity through its elegant combination of cryptographic assurances and game theoretic economic…
Blockchain and blockchain-inspired decentralized applications are on the rise thanks to their unique characteristics such as their decentralized nature, anonymity, and tamper-proof nature; however, blockchain transactions tend to experience…
A decentralized federated learning architecture is proposed to apply to the Businesses-to-Businesses scenarios by introducing the consortium blockchain in this paper. We introduce a model verification mechanism to ensure the quality of…
Blockchain introduces decentralized trust in peer-to-peer networks, advancing security and democratizing systems. Yet, a unified definition for decentralization remains elusive. Our Systematization of Knowledge (SoK) seeks to bridge this…
The surge in the spread of misleading information, lies, propaganda, and false facts, frequently known as fake news, raised questions concerning social media's influence in today's fast-moving democratic society. The widespread and rapid…
Consensus protocols inherently rely on the notion of leader election, in which one or a subset of participants are temporarily elected to authorize and announce the network's latest state. While leader election is a well studied problem,…
Centralization enhances the efficiency of Artificial Intelligence (AI) but also introduces critical challenges, including single points of failure, inherent biases, data privacy risks, and scalability limitations. To address these issues,…
Motivated by governance models adopted in blockchain applications, we study the problem of selecting appropriate system updates in a decentralised way. Contrary to most existing voting approaches, we use the input of a set of motivated…
As Artificial Intelligence (AI) integrates into diverse areas, particularly in content generation, ensuring rightful ownership and ethical use becomes paramount, AI service providers are expected to prioritize responsibly sourcing training…
The aim of this work is to study the use of decentralization and smart contracts on blockchain networks. We investigate the implementation and use of smart contracts on the platforms Bitcoin, Ethereum and Hyperledger Fabric. Additionally,…
The cost of conducting multi-site clinical trials has significantly increased over time, with site monitoring, data management, and amendments being key drivers. Clinical trial data management approaches typically rely on a central…
Federated Learning is an emerging distributed collaborative learning paradigm adopted by many of today's applications, e.g., keyboard prediction and object recognition. Its core principle is to learn from large amount of users data while…
Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Current incentive structures and regulatory delays may hinder…