Related papers: FedChain: An Efficient and Secure Consensus Protoc…
The Metaverse is rapidly evolving, bringing us closer to its imminent reality. However, the widespread adoption of this new automated technology poses significant research challenges in terms of authenticity, integrity, interoperability,…
The emerging Federated Edge Learning (FEL) technique has drawn considerable attention, which not only ensures good machine learning performance but also solves "data island" problems caused by data privacy concerns. However, large-scale FEL…
Federated Learning is a promising machine learning paradigm when multiple parties collaborate to build a high-quality machine learning model. Nonetheless, these parties are only willing to participate when given enough incentives, such as a…
Most cryptocurrencies rely on Proof-of-Work (PoW) "mining" for resistance to Sybil and double-spending attacks, as well as a mechanism for currency issuance. Hashcash PoW has successfully secured the Bitcoin network since its inception,…
Proof of Stake (PoS) blockchains offer promising alternatives to traditional Proof of Work (PoW) systems, providing scalability and energy efficiency. However, blockchains operate in a decentralized manner and the network is composed of…
Federated machine learning (FL) allows to collectively train models on sensitive data as only the clients' models and not their training data need to be shared. However, despite the attention that research on FL has drawn, the concept still…
Chatbots are mainly data-driven and usually based on utterances that might be sensitive. However, training deep learning models on shared data can violate user privacy. Such issues have commonly existed in chatbots since their inception. In…
Blockchain technology has revolutionized the digital landscape, driving innovations across industries through its decentralized and transparent infrastructure. These networks are primarily categorized as public or private, based on user…
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…
A key component of security in decentralized blockchains is proof of opportunity cost among block producers. In the case of proof-of-work (PoW), currently used by the most prominent systems, the cost is due to spent computation. In this…
Federated learning, as a promising machine learning approach, has emerged to leverage a distributed personalized dataset from a number of nodes, e.g., mobile devices, to improve performance while simultaneously providing privacy…
Nowadays, federated recommendation technology is rapidly evolving to help multiple organisations share data and train models while meeting user privacy, data security and government regulatory requirements. However, federated recommendation…
The blockchain has found numerous applications in many areas with the expectation to significantly enhance their security. The Internet of things (IoT) constitutes a prominent application domain of blockchain, with a number of architectures…
Federated learning can solve the privacy protection problem in distributed data mining and machine learning, and how to protect the ownership, use and income rights of all parties involved in federated learning is an important issue. This…
Many studies have been done to improve the performance of centrally controlled business processes and enhance the integration between different parties of these collaborations. However, the most serious issues of collaborative business…
In this paper we describe a prototype of a blockchain-in-a-box system which allows users to easily bootstrap the whole Ethereum Proof-of-Work (PoW) network running on multiple Raspberry Pi nodes - an inexpensive modular computers. Users are…
Deep learning has achieved great success in many applications. However, its deployment in practice has been hurdled by two issues: the privacy of data that has to be aggregated centrally for model training and high communication overhead…
This paper presents a fully coupled blockchain-assisted federated learning architecture that effectively eliminates single points of failure by decentralizing both the training and aggregation tasks across all participants. Our proposed…
Blockchain technology emerged with the advent of Bitcoin and rapidly developed over the past few decades, becoming widely accepted and known by the public. However, in the past decades, the massive adoption of blockchain technology has yet…
While the large-scale Internet of Things (IoT) makes many new applications feasible, like Smart Cities, IoT also brings new concerns on data reliability, security, and privacy. The rapid evolution in blockchain technologies, which relied on…