Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DID-eFed: Facilitating Federated Learning as a Service with
  Decentralized Identities   We have entered the era of big data, and it is considered to be the "fuel"
for the flourishing of artificial intelligence applications. The enactment of
the EU General Data Protection Regulation (GDPR) raises concerns about
individuals' privacy in big data. Federated learning (FL) emerges as a
functional solution that can help build high-performance models shared among
multiple parties while still complying with user privacy and data
confidentiality requirements. Although FL has been intensively studied and used
in real applications, there is still limited research related to its prospects
and applications as a FLaaS (Federated Learning as a Service) to interested 3rd
parties. In this paper, we present a FLaaS system: DID-eFed, where FL is
facilitated by decentralized identities (DID) and a smart contract. DID enables
a more flexible and credible decentralized access management in our system,
while the smart contract offers a frictionless and less error-prone process. We
describe particularly the scenario where our DID-eFed enables the FLaaS among
hospitals and research institutions.

0
The categories of this paper are: hep-ph
32
The categories of this paper are: atom-ph
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
19
The categories of this paper are: eess
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an