Confidential Truth Finding with Multi-Party Computation (Extended Version). (arXiv:2305.14727v1 [cs.CR])

Federated knowledge discovery and data mining are challenged to assess the
trustworthiness of data originating from autonomous sources while protecting
confidentiality and privacy. Truth-finding algorithms help corroborate data
from disagreeing sources. For each query it receives, a truth-finding algorithm
predicts a truth value of the answer, possibly updating the trustworthiness
factor of each source. Few works, however, address the issues of
confidentiality and privacy. We devise and present a secure
secret-sharing-based multi-party computation protocol for pseudo-equality tests
that are used …

algorithm algorithms autonomous computation confidential confidentiality data data mining discovery knowledge mining party privacy protecting query truth value version