We consider a situation where multiple parties, owning data that have to be frequently
updated, agree to share weighted sums of these data with some aggregator, but where they …

Federated learning has emerged as a promising paradigm by collaboratively training a
global model through sharing local gradients without exposing raw data. However, the …

Multi-client functional encryption (MCFE) is a more flexible variant of functional encryption
whose functional decryption involves multiple ciphertexts from different parties. Each party …

Mobile crowdsensing (MCS) is becoming an increasingly important topic due to rapid
proliferation of mobile apps where participants' anonymity is a pivotal requirement with direct …

Aggregating data from multiple sources is often required in multiple applications. In this
paper, we introduce DEVA DEVA, a protocol that allows a distributed set of servers to …

Edge computing is a highly virtualized paradigm that can services the Internet of Things (IoT)
devices more efficiently. It is a non-trivial extension of cloud computing, which can not only …

A private stream aggregation (PSA) scheme is a protocol of n clients and one aggregator. At
every time step, the clients send an encrypted value to the (untrusted) aggregator, who is …

Abstract Private Stream Aggregation (PSA) schemes are efficient protocols for distributed
data analytics. In a PSA scheme, a set of data producers can encrypt data for a central party …

Federated learning (FL) has been widely used for privacy-preserving model updates in
Industry 5.0, facilitated by 6G networks. Despite FL's privacy-preserving advantages, it …

Verifiable aggregator oblivious encryption is a useful notion that not only allows an untrusted
aggregator to compute aggregated data without learning any other information but also …