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Evaluating Homomorphic Operations on a Real-World Processing-In-Memory System. (arXiv:2309.06545v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Computing on encrypted data is a promising approach to reduce data security
and privacy risks, with homomorphic encryption serving as a facilitator in
achieving this goal. In this work, we accelerate homomorphic operations using
the Processing-in- Memory (PIM) paradigm to mitigate the large memory capacity
and frequent data movement requirements. Using a real-world PIM system, we
accelerate the Brakerski-Fan-Vercauteren (BFV) scheme for homomorphic addition
and multiplication. We evaluate the PIM implementations of these homomorphic
operations with statistical workloads (arithmetic mean, …
computing data data security data security and privacy encrypted encrypted data encryption homomorphic encryption large memory operations paradigm pim privacy privacy risks requirements risks security system work world