TY - GEN
T1 - Accelerating CKKS Homomorphic Encryption with Data Compression on GPUs
AU - Phan, Quoc Bao
AU - Nguyen, Linh
AU - Nguyen, Tuy Tan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Homomorphic encryption (HE) algorithms, particularly the Cheon-Kim-Kim-Song (CKKS) scheme, offer significant potential for secure computation on encrypted data, making them valuable for privacy-preserving machine learning. However, high latency in large integer operations in the CKKS algorithm hinders the processing of large datasets and complex computations. This paper proposes a novel strategy that combines lossless data compression techniques with the parallel processing power of graphics processing units to address these challenges. Our approach demonstrably reduces data size by 90% and achieves significant speedups of up to 100 times compared to conventional approaches. This method ensures data confidentiality while mitigating performance bottlenecks in CKKS-based computations, paving the way for more efficient and scalable HE applications.
AB - Homomorphic encryption (HE) algorithms, particularly the Cheon-Kim-Kim-Song (CKKS) scheme, offer significant potential for secure computation on encrypted data, making them valuable for privacy-preserving machine learning. However, high latency in large integer operations in the CKKS algorithm hinders the processing of large datasets and complex computations. This paper proposes a novel strategy that combines lossless data compression techniques with the parallel processing power of graphics processing units to address these challenges. Our approach demonstrably reduces data size by 90% and achieves significant speedups of up to 100 times compared to conventional approaches. This method ensures data confidentiality while mitigating performance bottlenecks in CKKS-based computations, paving the way for more efficient and scalable HE applications.
KW - CKKS
KW - data compression
KW - graphics processing units
KW - Homomorphic encryption
KW - privacy-preserving
UR - http://www.scopus.com/inward/record.url?scp=85205005578&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85205005578&partnerID=8YFLogxK
U2 - 10.1109/MWSCAS60917.2024.10658747
DO - 10.1109/MWSCAS60917.2024.10658747
M3 - Conference contribution
AN - SCOPUS:85205005578
T3 - Midwest Symposium on Circuits and Systems
SP - 1145
EP - 1149
BT - 2024 IEEE 67th International Midwest Symposium on Circuits and Systems, MWSCAS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 67th IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2024
Y2 - 11 August 2024 through 14 August 2024
ER -