FPGA implementation of a large-number multiplier for fully homomorphic encryption

By Wei Wang, Xinming Huang. 2013

50 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Wei Dai
2. Kim Laine
3. M. Sadegh Riazi
4. Blake Pelton
5. Berk Sunar
6. Yarkin Doröz
7. Erkay Savas
8. Erdinç Öztürk

In Information Systems

1. Wei Dai
2. Kim Laine
3. M. Sadegh Riazi
4. Blake Pelton
5. Yarkin Doröz
6. Berk Sunar
7. Erdinç Öztürk
8. Erkay Savas

Citations in the corpus

• HEAX: An Architecture for Computing on Encrypted Data (2019, methodology): “The security parameters for which we have instantiated HEAX are borrowed from the HE security standards [2] for 128-bit classical security.”
• A Survey on Homomorphic Encryption Schemes (2017, background): “…and reconfigurable environment provided by FPGAs motivates many researchers to speed up the practicality of FHE schemes [Cousins et al. 2012; Wang and Huang 2013; Cao et al. 2013; Moore et al. 2013; Chen et al. 2015; Cao et al. 2014; Moore et al. 2014a; Cousins et al. 2014; Roy et al. 2015;…”
• Accelerating Somewhat Homomorphic Evaluation using FPGAs (2015, methodology): “FPGA NTT transform [37] GH-FHE Stratix V FPGA 0.”
• Modular Hardware Architecture for Somewhat Homomorphic Function Evaluation (2015, methodology): “Wang and Huang [39,40] later showed that this multiplication can be further accelerated by a factor of approximately two together with significant reductions in power consumption by using FPGA and ASIC.”
• Accelerating NTRU based homomorphic encryption using GPUs (2014, methodology): “To tackle the efficiency bottleneck the use of alternative platforms, such as GPUs [16], reconfigurable logic [17]–[21] and custom ASIC [22], [23] has been proposed.”
• Accelerating Homomorphic Evaluation on Reconfigurable Hardware (2015, methodology): “An FPGA implementation of an integer multiplier for the Gentry-Halevi [24] FHE scheme is proposed in [43].”
• HEPCloud: An FPGA-Based Multicore Processor for FV Somewhat Homomorphic Function Evaluation (2018, result): “Hence, it is not surprising that during the recent years several publications [8], [13], [14], [15], [26], [28], [31], [33], [40], [41] have reported results”
• FPGA-Based High-Performance Parallel Architecture for Homomorphic Computing on Encrypted Data (2019, background): “In the literature there are several reported hardware implementation that try to speedup performance of HE schemes [11]–[21].”
• Accelerating integer-based fully homomorphic encryption using Comba multiplication (2014, methodology): “Furthermore, a design for a large-number multiplier for FHE targeting a Stratix-V FPGA technology was presented last year by Wang et al. [15]; this multiplier uses the FFT algorithm and is reported to be twice as fast as the same multiplication implemented on the NVIDA C2050 GPU.”
• High-Speed Fully Homomorphic Encryption Over the Integers (2014, methodology): “An FPGA implementation of a multiplier for the GH FHE scheme was proposed by Wang and Huang [19] and is stated to be about twice as fast as the previously mentioned GPU implementation [13].”
• Accelerating LTV Based Homomorphic Encryption in Reconfigurable Hardware (2015, background): “NTT transform [37] GH-FHE Stratix V FPGA 0.”
• A Custom Accelerator for Homomorphic Encryption Applications (2017, methodology): “present an optimized version of their result [17], which achieves speed-up factors of 174, 7.”