Accelerating Fully Homomorphic Encryption in Hardware

By Yarkin Doröz, Erdinç Öztürk, Berk Sunar. 2015

109 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. Kim Laine
2. Wei Dai
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, background): “ation. A line of research focuses on designing very large integer multipliers (768K-bit to 1.18M-bit multiplications) – based on FPGAs or ASICs – that can be used to accelerate homomorphic operations [13, 28, 29, 61, 62]. In [14], a large-integer multiplier and a Barrett modular reduction are propos”
• Accelerating Somewhat Homomorphic Evaluation using FPGAs (2015, background): “[18], which also implements the Gentry-Halevi FHE.”
• Polynomial multipliers for fully homomorphic encryption on FPGA (2015, methodology): “Again, they use a similar approach for operand loading and, as [16], they implement a FFT-based multiplication.”
• Accelerating LTV Based Homomorphic Encryption in Reconfigurable Hardware (2015, background): “Therefore, a good number of works focused on developing FFT/NTT based large integer multipliers [17,18,35,35].”
• A Custom Accelerator for Homomorphic Encryption Applications (2017, background): “[10], which also implements the Gentry-Halevi FHE.”
• High-Speed Fully Homomorphic Encryption Over the Integers (2014, methodology): “Further to this, an ASIC design of the full GH FHE scheme, without key generation, is proposed in [20].”
• HEAX: High-Performance Architecture for Computation on Homomorphically Encrypted Data in the Cloud (2019, background): “A line of research focuses on designing very large integer multipliers – based on FPGAs or ASICs – that can be used to accelerate homomorphic operations [74, 75, 28, 29, 13].”
• 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.”
• F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption (2021, background): “Prior FHE accelerators [20, 22, 27, 65, 66, 71] target individual FHE operations, and miss important ones that they leave to software.”