Linear Depth Integer-Wise Homomorphic Division

Part 3: CryptographyInternational audienceWe propose a secure integer-wise homomorphic division algorithm on fully homomorphic encryption schemes (FHE). For integer-wise algorithms, we encrypt plaintexts as integers without encoding them into bit values, while in bit-wise algorithms, plaintexts are encoded into binary and bit values are encrypted one by one. All the publicly available division algorithms are constructed in bit-wise style, and to the best of our knowledge there are no known integer-wise algorithm for secure division. We derive some empirical results on the FHE library HElib and show that our algorithm is 2.45x faster than the fastest bit-wise algorithm. We also show that the multiplicative depth of our algorithm is O(l), where l is the integer bit length, while that of existing division algorithms is $$O(l^2)$$. Furthermore, we generalise our secure division algorithm and propose a method for secure calculation of a general 2-variable function. The order of multiplicative depth of the algorithm, which is a main factor of the complexity of a FHE algorithm, is exactly the same as our secure division algorithm

A roadmap to fully homomorphic elections: Stronger security, better verifiability

After the trials of remote internet voting for local elections in 2011 and parliamentary elections in 2013, a number of local referendums has renewed interest in internet voting in Norway. The voting scheme used in Norway is not quantum-safe and it has limited voter verifiability. In this case study, we consider how we can use fully homomorphic encryption to construct a quantum-safe voting scheme with better voter verifiability. While fully homomorphic cryptosystems are not efficient enough for the the system we sketch to be implemented and run today, we expect future improvements in fully homomorphic encryption which may eventually make these techniques practical

Accelerating integer-based fully homomorphic encryption using Comba multiplication

n/

cuHE: A Homomorphic Encryption Accelerator Library

We introduce a CUDA GPU library to accelerate evaluations with homomorphic schemes defined over polynomial rings enabled with a number of optimizations including algebraic techniques for efficient evaluation, memory minimization techniques, memory and thread scheduling and low level CUDA hand-tuned assembly optimizations to take full advantage of the mass parallelism and high memory bandwidth GPUs offer. The arithmetic functions constructed to handle very large polynomial operands using number-theoretic transform (NTT) and Chinese remainder theorem (CRT) based methods are then extended to implement the primitives of the leveled homomorphic encryption scheme proposed by Löpez-Alt, Tromer and Vaikuntanathan. To compare the performance of the proposed CUDA library we implemented two applications: the Prince block cipher and homomorphic sorting algorithms on two GPU platforms in single GPU and multiple GPU configurations. We observed a speedup of 25 times and 51 times over the best previous GPU implementation for Prince with single and triple GPUs, respectively. Similarly for homomorphic sorting we obtained 12-41 times speedup depending on the number and size of the sorted elements

Faster Homomorphic Linear Transformations in HElib

HElib is a software library that implements homomorphic encryption (HE), with a focus on effective use of packed ciphertexts. An important operation (which is used in bootstrapping, as well as in other applications) is applying a known linear map to a vector of encrypted data. In this paper, we describe several algorithmic improvements that significantly speed up this operation: in our experiments, our new algorithms were 30-75 times faster than those currently implemented in HElib for typical parameters. Our techniques also reduce the size of the large public evaluation key, often using 33%-50% less space than the previous HElib implementation. We also implemented a new tradeoff that enables a drastic reduction in size, maybe a 25x factor or more for some parameters, paying only a 2-4x factor in runtime (and giving up some parallelization opportunities)

Large FHE Gates from tensored homomorphic accumulator

The main bottleneck of all known Fully Homomorphic Encryption schemes lies in the bootstrapping procedure invented by Gentry (STOC’09). The cost of this procedure can be mitigated either using Homomorphic SIMD techniques, or by performing larger computation per bootstrapping procedure.In this work, we propose new techniques allowing to perform more operations per bootstrapping in FHEW-type schemes (EUROCRYPT’13). While maintaining the quasi-quadratic Õ(n2) complexity of the whole cycle, our new scheme allows to evaluate gates with Ω(log n) input bits, which constitutes a quasi-linear speed-up. Our scheme is also very well adapted to large threshold gates, natively admitting up to Ω(n) inputs. This could be helpful for homomorphic evaluation of neural networks.Our theoretical contribution is backed by a preliminary prototype implementation, which can perform 6-to-6 bit gates in less than 10s on a single core, as well as threshold gates over 63 input bits even faster.<p