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Faster Homomorphic Trace-Type Function Evaluation
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DOI：10.1109/ACCESS.2021.3071264.png)
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摘要
En 中文
Homomorphic encryption enables computations over encrypted data without decryption, and can be used for outsourcing computations to some untrusted source. In homomorphic encryption based on the hardness of ring-learning with errors, offering promising security and functionality, a plaintext is represented by a polynomial. A plaintext is treated as a vector whose homomorphic evaluation enables component-wise addition and multiplication, as well as rotation across the components. We focus on a commonly used and time-consuming subroutine that enables homomorphically summing-up the components of the vector or homomorphically extracting the coefficients of the polynomial, and call it homomorphic trace-type function. We improve the efficiency of the homomorphic trace-type function evaluation. The homomorphic trace-type function evaluation is performed by repeating homomorphic rotation followed by addition (rotations-and-sums). To correctly add up a rotated ciphertext and an unrotated one, a special operation called key-switching should be performed on the rotated one. As key-switching is computationally expensive, the rotations-and-sums is inherently inefficient. We propose a more efficient trace-type function evaluation by using loop-unrolling, which is compatible with other optimization techniques such as hoisting, and can exploit multi-threading. We show that the rotations-and-sums is not the optimal solution in terms of runtime complexity and that a trade-off exists between time and space. Experimental results demonstrate that our proposed method works 1.32-2.12 times faster than the previous method.
Keyword:
Switches
Encryption
Runtime
Complexity theory
Outsourcing
Optimization
Licenses
Homomorphic encryption
secure outsourcing
ring-learning with errors
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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