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Kim, Miran
Applied Cryptography Lab
Research Interests
  • My research mainly focuses on secure computation, which aims to develop advanced cryptographic primitives to protect the sensitive data of individuals. I have been actively working on the development of privacy-preserving protocols in a wide range of applications such as cyber-physical systems, data query processing, genomic computation, and machine learning.

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Homomorphic Computation of Local Alignment

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Title
Homomorphic Computation of Local Alignment
Author
Bataa, MagsarjavSong, SiwooPark, KunsooKim, MiranCheon, Jung HeeKim, Sun
Issue Date
2020-12-16
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE International Conference on Bioinformatics and Biomedicine, pp.2167 - 2174
Abstract
In this paper we present a homomorphic computation algorithm that finds an optimal local alignment of a pair of encrypted sequences, based on the Smith-Waterman recurrence. Our algorithm also includes an efficient method of finding the location of an optimal local alignment, in order to avoid costly conditional branching in the backtracking. To reduce computation time, we use two level parallel computations: one for filling the entries of the dynamic programming recurrence, and the other for implementing the circuits. To the best of our knowledge, this is the first attempt to compute an optimal local alignment of homomorphically encrypted sequences. With the efficient location retrieval, parallel computations, and a proper HE scheme, our implementation shows good performances in the experiment so as to be useful in practice. © 2020 IEEE.
URI
https://scholarworks.unist.ac.kr/handle/201301/50117
DOI
10.1109/BIBM49941.2020.9313199
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