IEICE TRANSACTIONS on Fundamentals
L0 Norm Optimization in Scrambled Sparse Representation Domain and Its Application to EtC System
Summary :
In this paper, we propose L0 norm optimization in a scrambled sparse representation domain and its application to an Encryption-then-Compression (EtC) system. We design a random unitary transform that conserves L0 norm isometry. The resulting encryption method provides a practical orthogonal matching pursuit (OMP) algorithm that allows computation in the encrypted domain. We prove that the proposed method theoretically has exactly the same estimation performance as the nonencrypted variant of the OMP algorithm. In addition, we demonstrate the security strength of the proposed secure sparse representation when applied to the EtC system. Even if the dictionary information is leaked, the proposed scheme protects the privacy information of observed signals.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.12 pp.1589-1598
- Publication Date
- 2020/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2020SMP0027
- Type of Manuscript
- Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)
- Category
- Cryptography and Information Security
Authors
Takayuki NAKACHI
Nippon Telegraph and Telephone Corporation
Hitoshi KIYA
Tokyo Metropolitan University
Keyword
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Takayuki NAKACHI, Hitoshi KIYA, "L0 Norm Optimization in Scrambled Sparse Representation Domain and Its Application to EtC System" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 12, pp. 1589-1598, December 2020, doi: 10.1587/transfun.2020SMP0027.
Abstract: In this paper, we propose L0 norm optimization in a scrambled sparse representation domain and its application to an Encryption-then-Compression (EtC) system. We design a random unitary transform that conserves L0 norm isometry. The resulting encryption method provides a practical orthogonal matching pursuit (OMP) algorithm that allows computation in the encrypted domain. We prove that the proposed method theoretically has exactly the same estimation performance as the nonencrypted variant of the OMP algorithm. In addition, we demonstrate the security strength of the proposed secure sparse representation when applied to the EtC system. Even if the dictionary information is leaked, the proposed scheme protects the privacy information of observed signals.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020SMP0027/_p
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@ARTICLE{e103-a_12_1589,
author={Takayuki NAKACHI, Hitoshi KIYA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={L0 Norm Optimization in Scrambled Sparse Representation Domain and Its Application to EtC System},
year={2020},
volume={E103-A},
number={12},
pages={1589-1598},
abstract={In this paper, we propose L0 norm optimization in a scrambled sparse representation domain and its application to an Encryption-then-Compression (EtC) system. We design a random unitary transform that conserves L0 norm isometry. The resulting encryption method provides a practical orthogonal matching pursuit (OMP) algorithm that allows computation in the encrypted domain. We prove that the proposed method theoretically has exactly the same estimation performance as the nonencrypted variant of the OMP algorithm. In addition, we demonstrate the security strength of the proposed secure sparse representation when applied to the EtC system. Even if the dictionary information is leaked, the proposed scheme protects the privacy information of observed signals.},
keywords={},
doi={10.1587/transfun.2020SMP0027},
ISSN={1745-1337},
month={December},}
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TY - JOUR
TI - L0 Norm Optimization in Scrambled Sparse Representation Domain and Its Application to EtC System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1589
EP - 1598
AU - Takayuki NAKACHI
AU - Hitoshi KIYA
PY - 2020
DO - 10.1587/transfun.2020SMP0027
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2020
AB - In this paper, we propose L0 norm optimization in a scrambled sparse representation domain and its application to an Encryption-then-Compression (EtC) system. We design a random unitary transform that conserves L0 norm isometry. The resulting encryption method provides a practical orthogonal matching pursuit (OMP) algorithm that allows computation in the encrypted domain. We prove that the proposed method theoretically has exactly the same estimation performance as the nonencrypted variant of the OMP algorithm. In addition, we demonstrate the security strength of the proposed secure sparse representation when applied to the EtC system. Even if the dictionary information is leaked, the proposed scheme protects the privacy information of observed signals.
ER -
English
