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Author:

Bai, Yu (Bai, Yu.) | Zhuo, Li (Zhuo, Li.) (Scholars:卓力) | Cheng, Bo (Cheng, Bo.) | Peng, Yuan Fan (Peng, Yuan Fan.)

Indexed by:

CPCI-S

Abstract:

Signal processing in the encrypted domain has become a hot research topic, which enable signal processing tasks in a secure and privacy-preserving manner. Taken the fact that SURF (Speeded Up Robust Feature) has been widely utilized in various applications into account, SURF feature extraction method in the encrypted domain has been proposed in this paper. Because all steps must be implemented in the encrypted domain, Paillier homomorphic encryption method is adopted. Experimental results demonstrate that the number and location of SURF features extracted from the encrypted data are the same as those from the plaintext data. And the error between the descriptors obtained from the plaintext data and the encrypted data is only 0.0002932%. We also provide security analysis and complexity analysis. The proposed method can be used in the encrypted domain based applications, such as secure image processing and image retrieval.

Keyword:

privacy preserving SURF Homomorphic encryption

Author Community:

  • [ 1 ] [Bai, Yu]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 2 ] [Zhuo, Li]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 3 ] [Cheng, Bo]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China
  • [ 4 ] [Peng, Yuan Fan]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

Reprint Author's Address:

  • [Bai, Yu]Beijing Univ Technol, Signal & Informat Proc Lab, Beijing, Peoples R China

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Source :

2014 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME)

ISSN: 1945-7871

Year: 2014

Language: English

Cited Count:

WoS CC Cited Count: 9

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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