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A novel four image encryption approach in sparse domain based on biometric keys

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Abstract

In this paper, a novel four-image encryption method using biometric keys based on a compressive phase retrieval algorithm is proposed. In the encryption procedure, each input image to be encrypted is initially encoded in sparse data by using a phase retrieval algorithm, which is further combined with a distinct biometric phase mask key. This approach increases the non-linearity of the encryption process and also offers an additional layer of system security against unauthorized attacks. In the system, multiple phase keys from a single biometric hologram by changing the reconstruction parameters during the numerical reconstruction process are generated. The digital nature of the key generation process makes it available at encryption and decryption stages. In addition, the advantage associated with the proposed scheme is related to achieve in reducing space for data storage and transmission over a communication channel. The algorithms to implement the proposed scheme are discussed, and the results of the numerical simulations have presented the effectiveness of the proposed four-image encryption scheme that exhibits better performance in comparison to the reported methods.

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Authors and Affiliations

  1. School of Information and Communication Technology, Gautam Buddha University, Greater Noida, 201312, India

    Gaurav Verma

  2. Department of Electronics and Communication Engineering, B K Birla Institute of Engineering and Technology, Pilani, Rajasthan, 333031, India

    Gaurav Verma

  3. Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronics Engineering, Shenzhen University, Shenzhen, 518060, China

    Wenqi He & Xiang Peng

Authors
  1. Gaurav Verma
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  2. Wenqi He
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  3. Xiang Peng
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Correspondence to Gaurav Verma.

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Verma, G., He, W. & Peng, X. A novel four image encryption approach in sparse domain based on biometric keys. Multimed Tools Appl 82, 22889–22904 (2023). https://doi.org/10.1007/s11042-023-14801-7

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  • DOI: https://doi.org/10.1007/s11042-023-14801-7

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