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MEVSS: Modulo Encryption Based Visual Secret Sharing Scheme for Securing Visual Content

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Key Digital Trends in Artificial Intelligence and Robotics (ICDLAIR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 670))

Abstract

In recent years, there has been a rapid development in the digital world of image communication over unsecured networks. Many domains, including military, medical, government, and education, require transmitting sensitive data through images. Hence, it raises the primary concern of its secrecy with the advancement of technologies. Traditional methods such as Advanced Encryption Standard (AES) and Data Encryption Standard (DES) have been widely used for image security. However, key management is the main concern in protecting image data. This work uses Visual Secret Sharing Scheme (VSS) or Visual Cryptography (VC) to handle the above mentioned issue. Modulo encryption-based VSS scheme (MEVSS) is proposed to encrypt the secret image shared among n number of users. The secret image is recovered loss-less by XORing n shares followed by modulo decryption. Experimental results show that the proposed technique outperforms the exiting techniques Binary tree-based Secret Sharing Scheme and RSA-based VSS in Unified average changing intensity (UACI) and Number of Pixel Change Rate (NPCR), While, the proposed model outperforms the existing techniques in term of Pixel to Signal Noise Ratio (PSNR). Moreover, it is faster than traditional techniques as it works directly on color image without converting it into another form like binary or grayscale.

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Acknowledgment

The authors would like to thank to the DST GoI for sponsoring this work under DST/ICPS/General/2018.

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Correspondence to Parul Saini .

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Saini, P., Kumar, K., Kashid, S., Negi, A. (2023). MEVSS: Modulo Encryption Based Visual Secret Sharing Scheme for Securing Visual Content. In: Troiano, L., Vaccaro, A., Kesswani, N., Díaz Rodriguez, I., Brigui, I., Pastor-Escuredo, D. (eds) Key Digital Trends in Artificial Intelligence and Robotics. ICDLAIR 2022. Lecture Notes in Networks and Systems, vol 670. Springer, Cham. https://doi.org/10.1007/978-3-031-30396-8_3

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