Journal Articles
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Item Randomised visual secret sharing scheme for grey-scale and colour images(Institution of Engineering and Technology journals@theiet.org, 2018) Mhala, N.C.; Jamal, R.; Pais, A.R.Randomised visual secret sharing is an encryption technique that utilises block-based progressive visual secret sharing and discrete cosine transform (DCT) based reversible data embedding technique to recover a secret image. The recovery method is based on progressive visual secret sharing, which recovers the secret image block by block. The existing block based schemes achieve the highest contrast level of 50% for noise-like and meaningful shares. The proposed scheme achieves a contrast level of 70-90% for noise-like and 70-80% for meaningful shares. The enhancement of contrast is achieved by embedding additional information in the shares using DCT-based reversible data embedding technique. Experimental results showed that the proposed scheme restores the secret image with better visual quality in terms of human visual system based parameters. © The Institution of Engineering and Technology 2017.Item Contrast enhancement of Progressive Visual Secret Sharing (PVSS) scheme for gray-scale and color images using super-resolution(Elsevier B.V., 2019) Mhala, N.C.; Pais, A.R.Traditional Visual Secret Sharing (VSS) scheme encrypts the secret image into multiple shares. It recovers the secret image based on the “all or nothing” methodology (i.e. all shares must be stacked together to recover the secret image else nothing will be revealed). The modern VSS schemes differ from traditional VSS by progressively recovering the secret image by stacking number of shares. These are also referred as Progressive VSS (PVSS). PVSS schemes generate two types of shares namely 1) meaningful (are the shares which have a meaningful image embedded as the cover image on top of the shares) and 2) noise-like (shares have a random noise-like appearance). In the previous work, we have proposed PVSS based Randomized VSS (RVSS) scheme to recover the secret image by hiding random data into the shares. RVSS achieves the maximum contrast of 70–80% and 70–90% for meaningful and noise-like shares respectively. In this paper, we propose a novel PVSS based super-resolution technique to improve the contrast of RVSS scheme. The experimental results showed that the proposed scheme achieves the contrast of 70–80% for meaningful shares and 99% for noise-like shares. Also, proposed scheme recovers the secret image free from blocking artifacts, for noise-like shares. © 2019 Elsevier B.V.Item Verifiable XOR-based visual secret sharing scheme for hyperspectral images(SPIE, 2021) Srujana, O.S.; Mhala, N.C.; Pais, A.R.Hyperspectral images (HSIs) are the spectral images that provide spatial and spectral information. Unlike multispectral images, these images consist of 100 to 200 bands, which provide a large amount of data to identify minute details of the scene with the help of the spectral signatures. This information is valuable and should be secured while transmitting the HSI over the network. Visual cryptography is a well-known cryptographic method for securing images. It helps in securely transmitting images among n users. It converts visual data into unreadable shares that are transmitted and, stacking these shares together will reveal the image. Many visual secret sharing (VSS) schemes have been proposed in the past decade, which made it easier to hide the visual information from unauthorized users. We have proposed a verifiable XOR-based VSS method for the secure transmission of HSIs. We have introduced a preprocessing step for the image with a band selection technique, which reduces the size of the image and eliminates redundancy. It also includes the detection of the tampered shares. Embedding a verifiable bit in each pixel is performed to test the integrity of the shares. We have assessed the visual quality of the recovered image using quantitative measuring parameters. We also compared them with existing VSS methods. The proposed method recovers the HSI with a self-similarity index of 95% to 99%. The proposed method's experimental results show that the HSI is restored with better visual quality. © 2021 Society of Photo-Optical Instrumentation Engineers (SPIE).Item A novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution(Springer, 2021) Muhammed, A.; Mhala, N.C.; Pais, A.R.Fingerprint is the most recommended and extensively practicing biometric trait for personal authentication. Most of the fingerprint authentication systems trust minutiae as the characteristic for authentication. These characteristics are preserved as fingerprint templates in the database. However, it is observed that the databases are not secure and can be negotiated. Recent studies reveal that, if a person’s minutiae points are dripped, fingerprint can be restored from these points. Similarly, if the fingerprint records are lost, it is a permanent damage. There is no mechanism to replace the fingerprint as it is part of the human body. Hence there is a necessity to secure the fingerprint template in the database. In this paper, we introduce a novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution. During enrollment, a secret fingerprint image is encrypted into n shares. Each share is stored in a distinct database. During authentication, the shares are collected from various databases. The original secret fingerprint image is restored using a multiple image super-resolution procedure. The experimental results show that the reconstructed fingerprints are similar to the original fingerprints. The proposed method is robust, secure, and efficient in terms of fingerprint template protection and authentication. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.Item A secure visual secret sharing (VSS) scheme with CNN-based image enhancement for underwater images(Springer Science and Business Media Deutschland GmbH, 2021) Mhala, N.C.; Pais, A.R.Nowadays, underwater images are being used to identify various important resources like objects, minerals, and valuable metals. Due to the wide availability of the Internet, we can transmit underwater images over a network. As underwater images contain important information, there is a need to transmit them securely over a network. Visual secret sharing (VSS) scheme is a cryptographic technique, which is used to transmit visual information over insecure networks. Recently proposed randomized VSS (RVSS) scheme recovers secret image (SI) with a self-similarity index (SSIM) of 60–80%. But, RVSS is suitable for general images, whereas underwater images are more complex than general images. In this paper, we propose a VSS scheme using super-resolution for sharing underwater images. Additionally, we have removed blocking artifacts from the reconstructed SI using convolution neural network (CNN)-based architecture. The proposed CNN-based architecture uses a residue image as a cue to improve the visual quality of the SI. The experimental results show that the proposed VSS scheme can reconstruct SI with almost 86–99% SSIM. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Item GPGPU-based randomized visual secret sharing (GRVSS) for grayscale and colour images(Taylor and Francis Ltd., 2022) Holla, R.; Mhala, N.C.; Pais, A.R.Visual Secret Sharing (VSS) is a technique used for sharing secret images between users. The existing VSS schemes reconstruct the original secret image as a halftone image with only a 50% contrast. The Randomized Visual Secret Sharing (RVSS) scheme overcomes the disadvantages of existing VSS schemes. Although RVSS extracts the secret image with better contrast, it is computationally expensive. This paper proposes a General Purpose Graphics Processing Unit (GPGPU)-based Randomized Visual Secret Sharing (GRVSS) technique that leverages data parallelism in the RVSS pipeline. The performance of the GRVSS is compared with the RVSS in a generic and PARAM Shavak supercomputer architecture. The GRVSS outperforms the RVSS in both architectures. © 2020 Informa UK Limited, trading as Taylor & Francis Group.