An Enhance Scheme of Visual Secret Share for Lossless Recovery
Kalyan Das1, Sayantan Samajpati2, Abhirup Das3, Samir Kumar Bandyopadhyay4, Amiya Bhaumik5
1Kalyan Das, Assistant Professor, Department of Information Technology, St. Thomas’ College of Engineering and Technology, Kolkata (West Bengal), India.
2Sayantan Samajpati, Department of Information Technology, St. Thomas’ College of Engineering and Technology, Kolkata (West Bengal), India.
3Abhirup Das, Department of Information Technology, St. Thomas’ College of Engineering and Technology, Kolkata (West Bengal), India.
4Prof. Dr. Samir Kumar Bandyopadhyay, Professor, Lincoln University College, Malaysia. Former Registrar, West Bengal University of Technology, Kolkata (West Bengal), India.
5Prof. Dr. Amiya Bhaumik, President and Founder Lincoln University College Malaysia.
Manuscript received on 15 March 2020 | Revised Manuscript received on 22 March 2020 | Manuscript Published on 30 March 2020 | PP: 50-54 | Volume-9 Issue-3S March 2020 | Retrieval Number: C10150393S20/20©BEIESP | DOI: 10.35940/ijeat.C1015.0393S20
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Algorithms in Visual Cryptography usually uses a sharing scheme where instead of sharing the secret or message directly, it is embedded into multiple shares which are then shared between the intended individuals whereby upon receiving them the decrypting algorithm on the receiving end restores the original secret. A novel cryptographic scheme will not only hide the data, but also will do it in an efficient way which will further ensure that the algorithm is robust to noises and attacks. The proposed algorithm utilizes bitwise operations for efficient hiding of data. Also, it is important that the secret image is losslessly recovered.
Keywords: Key Less Secret Sharing, Lossless Recovery of Secret Image, Run Length Encoding (RLE).
Scope of the Article: Visual Analytics