V
V. Thanikaiselvan
Researcher at VIT University
Publications - 52
Citations - 285
V. Thanikaiselvan is an academic researcher from VIT University. The author has contributed to research in topics: Encryption & Steganography. The author has an hindex of 7, co-authored 38 publications receiving 176 citations.
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Proceedings ArticleDOI
Wave (let) decide choosy pixel embedding for stego
V. Thanikaiselvan,Pachiyappan Arulmozhivarman,Rengarajan Amirtharajan,John Bosco Balaguru Rayappan +3 more
TL;DR: This paper proposes a modern steganographic technique with Integer Wavelet transform (IWT) and double key to achieve high hiding capacity, high security and good visual quality.
Journal ArticleDOI
Colour image encryption based on customized neural network and DNA encoding
Sakshi Patel,V. Thanikaiselvan,Danilo Pelusi,B. Nagaraj,R. Arunkumar,Rengarajan Amirtharajan +5 more
TL;DR: The highly chaotic nature of hybrid chaos maps and neural network is combined to build a random number generator for cryptographic applications and a custom neural network with a user-defined layer transfer function is built to increase the generator’s randomness.
Proceedings ArticleDOI
High security image steganography using IWT and graph theory
TL;DR: A Color image steganography in transform domain is proposed, which shows good imperceptibility, High capacity and Robustness and Random selection of wavelet coefficients is based on the graph theory.
Journal ArticleDOI
A Graph Theory Practice on Transformed Image: A Random Image Steganography
TL;DR: The proposed method gives high imperceptibility through high PSNR value and high embedding capacity in the cover image due to adaptive embedding scheme and high robustness against blind attack through graph theoretic random selection of coefficients.
Journal ArticleDOI
Comparative analysis of integer wavelet transforms in reversible data hiding using threshold based histogram modification
Ahmad Shaik,V. Thanikaiselvan +1 more
TL;DR: This work compares the performance of all integer wavelet transforms and other state of the art techniques with respect to their embedding capacity and image visual quality and leads to a better understanding of the relationship between the embeddingcapacity and the stego image quality whenever different wavelets were utilized.