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Cartesian coordinated adaptive hiding for payload peaking

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Abstract

Transferring multimedia content without detection has gained traction over time. Employing steganography for hiding secret data, viz. passwords, medical information, and private messages, has become the norm. This work involves hiding confidential information in the images. It aims to increase the payload capacity by adaptively choosing the embedding pixel location, using hamming distance, and increasing the number of bits embedded per pixel using threshold while retaining the image quality. The secret PHI information was embedded into the medical cover image by choosing the pixels, such that the embedding order was random. The randomness in the embedding order was achieved by generating a random sequence using a Combined Logistical Tent map. (CLT map). The random sequence was used as the key to choose all the pixels, but in a random order for embedding. Two different ways can generate the CLT map. One is by generating the Logistical map sequence and Tent map sequence and performing the XOR operation of both sequences. The other way is to generate the CLT map sequence through governing equations. The algorithm is designed to perform embedding for images of various modalities, viz. effectively., Grayscale, RGB and DICOM. The algorithm was tested for over 100 images across databases. The test results were satisfactory. The resultant stego image has an acceptable range of Peak Signal to Noise Ratio (PSNR) values above 40 dB and Structural Similarity Index (SSIM) values above 0.9. The stego images with visually imperceptible secret information are good quality and could effectively mitigate steganalysis.

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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Acknowledgments

Authors thank the Department of Science & Technology, New Delhi, for the FIST funding (SR/FST/ET-I/2018/221(C)). The authors thank Intrusion LAB at School of Electrical & Electronics Engineering, SASTRA Deemed University, for providing infrastructural support to carry out this research work.

Funding

DST FIST funding (SR/FST/ET-I/2018/221(C)).

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Authors and Affiliations

  1. School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613 401, India

    V Manikandan & Rengarajan Amirtharajan

  2. CSE, Kalasalingam Academy of Research and Education, Krishnankoil, 626126, India

    V Manikandan

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  1. V Manikandan
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Correspondence to Rengarajan Amirtharajan.

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Manikandan, V., Amirtharajan, R. Cartesian coordinated adaptive hiding for payload peaking. Multimed Tools Appl 83, 17135–17162 (2024). https://doi.org/10.1007/s11042-023-16208-w

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