TY - GEN
T1 - A Steganographic Scheme to Protect Medical Data Using Radiological Images
AU - Anandha, Rr Diajeng Alfisyahrinnisa
AU - De La Croix, Ntivuguruzwa Jean
AU - Ahmad, Tohari
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The progress in data transmission technology has underscored the significance of safeguarding information, particularly with regards to confidentiality. Researchers have therefore dedicated their attention to tackling this concern by introducing various techniques for protecting data confidentiality, including cryptography and steganography. Steganography, a data hiding method that has showcased better results in data security in images, gained significant attention from information security practitioners. Nevertheless, the existing methods show a significant tradeoff between the payload capacity and the stego image's quality, making them not applicable to sensitive domains such as military and medical. In this work, we propose a new steganography method working in medical images based on difference expansions to optimize the alleviation of the imbalance between the payload size and the imperceptibility of the stego image. Our experimental results achieve the best performance of a psnr of 75.1312 dB and the best psnr capacity of 0.6831. Our results showed an improvement in payload capacity from 0.4835 bpp by comparing the existing method to 0.6705 bpp with the same cover image labeled 'Leg'.
AB - The progress in data transmission technology has underscored the significance of safeguarding information, particularly with regards to confidentiality. Researchers have therefore dedicated their attention to tackling this concern by introducing various techniques for protecting data confidentiality, including cryptography and steganography. Steganography, a data hiding method that has showcased better results in data security in images, gained significant attention from information security practitioners. Nevertheless, the existing methods show a significant tradeoff between the payload capacity and the stego image's quality, making them not applicable to sensitive domains such as military and medical. In this work, we propose a new steganography method working in medical images based on difference expansions to optimize the alleviation of the imbalance between the payload size and the imperceptibility of the stego image. Our experimental results achieve the best performance of a psnr of 75.1312 dB and the best psnr capacity of 0.6831. Our results showed an improvement in payload capacity from 0.4835 bpp by comparing the existing method to 0.6705 bpp with the same cover image labeled 'Leg'.
KW - Network infrastructure
KW - information security
KW - national security
KW - radiological images
KW - spatial domain
UR - http://www.scopus.com/inward/record.url?scp=85184989523&partnerID=8YFLogxK
U2 - 10.1109/CICN59264.2023.10402248
DO - 10.1109/CICN59264.2023.10402248
M3 - Conference contribution
AN - SCOPUS:85184989523
T3 - Proceedings - 2023 15th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2023
SP - 369
EP - 374
BT - Proceedings - 2023 15th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2023
Y2 - 22 December 2023 through 23 December 2023
ER -