@inproceedings{f12f689cd8524827a8f06f008481e4e1,
title = "Improved Logistic-Sine Chaotic Map based S-box and Bit-Plane Scrambling Encryption Schemes Performance on Compressed ECG Data",
abstract = "Telehealth technology, especially Telehealth Electrocardiograph (ECG), is currently developing. Along with the development of Telehealth ECG, data transmission security on the system becomes very important due to the high level of sensitivity and confidentiality of health data. ECG data encryption approach based on digital image encryption schemes is chosen because it produces a high degree of difference with initial data and low computational complexity levels. This is based on the assumption that parts of ECG data signals have a high degree of correlation. We proposed two digital image encryption schemes, such as the bit-plane scrambling and Double Chaotic S-box, on ECG data. The Double Chaotic S-box encryption scheme proves to be superior to the bit-plane scrambling encryption scheme in the aspect of execution time and keyspace. Having a pretty large keyspace of 2268 and compared to the baseline encryption method, namely SIT, which needs 343.93s to encrypt, the Double Chaotic S-box method needs the only 1.45s to encrypt. This result shows that the proposed method enormous potential as a fast ECG encryption scheme with a high-security level. ",
keywords = "Bit-plane, chaos, cryptography, Digital Image, ECG, S-box",
author = "Muhammad Fauzi and Grafika Jati and Rachmadi, {Muhammad Febrian} and Wisnu Jatmiko",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 5th International Workshop on Big Data and Information Security, IWBIS 2020 ; Conference date: 17-10-2020 Through 18-10-2020",
year = "2020",
month = oct,
day = "17",
doi = "10.1109/IWBIS50925.2020.9255507",
language = "English",
series = "2020 International Workshop on Big Data and Information Security, IWBIS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "97--102",
booktitle = "2020 International Workshop on Big Data and Information Security, IWBIS 2020",
address = "United States",
}