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Please use this identifier to cite or link to this item: http://142.54.178.187:9060/xmlui/handle/123456789/1053
Title: Chaos Based Enhanced RC5 Algorithm for Security and Integrity of Clinical Images in Remote Health Monitoring
Authors: Shahzadi, Romana
Anwar, Syed Muhammad
Qamar, Farhan
Ali, Mudassar
Rodrigues, Joel J. P. C
Keywords: Medical and Health Sciences
Biomedical imaging
Body area networks
Medical image processing
Clinical Images
Medical image processing
Issue Date: 15-Apr-2019
Publisher: IEEE Access
Abstract: The demand for remote health monitoring will significantly increase in the near future due to a decrease in the doctor/patient ratio as the world population grows. In remote health monitoring, one of the major goals is to send patient's data to clinical experts at geographically distant locations. In this scenario, the importance of implementing security on patients' clinical information increases, so that this could not be either changed or read by an unauthorized person. Rivest Cipher (RC5) algorithm is a secure and simple encryption algorithm. Due to its simplicity, fast encryption, and low memory requirements, it is considered as a suitable block cipher for resource constraint environments, such as body area networks (BAN), although it can be broken by various attacks due to poor diffusion. In this paper, we propose a chaotic-based key scheduling algorithm for the RC5 in which round keys are generated based on 2-D chaotic maps and used as a symmetric key during the encryption and decryption process. Cipher feedback mode is adapted to further increase the diffusion property of the cipher. This chaos-based key is very difficult to trace, and the cipher is extremely hard to break. A strict security analysis of the proposed cipher is performed against several attacks. The experimental results have shown that the impact of this approach is significantly better than the conventional security mechanisms in case of BAN when applied to critical clinical images.
URI: http://142.54.178.187:9060/xmlui/handle/123456789/1053
ISSN: 2169-3536
Appears in Collections:Journals

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