- Title
- Chaos-based robust method of zero-watermarking for medical signals
- Creator
- Ali, Zulfiqar; Imran, Muhammad; Alsulaiman, Mansour; Shoaib, Muhammad; Ullah, Sana
- Date
- 2018
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/181805
- Identifier
- vital:15997
- Identifier
-
https://doi.org/10.1016/j.future.2018.05.058
- Identifier
- ISBN:0167-739X (ISSN)
- Abstract
- The growing use of wireless health data transmission via Internet of Things is significantly beneficial to the healthcare industry for optimal usage of health-related facilities. However, at the same time, the use raises concern of privacy protection. Health-related data are private and should be suitably protected. Several pathologies, such as vocal fold disorders, indicate high risks of prevalence in individuals with voice-related occupations, such as teachers, singers, and lawyers. Approximately, one-third of the world population suffers from the voice-related problems during the life span and unauthorized access to their data can create unavoidable circumstances in their personal and professional lives. In this study, a zero-watermarking method is proposed and implemented to protect the identity of patients who suffer from vocal fold disorders. In the proposed method, an image for a patient's identity is generated and inserted into secret keys instead of a host medical signal. Consequently, imperceptibility is naturally achieved. The locations for the insertion of the watermark are determined by a computation of local binary patterns from the time–frequency spectrum. The spectrum is calculated for low frequencies such that it may not be affected by noise attacks. The experimental results suggest that the proposed method has good performance and robustness against noise, and it is reliable in the recovery of an individual's identity. © 2018 Elsevier B.V.
- Publisher
- Elsevier B.V.
- Relation
- Future Generation Computer Systems Vol. 88, no. (2018), p. 400-412
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2018 Elsevier B.V.
- Rights
- Open Access
- Subject
- 4604 Cybersecurity and Privacy; 4606 Distributed Computing and Systems Software; Chaotic system; Healthcare; Logistic map; Privacy protection; Vocal fold disorders
- Full Text
- Reviewed
- Funder
- The authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for funding this research through Research Group Project No.(RG#1439-036).
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