An emerging paradigm for instituting smart city that incorporates information and communication technologies demands an exponential rise in networked infrastructure and advancement of IoT. The physical world has to be monitored in real-time to introduce smart services to the public in the areas of healthcare, entertainment, education, environment, transportation, etc., Conventional healthcare is profoundly transforming into electronic healthcare that anticipates a high degree of security and privacy. Computationally efficient, highly secured algorithms are to be developed to protect electronic health records used in real-time communication for telediagnosis and treatment. This necessitates the proposed scheme named as RIGID (Reversible lIght weiGht hIgh payloaD) for ensuring reversible data mechanism to handle high payload for processing electronic health record in smart city applications by using Pseudo Random Matrices(PRM) and scrambling technique. PRBM has been employed to find the position for permutation and Pseudo Random Number matrix (PRNM) can aid substitution. The proposed RIGID scheme has endorsed a promising result when tested with standard benchmark medical / images and a set of images chosen at random from UCID repository by supporting high payload and reversibility. This scheme is capable of detecting most of the intrusions caused by signal processing and geometric attacks. Experimental investigations disclose the proposed project as an ideal choice for the exchange of EHR in IoT based healthcare system for smart city applications.
Electronic health records Pseudo-random binary matrix Blum-Blum-Shub Semantic security
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This part of this research work is supported by Department of Science and Technology (DST), Science and Engineering Board (SERB), Government of India under the ECR grant (ECR/2017/000679/ES)
This study was funded by Department of Science and Technology (DST), Science and Engineering Board (SERB), Government of India (grant number: ECR/2017/000679/ES).
Compliance with ethical standards
Conflict of interest
Dr. N. Sasikaladevi declares that she has no conflict of interest. Dr. K. Geetha and Dr. A. Revathi declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
Agarwal H, Atrey PK, Raman B (2015) Image watermarking in real oriented wavelet transform domain. Multimed Tools Appl 74(23):10883–10921CrossRefGoogle Scholar
Ahmed IA (2017) Security in the Internet of Things (IoT). In: HCT Information Technology Trends (ITT). IEEE, pp 84–90Google Scholar
Alattar AM (2004) Reversible watermark using the difference expansion of a generalized integer transform. IEEE Trans Image Process 13(8):1147–1156MathSciNetCrossRefGoogle Scholar
Blum MA (1984) An efficient probabilistic public-key encryption scheme which hides all partial information. In: Workshop on the theory and application of cryptographic techniques. Springer, Berlin/Heidelberg, pp 289–299Google Scholar
Islam SR-S (2015) The internet of things for health care: a comprehensive survey. IEEE Access:678–700Google Scholar
Jung K-H, Yoo K-Y (2009) Data hiding method using image interpolation. Compu Stand Interfaces 31(2):465–470CrossRefGoogle Scholar
Jung K-H, Yoo K-Y (2015) Steganographic method based on interpolation and LSB substitution of digital images. Multimed Tools Appl 74(6):2143–2155CrossRefGoogle Scholar
Karajeh H, Khatib T, Rajab L, Maqableh M (2019) A robust digital audio watermarking scheme based on DWT and Schur decomposition. Multimed Tools Appl 78(13):18395–18418CrossRefGoogle Scholar
Kodali RK (2015) An implementation of IoT for healthcare. In: IEEE Recent Advances in In Intelligent Computational Systems (RAICS). IEEE, pp 411–416Google Scholar
Lee C-F, Huang Y-L (2012) An efficient image interpolation increasing payload in reversible data hiding. Expert Syst Appl 39(8):6712–6719CrossRefGoogle Scholar
Luo H et al (2011) Reversible data hiding based on block median preservation. Inf Sci 181(2):308–328CrossRefGoogle Scholar
Muhammad KM (2016) Image steganography using uncorrelated color space and its application for security of visual contents in online social networks. Futur Gener Comput SystGoogle Scholar
Muhammad KJ (2017a) CISSKA-LSB: color image steganography using stego key-directed adaptive LSB substitution method. Multimed Tools Appl 76(6):8597–8626CrossRefGoogle Scholar
Muhammad KJ (2017b) Image steganography for authenticity of visual contents in social networks. Multimed Tools Appl 76(18):18985–19004CrossRefGoogle Scholar
Öztürk I, Kılıç R (2015) A novel method for producing pseudo random numbers from differential equation-based chaotic systems. Nonlinear Dyn 80(3):1147–1157MathSciNetCrossRefGoogle Scholar
Parah SA (2017a) Hiding clinical information in medical images: a new high capacity and reversible data hiding technique. J Biomed Inform 66:214–230CrossRefGoogle Scholar
Parah SA (2017b) Hiding in encrypted images: a three tier security data hiding technique. Multidim Syst Sign Process 28(2):549–572CrossRefGoogle Scholar
Parah SA (2017c) Information hiding in medical images: a robust medical image watermarking system for E-healthcare. Multimed Tools Appl 76(8):10599–10633CrossRefGoogle Scholar
Parah SA et al (2018) Electronic health record hiding in images for smart city applications: a computationally efficient and reversible information hiding technique for secure communication. Futur Gener Comput SystGoogle Scholar
Rangel-Espinoza K, Fragoso-Navarro E, Cruz-Ramos C, Reyes-Reyes R, Nakano-Miyatake M, Pérez-Meana HM (2018) Adaptive removable visible watermarking technique using dual watermarking for digital color images. Multimed Tools Appl 77(11):13047–13074CrossRefGoogle Scholar
Santos AJ (2014) Internet of things and smart objects for M-health monitoring and control. Procedia Technology 16:1351–1360CrossRefGoogle Scholar
Singh AK (2015) Multiple watermarking on medical images using selective discrete wavelet transform coefficients. J Med Imaging Health Inf 5(3):607–614CrossRefGoogle Scholar
Takpor T, Atayero AA (2015) Integrating internet of things and health solutions for students’ healthcare. In: Proceedings of the world congress on engineering. World Congress on Engineering, LondonGoogle Scholar
Tang MJ (2014) A high capacity image steganography using multi-layer embedding. Optik Int J Light Electron Opt 125(15):3972–3976CrossRefGoogle Scholar
Thévenaz PT (2000) Interpolation revisited [medical images application]. IEEE Trans Med Imaging 19(7):739–758CrossRefGoogle Scholar
Vaidya P, Chandra Mouli PVSSR (2017) A robust semi-blind watermarking for color images based on multiple decompositions. Multimed Tools Appl 76(24):25623–25656CrossRefGoogle Scholar
Vaidya P, Chandra Mouli PVSSR (2018) Adaptive, robust and blind digital watermarking using Bhattacharyya distance and bit manipulation. Multimed Tools Appl 77(5):5609–5635CrossRefGoogle Scholar
Wu X, Sun W (2014) High-capacity reversible data hiding in encrypted images by prediction error. Signal Process 104:387–400CrossRefGoogle Scholar