Internet of medical things-based authentication for an optimized watermarking of encrypted EEG.

Medical data are increasing drastically due to the vast development of medical sciences. The security of this immense data is also a challenge of the present era. Image watermarking is a technique to secure medical data from alteration. Authentication of patients records is also necessary in case of medical data transmission. In this paper, an optimized electroencephalogram watermarking technique are proposed with dual authentication using Advanced encryption standards (AES) and speeded-up robust features is proposed. Scaling factor plays an important role to balance the properties of watermarking algorithm. The cuckoo search optimization is used to get the optimized scaling factor. The Henon encryption (HE) is used to enhance the security of sub-band obtained from identity of the patient image used as the watermark. The diagonalized Hessenberg decomposition (HD) is used for embedding watermark while secured hash algorithm (SHA-256) is used to protect watermark against malicious attacks. For the proposed technique, detailed security analysis has been performed for AES encryption technique. Various performance metrics are computed for the proposed technique to estimate the effectiveness of the watermarking system. [ABSTRACT FROM AUTHOR]