Abstract
In this paper, session key exchange and authentication technique executing in parallel fashion using the fine tuning of Two Tier Neural Network in wireless communication has been proposed for secured information transmission. E-Health online transmission of any medical information needs cryptographic implementations. Any medical information related to the patients which need to be shared secretly between different authorized parties. This proposed technique can be merged with any digitized cardiological-based Expert System with patients’ data preservation. Ischemic Heart Disease (IHD) is a set of cardiovascular problems with decreased blood flow rate. It is mainly caused due to narrowing of coronary arteries due to plaque accumulation in the channel. ECG signal diagnosing IHD is being digitized for secured transmission purpose. In this proposed technique identical Two Tier Neural Network is used by the both patient and Cardiologist. They mould to evoke a fine tuning of synaptic weight based on learning rules depending on their output value. Finally tuned weight vector becomes the secret session key for that particular session. At the time of parallel key exchange procedure, key authentication technique is also performed simultaneously. Different types of parametric tests were carried out and outputs are being compared with few classical techniques, which show favorable results for the proposed system.
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Our deep sense of gratitude to physionet database https://physionet.org/physiobank/database/stdb/. The signals from MIT-BIH ST Change Database had been used for experimental purpose.
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Sarkar, A., Dey, J., Bhowmik, A., Mandal, J.K., Karforma, S. (2019). Computational Intelligence Based Neural Session Key Generation on E-Health System for Ischemic Heart Disease Information Sharing. In: Mandal, J., Sinha, D., Bandopadhyay, J. (eds) Contemporary Advances in Innovative and Applicable Information Technology. Advances in Intelligent Systems and Computing, vol 812. Springer, Singapore. https://doi.org/10.1007/978-981-13-1540-4_3
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DOI: https://doi.org/10.1007/978-981-13-1540-4_3
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