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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cryptography Key: Retrieved 06 Aug 2017, from http://en.wikipedia.org/wiki/Key_(cryptography)
Diffie, W., Hellman, M.: Multi-user cryptographic techniques. In: Proceedings of the AFIPS Proceedings, vol. 45, pp. 109–112, 8 June 1976
Diffie, W., Hellman, M.: New directions in cryptography. IEEE Trans. Inform. Theory 22(6), 644–654 (1976)
Praveenkumar, P., Catherine Priya, P., Avila, J., et al.: Wireless Pers. Commun. (2017). https://doi.org/10.1007/s11277-017-4795-x. Springer US, Print ISSN 0929-6212, Online ISSN 1572-834X
Anusudha, K., Venkateswaran, N., Valarmathi, J.: Multimed. Tools Appl. 76(2), 2911–2932 (2017). https://doi.org/10.1007/s11042-015-3213-1. Springer US, Print ISSN 1380-7501, Online ISSN 1573-7721
Hemeda, Afaf, Saif, Aasem, et al.: Simultaneous acute arterial and venous cerebral thrombosis and acute upper limb thrombotic ischemia due to combined uncommon hereditary factors for thrombophilia in young adult. J. Vascu. Med. Surg. 2017, 297 (2017)
Seong, A.C., et al.: A review of coronary artery disease research in Malaysia. Med. J. Malays. 71(Suppl), 42–57 (2016)
Nandavaram, S., Chandrasekar, V.T., Savici, D.: Acute pulmonary vascular talcosis: mimicking acute pulmonary embolism case report. J. Vasc. Med. Surg. 4, 272 (2016)
Schummer, W.: Towards optimal central venous catheter tip position. J. Vasc. Med. Surg. 2016, 260 (2016)
Al-Haj, A., Mohammad, A., Amer, A.: J Digit Imaging 30(1), 26–38. https://doi.org/10.1007/s10278-016-9901-1
Sarkar, A., Mandal, J.K.: Computational science guided soft computing based cryptographic technique using ant colony intelligence for wireless communication (ACICT). Int. J. Comput. Sci. Appl. (IJCSA) 4(5), 61–73 (2014). https://doi.org/10.5121/ijcsa.2014.4505. ISSN 2200-0011
Sarkar, A., Mandal, J.K.: Intelligent soft computing based cryptographic technique using chaos synchronization for wireless communication (CSCT). Int. J. Ambient Syst. Appl. (IJASA) 2(3), 11–20 (2014). https://doi.org/10.5121/ijasa.2014.2302. ISSN 2321-6344
Sarkar, A., Mandal, J.K.: Secured transmission through multi layer perceptron in wireless communication (STMLP). Int. J. Mob. Netw. Commun. Telemat. (IJMNCT) 4(4), 1–16. ISSN 1839-5678
Sarkar, A., Mandal, J.R.: Cryptanalysis of key exchange method using computational intelligence guided multilayer perceptron in wireless communication (CREMLP). Adv. Comput. Intell. Int. J. ACII 1(1), 1–9 (2014). ISSN 2317-4113
Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.-K., Stanley, H.E.: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23):e215–e220. Circulation Electronic Pages; http://circ.ahajournals.org/content/101/23/e215.full, 13 June 2000
Acknowledgements
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-981-13-1540-4_3
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1539-8
Online ISBN: 978-981-13-1540-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)