Abstract
Security and privacy of patients’ information remains a major issue of concern among health practitioners. Therefore, measures must be put in place to ensure that unauthorized individual do not have access to this information. However, the adoption of digital alternative of retrieving and documenting medical information has further opened it up to more attacks. This article presents a modified blowfish algorithm for securing textual and graphical medical information. The F-function used in generating round sub-keys was strengthened so as to produce a strong key that could resist differential attacks. Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI) of 98.85% and 33.65% revealed that the modified algorithm is sensitive to changes in its key and also resistive to differential attacks. Furthermore, the modified algorithm demonstrated a better encryption and decryption time than the existing blowfish algorithm.
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References
Christiana, A.O., Adeshola, G.Q., Oluwatobi, A.N.: Implementation of textual information encryption using 128, 192 and 256 bits advanced encryption standard algorithm. Ann. Comput. Sci. Ser. 15(2), 153–159 (2017)
Alabaichi, A.M.: Security Analysis of Blowfish Algorithm, September 2013. https://doi.org/10.1109/ICoIA.2013.6650222
Andriole, K.P.: Security of electronic medical information and patient privacy: what you need to know. J. Am. Coll. Radiol. 11(12), 1212–1216 (2014). https://doi.org/10.1016/j.jacr.2014.09.011
Bai, T., et al.: A lightweight method of data encryption in BANs using electrocardiogram signal. Future Gener. Comput. Syst. (2018). https://doi.org/10.1016/j.future.2018.01.031
Chauhan, A., Gupta, J.: A novel technique of cloud security based on hybrid encryption by Blowfish and MD5. In: 4th International Conference on Signal Processing, Computing and Control (ISPCC) (2017)
Chen, X., Hu, C.: Adaptive medical image encryption algorithm based on multiple chaotic mapping. Saudi J. Biol. Sci. 24(8), 1821–1827 (2017). https://doi.org/10.1016/j.sjbs.2017.11.023
Deng, X.H., Zhu, C.X.: Image encryption algorithms based on chaos through dual scrambling of pixel position and bit. J. Commun. 35(3), 216–223 (2014)
Christina, L., Joe, I.: Optimized Blowfish encryption technique. Int. J. Innov. Res. Comput. Commun. Eng. 2(7), 5009–5015 (2014)
Gowda, S.N.: Using Blowfish encryption to enhance security feature of an image, vol. 200, pp. 126–129 (2016)
Hazra, T.K., Mahato, A., Mandal, A., Chakraborty, A.K.: A hybrid cryptosystem of image and text files using Blowfish and Diffie-Hellman techniques. In: 8th Annual Industrial Automation and Electromechanical Engineering Conference (IEMECON), pp. 137–141 (2017)
Hua, Z., Jin, F., Xu, B., Huang, H.: 2D logistic-sine-coupling map for image encryption. Sig. Process. (2018). https://doi.org/10.1016/j.sigpro.2018.03.010
ICIT: Institute for Critical Infrastructure Technology. Hacking healthcare in 2016: lessons the healthcare industry can learn from the OPM breach (2016). http://icitech.org/wp-content/uploads/2016/01/ICIT-Brief-Hacking-Healthcare-IT-in-2016.pdf
Ismail, S.M., Said, L.A., Radwan, A.G., Madian, A.H., Abu-elyazeed, M.F.: Generalized double-humped logistic map-based medical image encryption. J. Adv. Res. 10, 85–98 (2018). https://doi.org/10.1016/j.jare.2018.01.009
Jack, M.: Survey : 64 percent of patients use a digital device to manage health. Mobi Health News (2018)
Kaur, A., Singh, G.: A random selective block encryption technique for secure image cryptography using Blowfish algorithm. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 1290–1293 (2018)
Keckley, P.H.: Privacy and security in health care : a fresh look. Deloitte Center for Health Solutions, pp. 1–20 (2013)
Kondawar, S.S., Gawali, D.H.: Blowfish algorithm for patient health monitoring. In: International Conference on Inventive Computation Technologies (ICICT), pp. 1–6 (2016)
KPMG: Health care and cyber security: increasing threats require increased capabilities (2015). https://assets.kpmg.com/content/dam/kpmg/pdf/2015/09/cyber-health-care-surveykpmg-2015.pdf
Landge, I.A.: VHDL based Blowfish implementation for secured embedded system design, pp. 3–7 (2017)
Langer, S.G.: Cyber-security issues in healthcare information technology. J. Dig. Imaging 2016(October 2016), 117–125 (2017). https://doi.org/10.1007/s10278-016-9913-x
Lima, J.B., Madeiro, F., Sales, F.J.R.: Signal processing: image communication encryption of medical images based on the cosine number transform. Sig. Process. Image Commun. 35, 1–8 (2015). https://doi.org/10.1016/j.image.2015.03.005
Martin, G., Martin, P., Hankin, C.: Cybersecurity and healthcare : how safe are we ? 3179, 4–7 (2017). https://doi.org/10.1136/bmj.j3179
Masilamani, V.: ScienceDirect reversible reversible data data hiding hiding scheme scheme during during encryption encryption using using machine machine learning learning. Proc. Comput. Sci. 133, 348–356 (2018). https://doi.org/10.1016/j.procs.2018.07.043
Netwrix Research Lab: 2017 IT Risks Report (2017)
Nie, T., Zhang, T.: A study of DES and Blowfish encryption algorithm. In: IEEE Region 10 Conference (TENCON 2009), pp. 1–4 (2009)
Nur, K., St, P., Darlis, D., Si, S.: An implementation of data encryption for Internet of Things using Blowfish algorithm on FPGA 2. In: 2nd International Conference on Information and Communication Technology (ICoICT), pp. 75–79 (2014)
Panda, M.: Performance Analysis of Encryption Algorithms for Security, pp. 278–284 (2016)
Park, E.H., Kim, J., Wile, L.L., Park, Y.S.: Factors affecting intention to disclose patientsÕ health information. Comput. Secur. (2018). https://doi.org/10.1016/j.cose.2018.05.003
Patel, P., Patel, R., Patel, N.: Integrated ECC and Blowfish for smartphone security. Proc. Comput. Sci. 78(December 2015), 210–216 (2016). https://doi.org/10.1016/j.procs.2016.02.035
Quist-Aphetsi, K., Laurent, N., Anca, C.P., Sophie, G., Jojo, M.E., Nii, N.Q.: A cryptographic technique for security of medical images in health information systems. Proc. Comput. Sci. 58, 538–543 (2015). https://doi.org/10.1016/j.procs.2015.08.070
Raigoza, J.: Evaluating performance of symmetric encryption algorithms, pp. 1378–1381 (2016). https://doi.org/10.1109/CSCI.2016.257
William, J.G., Adam, F., Adam, L.: Threats to information security—public health implications. New Engl. J. Med. 377, 1–3 (2017)
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Akande, N.O., Abikoye, C.O., Adebiyi, M.O., Kayode, A.A., Adegun, A.A., Ogundokun, R.O. (2019). Electronic Medical Information Encryption Using Modified Blowfish Algorithm. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11623. Springer, Cham. https://doi.org/10.1007/978-3-030-24308-1_14
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