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Research Article

CAML: Cryptographic-Based Cloud Security for Healthcare Data with Machine Learning Technique

In Press, (this is not the final "Version of Record"). Available online 02 November, 2023
Author(s): Chaithra M.H.* and Vagdevi S.
Published on: 02 November, 2023

Article ID: e241023222580

DOI: 10.2174/0118722121241098230926064800

Price: $95

Abstract

Background: The Cloud model is one of the most realistic frameworks with a vast range of social networking interactions. In medical data, security is a major constraint as it incorporates information about the patients. The cloud environment subjected to mobility and openness is exposed to security issues and limits authorization levels for data transmission.

Objective: This paper aims to propose a security model for attack prevention within the healthcare environment.

Method: The proposed Cryptographic Attribute-based Machine Learning (CAML) scheme incorporates three stages. Initially, the homomorphic encryption escrow is performed for secure data transmission in the cloud. Secondly, the information of the users is evaluated based on the consideration of users' authorization. The authorization process for the users is carried out with the attribute-based ECC technique. Finally, the ML model with the classifier is applied for the detection and classification of attacks in the medical network.

Results: The detected attack is computed and processed with the CNN model. Simulation analysis is performed for the proposed CAML with conventional ANN, CNN, and RNN models. The simulation analysis of proposed CAML achieves a higher accuracy of 0.96 while conventional SVM, RF, and DT achieve an accuracy of 0.82, 0.89 and 0.93, respectively.

Conclusion: With the analysis, it is concluded that the proposed CAML model achieves higher classification accuracy for attack detection and prevention in the cloud computing environment.

[1]
L.M. Dang, M.J. Piran, D. Han, K. Min, and H. Moon, "A survey on internet of things and cloud computing for healthcare", Electronics, vol. 8, no. 7, p. 768, 2019.
[http://dx.doi.org/10.3390/electronics8070768]
[2]
T. Alam, "Cloud computing and its role in the information technology", IAIC Transac. Sustain. Digital Innov. (ITSDI), vol. 1, no. 2, pp. 108-115, 2020.
[http://dx.doi.org/10.34306/itsdi.v1i2.103]
[3]
K. Gai, J. Guo, L. Zhu, and S. Yu, "Blockchain meets cloud computing: A survey", IEEE Commun. Surv. Tutor., vol. 22, no. 3, pp. 2009-2030, 2020.
[http://dx.doi.org/10.1109/COMST.2020.2989392]
[4]
M. Mohammed Sadeeq, N.M. Abdulkareem, S.R.M. Zeebaree, D. Mikaeel Ahmed, A. Saifullah Sami, and R.R. Zebari, "IoT and Cloud computing issues, challenges and opportunities: A review", Qubahan Academic J., vol. 1, no. 2, pp. 1-7, 2021.
[http://dx.doi.org/10.48161/qaj.v1n2a36]
[5]
L. Rajabion, A.A. Shaltooki, M. Taghikhah, A. Ghasemi, and A. Badfar, "Healthcare big data processing mechanisms: The role of cloud computing", Int. J. Inf. Manage., vol. 49, pp. 271-289, 2019.
[http://dx.doi.org/10.1016/j.ijinfomgt.2019.05.017]
[6]
A. Darwish, A.E. Hassanien, M. Elhoseny, A.K. Sangaiah, and K. Muhammad, "The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: Opportunities, challenges, and open problems", J. Ambient Intell. Humaniz. Comput., vol. 10, no. 10, pp. 4151-4166, 2019.
[http://dx.doi.org/10.1007/s12652-017-0659-1]
[7]
L. Ehwerhemuepha, G. Gasperino, N. Bischoff, S. Taraman, A. Chang, and W. Feaster, "HealtheDataLab - a cloud computing solution for data science and advanced analytics in healthcare with application to predicting multi-center pediatric readmissions", BMC Med. Inform. Decis. Mak., vol. 20, no. 1, p. 115, 2020.
[http://dx.doi.org/10.1186/s12911-020-01153-7] [PMID: 31906929]
[8]
M. Shabbir, A. Shabbir, C. Iwendi, A.R. Javed, M. Rizwan, N. Herencsar, and J.C.W. Lin, "Enhancing security of health information using modular encryption standard in mobile cloud computing", IEEE Access, vol. 9, pp. 8820-8834, 2021.
[http://dx.doi.org/10.1109/ACCESS.2021.3049564]
[9]
R. Sivan, and Z.A. Zukarnain, "Security and privacy in cloud-based E-health system", Symmetry, vol. 13, no. 5, p. 742, 2021.
[http://dx.doi.org/10.3390/sym13050742]
[10]
I. Keshta, and A. Odeh, "Security and privacy of electronic health records: Concerns and challenges", Egyptian Inform. J., vol. 22, no. 2, pp. 177-183, 2021.
[http://dx.doi.org/10.1016/j.eij.2020.07.003]
[11]
J. Deepika, C. Rajan, and T. Senthil, "Security and privacy of cloud-and IoT-based medical image diagnosis using fuzzy convolutional neural network", Comput. Intell. Neurosci., vol. 2021, pp. 1-17, 2021.
[http://dx.doi.org/10.1155/2021/6615411] [PMID: 33790958]
[12]
D.K. Sharma, D.S. Chakravarthi, A.A. Shaikh, A.A.A. Ahmed, S. Jaiswal, and M. Naved, "The aspect of vast data management problem in healthcare sector and implementation of cloud computing technique", Mater. Today Proc., vol. 80, no. 3, pp. 3805-3810, 2021.
[13]
N. Rajkumar, and E. Kannan, "Security enhancement of e-healthcare system in cloud using efficient cryptographic method", In: Recent Trends in Communication and Intelligent Systems.., Springer: Singapore, 2021, pp. 47-55.
[http://dx.doi.org/10.1007/978-981-16-0167-5_6]
[14]
M. AbdulRaheem, "An enhanced lightweight speck system for cloud-based smart healthcare", In: International Conference on Applied Informatics.., Springer: Cham, 2021, pp. 363-376.
[15]
A. Chhaybi, and S. Lazaar, "Definition of a lightweight cryptographic solution to secure health data on IoT and cloud", General Lett. Math., vol. 10, no. 2, pp. 54-60, 2021.
[http://dx.doi.org/10.31559/glm2021.10.2.6]
[16]
A. Ali, M.F. Pasha, J. Ali, O.H. Fang, M. Masud, A.D. Jurcut, and M.A. Alzain, "Deep learning based homomorphic secure search-able encryption for keyword search in blockchain healthcare system: A novel approach to cryptography", Sensors, vol. 22, no. 2, p. 528, 2022.
[http://dx.doi.org/10.3390/s22020528] [PMID: 35062491]
[17]
K. Sowjanya, M. Dasgupta, and S. Ray, "A lightweight key management scheme for key-escrow-free ECC-based CP-ABE for IoT healthcare systems", J. Systems Archit., vol. 117, p. 102108, 2021.
[http://dx.doi.org/10.1016/j.sysarc.2021.102108]
[18]
H.K. Andi, "Estimating the role of blockchain, deep learning and cryptography algorithms in cloud security", J. Trends Comput. Sci. Smart Technol., vol. 3, no. 4, pp. 305-313, 2022.
[http://dx.doi.org/10.36548/jtcsst.2021.4.006]
[19]
S. Kumar, G. Karnani, M.S. Gaur, and A. Mishra, "Cloud security using hybrid cryptography algorithms", In 2nd International Conference on Intelligent Engineering and Management (ICIEM), London, United Kingdom, 28-30 April, 2021, pp. 599-604
[http://dx.doi.org/10.1109/ICIEM51511.2021.9445377]
[20]
K. Sundar, S. Sasikumar, and C. Jayakumar, "Enhanced cloud security model using QKDP (ECSM-QKDP) for advanced data security over cloud", Quantum Inform. Process., vol. 21, no. 3, p. 115, 2022.
[http://dx.doi.org/10.1007/s11128-022-03452-6]
[21]
K. Gupta, D. Gupta, S.K. Prasad, and P. Johri, "A review on cryptography based data security techniques for the cloud computing", In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 04-05 Mar, 2021, pp. 1039-1044
[http://dx.doi.org/10.1109/ICACITE51222.2021.9404568]
[22]
F. Thabit, A.P.S. Alhomdy, A.H.A. Al-Ahdal, and P.D.S. Jagtap, "A new lightweight cryptographic algorithm for enhancing data security in cloud computing", Glob. Transit. Proc., vol. 2, no. 1, pp. 91-99, 2021.
[http://dx.doi.org/10.1016/j.gltp.2021.01.013]
[23]
K.D. Abel, S. Misra, A. Agrawal, R. Maskeliunas, and R. Damasevicius, "Data security using cryptography and steganography technique on the cloud", In: Computational Intelligence in Machine Learning: Select Proceedings of ICCIML.., Springer: Singapore, 2022, pp. 475-481.
[http://dx.doi.org/10.1007/978-981-16-8484-5_46]
[24]
P. Velmurugadass, S. Dhanasekaran, S. Shasi Anand, and V. Vasudevan, "Enhancing Blockchain security in cloud computing with IoT environment using ECIES and cryptography hash algorithm", Mater. Today Proc., vol. 37, pp. 2653-2659, 2021.
[http://dx.doi.org/10.1016/j.matpr.2020.08.519]
[25]
A. Musa, and A. Mahmood, "Client-side cryptography based security for cloud computing system", In 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS), Coimbatore, India, 25-27 Mar, 2021, pp. 594-600
[http://dx.doi.org/10.1109/ICAIS50930.2021.9395890]
[26]
V.B. Savant, and R.D. Kasar, "A review on network security and cryptography", Res. J. Eng. Technol., vol. 12, no. 4, pp. 110-114, 2021.
[http://dx.doi.org/10.52711/2321-581X.2021.00019]
[27]
R. Adee, and H. Mouratidis, "A dynamic four-step data security model for data in cloud computing based on cryptography and steganography", Sensors, vol. 22, no. 3, p. 1109, 2022.
[http://dx.doi.org/10.3390/s22031109] [PMID: 35161853]
[28]
M. Tahir, M. Sardaraz, Z. Mehmood, and S. Muhammad, "CryptoGA: A cryptosystem based on genetic algorithm for cloud data security", Cluster Comput., vol. 24, no. 2, pp. 739-752, 2021.
[http://dx.doi.org/10.1007/s10586-020-03157-4]

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