1
Department of CSE , PVP Siddhartha Institute of Technology, Vijayawada, India
(sppraveen@pvpsiddhartha.ac.in)
2
Department of CSE. Dhanekula Institute of Engineering & Technology. Ganguru , Vijayawada
(balu.thati9@gmail.com)
3
Department of CSE, Koneru Lakshmaiah Educational Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India
(akshayagokul2009@mail.com)
4
Department of CSE, NRI Institute of Technology, Agiripalli, Andhra Pradesh, India
(ssindhurapraveen@gmail.com)
5
Department of medical instruments engineering techniques, Alfarahidi University, Baghdad, Iraq
(m.altaee@alfarahidiuc.edu.iq)
6
Department of Computer Engineering techniques, Alturath University college, Baghdad, Iraq
(mohammed.jalil@turath.edu.iq)
Abstract :
Individuals start - ups and large corporations in the healthcare sector have new opportunities to outsource data and outsourcing computation offers to cloud computing. Although the cloud computing paradigm presents users with interesting and cost effective opportunities still in its early stage, and using the cloud introduces with new obstacles. A another issue is the security of cloud data, which may be affected the data particularly in the case of healthcare systems that store and process sensitive data and is outsourced to a cloud computing system.Although there has been significant progress in the development of health services there are still issues that need to be settled regarding, integrity, the security, large-scale deployment, service integration, confidentiality of sensitive medical data. To ensure that sensitive medical data is captured, stored and consumed securely, an information sharing policy syntax based on rules, the Data Capture and Auto Identification Reference (DACAR) platform features a Single Point of Contact as well as data buckets that are hosted on a cost-effective cloud infrastructure and scalable.As a result, security, accuracy, and precision are achieved in this analysis and query time is reduced.
Keywords :
Data Security; Cloud Computing; Dynamic Cloud Computing Architecture; Data Privacy; Auto Identification Reference (DACAR); Data Capture
References :
[1]H. Hesham, M. Ashour and T. el-Shabrawy, "An Energy Efficient ConstraintRRH to Bbu Association in Cloud Radio Access Networks," 2020 37th National Radio Science Conference (NRSC), pp. 155-163, 2020.
[2]H. K. Apat, K. Bhaisare, B. Sahoo and P. Maiti, "Energy Efficient Resource Management in Fog Computing Supported Medical Cyber-Physical System," 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), pp. 1-6, 2020, doi: 10.1109/ICCSEA49143.2020.9132855.
[3]C. Thiam and F. Thiam, "An Energy-Efficient VM migrations optimization in Cloud Data Centers," 2019 IEEE AFRICON, 2019, pp. 1-5, doi: 10.1109/AFRICON46755.2019.9133776
[4]S. M. Moghaddam, S. F. Piraghaj, M. O’Sullivan, C. Walker and C. Unsworth, "Energy-Efficient and SLA-Aware Virtual Machine Selection Algorithm for Dynamic Resource Allocation in Cloud Data Centers," 2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC), pp. 103-113,2018. doi: 10.1109/UCC.2018.00019.
[5]M. S. Puneetha and M. B. Nirmala, "Energy efficient power aware VM scheduling in decentralized cloud," 2017 2nd International Conference On Emerging Computation and Information Technologies (ICECIT), pp. 1-4, 2017.doi: 10.1109/ICECIT.2017.8453332.
[6]Shally, S. K. Sharma and S. Kumar, "Energy efficient resource management in cloud environment: Progress and challenges," 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC), pp. 636-641,2016. doi: 10.1109/PDGC.2016.7913200.
[7] D. Springall, Z. Durumeric and J. A. Halderman, "FTP: The Forgotten Cloud," 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2016, pp. 503-513.
[8] Mehdi Bahrami and Mukesh Singhal, “The Role of Cloud Computing Architecture in Big Data”, Information Granularity, Big Data, and Computational Intelligence, Vol. 8, pp. 275-295, Chapter 13, Pedrycz and S.-M. Chen (eds.), Springer, 2015 http://goo.gl/4gNW3s
[9] Mehdi Bahrami and Mukesh Singhal, “DCCSOA: A Dynamic Cloud Computing Service-Oriented Architecture”, IEEE International Conference on Information Reuse and Integration (IEEE IRI’15), San Francisco, CA, USA. Aug 2015.
[10] M. Smith, W. Buchanan, C. Thuemmler, D. Bell and R. Hazelhoff, “Analysis of Information Governance and Patient Data Protection within Primary Health Care,” To appear in Int. J. for Quality in Health Care.
[11] S. Yi, Z. Hao, Z. Qin, Q. Li, in 2015 Third IEEE Workshop on Hot Topics in WebSystems and Technologies (HotWeb), Washington, DC. Fog Computing: Platform and Applications, (2015), pp. 73–78. https://doi.org/10.1109/ HotWeb.2015.22
[12] H. Dubey, J. Yang, N. Constant, A. M. Amiri, Q. Yang, K. Makodiya, inProceedings of the ASE BigData & SocialInformatics 2015 Article No. 14Kaohsiung, Taiwan - October 07 - 09, 2015. Fog data: Enhancing telehealth big data through fog computing, (2015)
[13] T. N. Gia, M. Jiang, A. Rahmani, T. Westerlund, P. Liljeberg, H. Tenhunen, in2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing,Liverpool. Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction, (2015), pp. 356–363. https://doi.org/10.1109/ CIT/IUCC/DASC/PICOM.2015.51
[14] Landau, Susan. "Highlights from Making Sense of Snowden, Part II: What's Significant in the NSA Revelations" Security & Privacy, IEEE 12.1 (2014): 62-64.
[15] N. Paladi, A. Michalas, and C. Gehrmann, “Domain based storage protection with secure access control for the cloud,” in Proceedings of the 2014 International Workshop on Security in Cloud Computing, ASIACCS ’14, (New York, NY, USA), ACM, 2014.
[16] A. Michalas, N. Paladi, and C. Gehrmann, “Security aspects of e-health systems migration to the cloud,” in e-Health Networking, Applications and Services (Healthcom), 2014 IEEE 16th International Conference on, pp. 212–218, Oct 2014
[17] Krishna, T., Praveen, S. P., Ahmed, S., & Srinivasu, P. N. Software-driven secure framework for mobile healthcare applications in IoMT. Intelligent Decision Technologies, (Preprint), 1-14.
[18] Fan, Lu, "DACAR platform for eHealth services cloud." Cloud Computing (CLOUD), 2011 IEEE International Conference on. IEEE, 2011.
[19] R. Zhang and L. Liu, “Security Models and Requirements for Healthcare Application Clouds,” in Proc of CLOUD ’10. IEEE, 2010, pp. 268–275.
[20] Praveen, S.P., Ali, M.H., Jaber, M.M., Buddhi, D., Prakash, C., Rani, D.R. and Thirugnanam, T., 2022. IOT-Enabled Healthcare Data Analysis in Virtual Hospital Systems Using Industry 4.0 Smart Manufacturing. International Journal of Pattern Recognition and Artificial Intelligence.
[21] Praveen, S. Phani, et al. "A robust framework for handling health care information based on machine learning and bigdata engineering Techniques." International Journal of Healthcare Management (2022): 1-18.
[22] Praveen, S. P., Krishna, T. B. M., Chawla, S. K., & Anuradha, C. (2021). Virtual Private Network Flow Detection in Wireless Sensor Networks Using Machine Learning Techniques. International Journal of Sensors Wireless Communications and Control, 11(7), 716-724.
[23] Osman, L., Taiwo, O., Elashry, A. and Ezugwu, A.E., 2023. Intelligent Edge Computing for IoT: Enhancing Security and Privacy. Journal of Intelligent Systems & Internet of Things, 8(1).
[24] Praveen, S. P., Ghasempoor, H., Shahabi, N., & Izanloo, F. (2023). A hybrid gravitational emulation local search-based algorithm for task scheduling in cloud computing. Mathematical Problems in Engineering, 2023.
[25] P. Sherubha, S. Sasirekha, A. Dinesh Kumar Anguraj et al., “An efficient unsupervised learning approach for detecting an anomaly in cloud,” Comput Syst Sci Eng, vol. 45, no. 1, pp. 149–166, 2023.
[26] Phani Praveen, S., Ali, M. H., Jarwar, M. A., Prakash, C., Reddy, C. R. K., Malliga, L., & Chandru Vignesh, C. (2023). 6G assisted federated learning for continuous monitoring in wireless sensor network using game theory. Wireless Networks, 1-27.
| Style | # |
|---|---|
| MLA | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil. "A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing." Journal of Intelligent Systems and Internet of Things, Vol. 9, No. 1, 2023 ,PP. 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |
| APA | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil. (2023). A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing. Journal of Journal of Intelligent Systems and Internet of Things, 9 ( 1 ), 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |
| Chicago | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil. "A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing." Journal of Journal of Intelligent Systems and Internet of Things, 9 no. 1 (2023): 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |
| Harvard | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil. (2023). A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing. Journal of Journal of Intelligent Systems and Internet of Things, 9 ( 1 ), 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |
| Vancouver | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil. A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing. Journal of Journal of Intelligent Systems and Internet of Things, (2023); 9 ( 1 ): 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |
| IEEE | S. Phani Praveen, Balamuralikrishna Thati, Ch Anuradha, S. Sindhura, Mohammed Altaee, M. Abdul jalil, A Novel Approach for Enhance Fusion Based Healthcare System In Cloud Computing, Journal of Journal of Intelligent Systems and Internet of Things, Vol. 9 , No. 1 , (2023) : 84-96 (Doi : https://doi.org/10.54216/JISIoT.090106) |