Home > Archives > IJSRST1841248
Power Efficient, Reliable & Secure Body Area Network using Clustering
Authors(3) :-Shaikh Ayaz Shaikh Mahmood, Dr. M. S. Kathane, Yogesh B. Jadhao
Healthcare systems use a medical text mining which have been increasingly facilitating health condition monitoring and disease modelling. System works on the Personal Health Information (PHI) of the user. and analysis, which can hardly afford the dynamic health condition fluctuation Healthcare system grant users access to range of health information and medical knowledge. In proposed system I basically created the database of 150 to 200 diseases with their precaution suggestions. System will output the next highly probable disease by narrowing down the number of diseases from the list of diseases according to the related symptoms either entered by the users or captured by the different sensors nodes. Benefit of the system is all the information about disease, precautions and healthcare are store at one place. Unfortunately, delegating both storage and computation to the untreated entity would bring a series of security and privacy issues. One of the controversial issues for PHI is how the technology could threaten the privacy of patient health information. The proposed system focused on fine-grained privacy-preserving static medical text access.
Shaikh Ayaz Shaikh Mahmood, Dr. M. S. Kathane, Yogesh B. Jadhao
WBAN, WSN, Cloud Computing, K-Mean Clustering Algorithm, Rijndeal AES algorithm
- R.A. Miller, “Medical diagnostic decision support systems Past, present, and future A threaded bibliography and brief commentary,” J. Amer. Med. Inf. Assoc., vol. 1, pp. 8–27, 1994.
- W. Siegenthaler, Differential Diagnosis in Internal Medicine: From Symptomto Diagnosis. New York: Thieme Medical Publishers, 2011.
- S. F.Murray and S. C. Pearson, “Maternity referral systems in developing countries :Current knowledge and future research needs, ”Social Sci. Med., vol. 62, no. 9, pp. 2205–2215, May 2006.
- L. Li, L. Jing, and D. Huang, “Protein-protein interaction extraction from biomedical literatures based on modified SVM-KNN,” in Nat. Lang. Process. Know. Engineer., 2009, pp. 1–7.
- H. Kordylewski and D. Graupe, “Applications of the LAMSTAR neural network to medical and engineering diagnosis/fault detection,” in Proc7th Artificial Neural Networks in Eng. Conf., St. Louis, MO, 1997.
- D. Graupe and H. Kordylewski, “A large memory storage and retrieval neural network for adaptive retrieval and diagnosis,” Int. J. Software Eng. Knowledge Eng., vol. 8, no. 1, pp. 115–138, 1998.
- Kokol P, Povalej, P., Leni?, M, Štiglic, G.: Building classifier cellular automata. 6th international conference on cellular automata for research and industry, ACRI 2004, Amsterdam, The Netherlands, October 25-27, 2004. (Lecture notes in computer science, 3305). Berlin: Springer, 2004, pp. 823-830.
- G.Z. Wu, “The application of data mining for medical database”, Master Thesis of Department of Biomedical Engineering, Chung Yuan University, Taiwan, Chung Li, 2000.
- R. Carvalho, R. Isola, and A. Tripathy, “MediQuery—An automated decision support system,” in Proc. 24th Int. Symp. Comput.-Based Med. Syst., Jun. 27–30, 2011, pp. 1–6.
- Shucheng Yu, Cong Wang, KuiRen, Wenjing Lou in their paper “Attribute based data sharing with attribute revocation”
- C.Y. Hsu, C.S. Lu and S.C. Pei,Image Feature Extraction in Encrypted Domain with Privacy preserving SIFT, IEEE Trans. on Image Processing, 21(11): 4593-4607, 2012.
- Jun Zhou, Zhenfu Cao, Xiaolei Dong, Xiaodong Lin “PPDM: Privacy-preserving Protocol for Dynamic Medical Text Mining and Image Feature Extraction from Secure Data Aggregation in Cloud-assisted e-Healthcare Systems,” IEEE journal of selected topics in signal processing.
- Olawuni, Omotayo, Adegoke, Olarinoye ,“Medical image Feature Extraction: A Survey,” International Journal of Electronics Communication and Computer Technology (IJECCT) Volume 3 Issue 5 (September 2013).
- Peter L. Stanchev, David Green Jr., BoyanDimitrov, “High Level Colour Similarity Retrievl,” 28th international conference ICT & P 2003, Varna, Bulgaria.
- Jun Zhou, Zhenfu Cao, XiaoleiDond, “Securing M-Healthcare Social Networks: Challenges
Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-05-31
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 322-332
Manuscript Number : IJSRST1841248
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Shaikh Ayaz Shaikh Mahmood, Dr. M. S. Kathane, Yogesh B. Jadhao, "Power Efficient, Reliable & Secure Body Area Network using Clustering", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 8, pp.322-332, May-June-2018.
Journal URL : http://ijsrst.com/IJSRST1841248