Abstract
The development in the field of miniature sensors and wireless communication enables the successful deployment of Internet of Things (IoT) in the healthcare sector. The healthcare data generated by the medical sensors is very sensitive and enough to qualify as an instance of big data. In this paper, a secure framework is designed to assist the diabetic patients. The sensors’ data of each patient is used to generate context aware correlation rules by using map-reduce apriori algorithm. From these rules another labeled dataset is created to build a classifier for predicting the present state of the patient. After the successful deployment of this classifier on the service provider side, secure communication has been provided between the patient and the service provider using Key-Policy Attribute Based Encryption. Hence, providing an IoT based secure ambient assisted living system for diabetic patient may be helpful to the healthcare sector.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Rashidi, P., Mihailidis, A.: A survey on ambient-assisted living tools for older adults. IEEE J. Biomed. Health Inform. 17(3), 579–590 (2013). https://doi.org/10.1109/JBHI.2012.2234129
Anjana, R.M., Deepa, M., Pradeepa, R., et al.: Prevalence of diabetes and prediabetes in 15 states of India: results from the ICMR-INDIAB population-based cross-sectional study. Lancet Diab. Endocrinol. 5(8), 585–596 (2017). https://doi.org/10.1016/S2213-8587(17)30174-2
National Diabetes Statistics Report: 2017: Estimates of Diabetes and Its Burden in the United States. Accessed 8 Apr 2018
United States Department of Health and Human Services, Privacy, Security, and Electronic Health Records. https://www.hhs.gov/sites/default/files/ocr/privacy/hipaa/understanding/consumers/privacy-security-electronic-records.pdf. Accessed 19 Apr 2018
United States Department of Health and Human Services, Sharing Health Information with Family Members and Friends. https://www.hhs.gov/sites/default/files/ocr/privacy/hipaa/understanding/consumers/sharing-family-friends.pdf. Accessed 19 Apr 2018
Benjelloun, F.Z., Lahcen, A.A., Belfkih, S.: An overview of big data opportunities, applications and tools. In: IEEE Conference on Intelligent Systems and Computer Vision (ISCV), Fez, Morocco, pp. 1–6 (2015). https://doi.org/10.1109/ISACV.2015.7105553
Lin, X.: MR-Apriori: association rules algorithm based on MapReduce. In: IEEE 5th International Conference on Software Engineering and Service Science, Beijing, China, pp. 141–144 (2014). https://doi.org/10.1109/ICSESS.2014.6933531
Maitrey, S., Jha, C.K.: Handling big data efficiently by using map reduce technique. In: IEEE International Conference on Computational Intelligence and Communication Technology, Ghaziabad, India, pp. 703–708 (2015). https://doi.org/10.1109/CICT.2015.140
Forkan, A., Khalil, I., Tari, Z.: CoCaMAAL: a cloud-oriented context-aware middle-ware in ambient assisted living. Future Gener. Comput. Syst. 35, 114–127 (2014). https://doi.org/10.1016/j.future.2013.07.009
Forkan, A.R.M., Khalil, I., Ibaida, A., Tari, Z.: BDCaM: big data for context-aware monitoring-a personalized knowledge discovery framework for assisted healthcare. IEEE Trans. Cloud Comput. 5(4), 628–641 (2017). https://doi.org/10.1109/TCC.2015.2440269
Forkan, A.R.M., Khalil, I.: A probabilistic model for early prediction of abnormal clinical events using vital sign correlations in home-based monitoring. In: IEEE International Conference on Pervasive Computing and Communications (PerCom), Sydney, NSW, Australia, pp. 1–9 (2016). https://doi.org/10.1109/PERCOM.2016.7456519
Rodrigues, J.J.P.C., Segundo, D.B.D.R., Junqueira, H.A., et al.: Enabling technologies for the internet of health things. IEEE Access 6, 13129–13141 (2018). https://doi.org/10.1109/ACCESS.2017.2789329
Zhao, Z.: An efficient anonymous authentication scheme for wireless body area networks using elliptic curve cryptosystem. J. Med. Syst. 38(2), 1–7 (2014). https://doi.org/10.1007/s10916-014-0013-5
He, D., Zeadally, S.: Authentication protocol for an ambient assisted living system. IEEE Commun. Mag. 53(1), 71–77 (2015). https://doi.org/10.1109/MCOM.2015.7010518
Yao, X., Chen, Z., Tian, Y.: A lightweight attribute-based encryption scheme for the internet of things. Future Gener. Comput. Syst. 49(C), 104–112 (2015). https://doi.org/10.1016/j.future.2014.10.010
Hong, H., Sun, Z.: High efficient key-insulated attribute based encryption scheme without bilinear pairing operations. SpringerPlus: SpringerOpen J. 1–12 (2016). https://doi.org/10.1186/s40064-016-1765-9.
Karati, A., Amin, R., Biswas, G.P.: Provably secure threshold- based ABE scheme without bilinear map. Arab. J. Sci. Eng. 41(8), 3201–3213 (2016). https://doi.org/10.1007/s13369-016-2156-9
Pei, J., Han, J., Kamber, M. (eds.): Data Mining: Concepts and Techniques (English), 3rd edn. ElsevieR Publication, Amsterdam (2012)
https://physionet.org/works/MIMICIIClinicalDatabase/. Accessed 20 Oct 2017
http://markahall.blogspot.in/2013/10/weka-and-hadoop-part-1.html. Accessed 15 Jan 2018
https://aws.amazon.com/emr/. Accessed 11 Dec 2017
Singh, M., Rajan, M.A., Shivraj, V.L., Balamuralidhar, P.: Secure MQTT for internet of things (IoT). In: IEEE Fifth International Conference on Communication Systems and Network Technologies, Gwalior, India, pp. 746–751 (2015). https://doi.org/10.1109/CSNT.2015.16
Alsulami, M.H., Atkins, A.S., Campion, R.J., Alaboudi, A.A.: An enhanced conceptual model for using ambient assisted living to provide a home proactive monitoring system for elderly Saudi Arabians. In: IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), Hammamet, Tunisia, pp. 1443–1449 (2017). https://doi.org/10.1109/AICCSA.2017.214
Costa, S.E., et al.: Integration of wearable solutions in AAL environments with mobility support. J. Med. Syst. 39(12), 1–8 (2015). https://doi.org/10.1007/s10916-015-0342-z
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
Sowjanya, K., Dasgupta, M. (2019). Secure Framework for Ambient Assisted Living System. In: Mandal, J., Mukhopadhyay, S., Dutta, P., Dasgupta, K. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2018. Communications in Computer and Information Science, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-13-8581-0_34
Download citation
DOI: https://doi.org/10.1007/978-981-13-8581-0_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-8580-3
Online ISBN: 978-981-13-8581-0
eBook Packages: Computer ScienceComputer Science (R0)