Pervasive m-Healthcare Framework for Diabetes

Authors

  • Madhu Sharma Gaur Department of Information Technology Graphic Era University, Dehradun, India
  • Bhasker Pant Department of Information Technology Graphic Era University, Dehradun, India

Keywords:

Diabetes, Mobile Pervasive Environment, Pervasive m-Healthcare, Security Assurance, and Trust Management.

Abstract

Vision of pervasive computing includes wireless communication and information processing anywhere, anytime
using mobile sensor devices connected seamlessly. Pervasive environment characterized by highly dynamic,
open and diverse infrastructure where resource-restricted dissimilar mobile objects have the ability of Ad-hoc
network set-up, self-organization and cooperation for information exchange and distributed operation unknown
by the user. In such open computing environments, traditional security schemes and encryption algorithms
cannot be always applied to address the security assurance challenges. Therefore, concepts of trust and
reputation evaluation emerged by researchers. In addition to that in human-centric healthcare applications,
reliability and trustworthiness between communicating nodes, quality of information assessment cannot be
effectively ensured through hard security concerns. Thus soft security analysis becomes an important aspect for
enhancing the security assurance and degree of trust in ICT enabled application and services where information
is ubiquitous. In our proposed research work, we explore existing pervasive security and trust methods to assess
the challenging gap. We put forward need of soft security and proposed a trust metric for trust based security
assessment with classical clustering technique for energy-efficient resource restricted trusted and secure
communication. Major security attacks and impact of signal strength on security for unnoticed pervasive
services also evaluated. In winding up, we present pervasive healthcare application framework especially
focused to awareness and quality remote care for diabetes, to realize and validate the conceptual model with
case study.

Downloads

Download data is not yet available.

References

Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013). A survey on ambient intelligence in

healthcare. Proceedings of the IEEE, 101(12), 2470-2494.

Alemdar, H., & Ersoy, C. (2010). Wireless Sensor Networks for Healthcare: A Survey”. In Proceedings of

Computer Networks, 54(15), 2688–2710.

Ali, H., Shahzad, W., & Khan, F. A. (2012). Energy-efficient clustering in mobile ad-hoc networks using multi-

objective particle swarm optimization. Applied Soft Computing, 12(7), 1913-1928.

Almenárez, F., Marín, A., Campo, C., & Garcia, C. (2004, August). PTM: A pervasive trust management model

for dynamic open environments. In First Workshop on Pervasive Security, Privacy and Trust PSPT (Vol. 4, pp.

-8).

Journal of Graphic Era University

Vol. 5, Issue 2, 69-83, 2017

ISSN: 0975-1416 (Print), 2456-4281 (Online)

Bao, F., Chen, I. R., Chang, M., & Cho, J. H. (2011). Hierarchical trust management for wireless sensor

networks and its application to trust-based routing. In Proceedings of the 2011 ACM Symposium on Applied

Computing, 9(2), (pp. 1732-1738). ACM.

Bao, F., Chen, R., Chang, M., & Cho, J. H. (2012). Hierarchical trust management for wireless sensor networks

and its applications to trust-based routing and intrusion detection. IEEE Transactions on Network and Service

Management, 9(2), 169-183.

Bu, S., Yu, F. R., Liu, X. P., Mason, P., & Tang, H. (2011). Distributed combined authentication and intrusion

detection with data fusion in high-security mobile ad hoc networks. IEEE Transactions on Vehicular

Technology, 60(3), 1025-1036.

Chang, E., Hussain, F., & Dillon, T. (2006). Trust and reputation for service-oriented environments:

technologies for building business intelligence and consumer confidence. John Wiley & Sons.

Cho, J. H., Swami, A., & Chen, R. (2011). A survey on trust management for mobile ad hoc networks. IEEE

Communications Surveys & Tutorials, 13(4), 562-583.

Cisco. (2010-2015). Cisco visual networking index: global mobile data traffic forecast, www.cisco.com

El-Haleem, A. M. A., & Ali, I. A. (2011). TRIUMF: Trust-based routing protocol with controlled degree of

selfishness for securing MANET against packet dropping attack. International Journal of Computer Science,

(4), 99-110.

Gaur, M. S., & Pant, B. (2014). A Bio-inspired trusted clustering for mobile pervasive environment. In

Proceedings of the Third International Conference on Soft Computing for Problem Solving 259: (pp. 553-564).

Springer India.

Gaur, M. S., & Pant, B. (2014). Trust metric based soft security in mobile pervasive environment. International

Journal of Computer Network and Information Security, 6(10), 64-71.

Gaur, M. S., & Pant, B. (2015). Impact of signal-strength on trusted and secure clustering in mobile pervasive

environment. Procedia Computer Science, 57, 178-188.

Gaur, M. S., & Pant, B. (2015). Trusted and secure clustering in mobile pervasive environment. Human-Centric

Computing and Information Sciences, 5(32), 1-17.

Ghorbel, M., Khatib, M., Mhamed, A., & Mokhtari, M. (2009). Secured and trusted service provision in

pervasive environment. In 2009 IEEE International Conference on Wireless and Mobile Computing,

Networking and Communications, (pp. 400-405), IEEE.

Hsieh, M. Y., Huang, Y. M., & Chao, H. C. (2007). Adaptive security design with malicious node detection in

cluster-based sensor networks. Computer Communications, 30(11), 2385-2400.

I. D. F. (2013), International Diabeted Federation Diabetes Atlas, 6th edition.

International diabetes federation, (2014). Key findings update, IDF diabetes Atlas. 6/e.

Liang, X., Li, X., Barua, M., Chen, L., Lu, R., Shen, X., & Luo, H. (2012). Enable pervasive healthcare through

continuous remote health monitoring. IEEE Wireless Communications, 19(6), 10-18.

Liu, J., Yu, F. R., Lung, C. H., & Tang, H. (2009). Optimal combined intrusion detection and biometric-based

continuous authentication in high security mobile ad hoc networks. IEEE Transactions on Wireless

Communications, 8(2), 806-815.

Nwin, N., Whiting, D., Gariguata, L., Ghyoot, G., & Ganeds, D. (2011). Diabetes atlas, international diabetes

federation, Brussels, Belgium, 5/e.

Sridhar, V., & Hämmäinen, H. (2011). Mobile Internet: Indian telecom leading the way, DataQuest.

Journal of Graphic Era University

Vol. 5, Issue 2, 69-83, 2017

ISSN: 0975-1416 (Print), 2456-4281 (Online)

T. C. G. (2010). TCG MPWG mobile trusted module specification, version 1.0, Revision 7.02 29.

T. C. G. (2009). Mobile Phone Work Group, Selected use case analyses-v 1.0.

Velloso, P. B., Laufer, R. P., Cunha, D. D. O., Duarte, O. C. M., & Pujolle, G. (2010). Trust management in

mobile ad hoc networks using a scalable maturity-based model. IEEE Transactions on Network and Service

Management, 7(3), 172-185.

Weiser, M. (1991). The computer for the 21st century-scientific American special issue on communications.

Computers, and Networks (September 1991), 94-104.

Yang, H., Luo, H., Ye, F., Lu, S., & Zhang, L. (2004). Security in mobile ad hoc networks: challenges and

solutions. IEEE Wireless Communications, 11(1), 38-47.

Zhang, K., Wang, C., & Wang, C. (2008). A secure routing protocol for cluster-based wireless sensor networks

using group key management. In 2008 4th International Conference on Wireless Communications, Networking

and Mobile Computing, (pp. 1-5), IEEE.

Downloads

Published

2023-02-28

How to Cite

Gaur, M. S., & Pant, B. (2023). Pervasive m-Healthcare Framework for Diabetes. Journal of Graphic Era University, 5(2), 69–83. Retrieved from https://www.journal.riverpublishers.com/index.php/JGEU/article/view/100

Issue

Section

Articles