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[OBB17] Exploring Formal Strategy Framework for the Security in e-Health based IoT Context using Computational Intelligence
Chapitres de Livre : Titre du livre: "Internet of Things and Big Data Technologies for Next Generation Healthcare", January 2017, Springer International Publishing, pp. 63-90, (isbn: 978-3-319-49735-8)
motcle:
Résumé:
This chapter proposes a novel strategic framework and computa-tionally intelligent model to measure possible vulnerabilities for security context in e-health. In order to keep track of security of e-health paradigm, the chapter conceives a bio-inspired model comprising the collective intelligence of social insects e.g. ant colony. Ant colony optimization is a computationally intelligent meta-heuristics, which takes care-off the different random and uncertain behavior of different sensors deployed towards e-health measures. The essential input is provided from interconnected wireless sensors under Internet of Things (IoT) paradigm and in-telligent social insects that could sense the possibility of threats for a patient moving in different physical locations during his medical diagnosis. Social insect ants can sense and communicate through a chemical, known as pheromone, remotely from their nest towards collection of food. The intensity of pheromone measure for different interconnected graphs of e-health could lead to a consolidated algorithm and finally the differences of intensi-ties can infer about the affected or safe path for propagation of medical information. Modelling the pheromone dynamics can be a precise measure to quantify the different e-health security issues like Sinkhole threat or sybil attack under IoT environment. The proposed pheromone alert is presented and compared statistically in terms of precision, to identify the classification of possible vulnerability.
BibTeX
| @inbook { | |||
| OBB17, | |||
| title | = | "{Internet of Things and Big Data Technologies for Next Generation Healthcare}", | |
| chapter | = | "{Exploring Formal Strategy Framework for the Security in e-Health based IoT Context using Computational Intelligence}", | |
| author | = | "Y. Ould Yahia and S. Banerjee and S. Bouzefrane and H. Boucheneb", | |
| year | = | 2017, | |
| publisher | = | "Springer International Publishing", | |
| pages | = | "63-90", | |
| isbn | = | "978-3-319-49735-8", | |
| } | |||
