238
A. Tissaoui and M. Saidi
– Identification of vulnerabilities at a various level in the network. which work
as entry points for numerous attacks.
– adaptation of trust relationships on the following levels:
• IoT entities;
• data perception (sensor sensibility, preciseness, security, reliability, persistence, data collection efficiency);
• privacy preservation (user data and personal information);
• data fusion and mining;
• data transmission and communication;
• quality of IoT services;
• acceptance of shared standards to cope with the diversity of devices and
applications;
– creation of simulations and models of uncertainty phenomena;
References
1. Knight, F.H.: Risk: Uncertainty and Profit, pp. 224–225. Beard Books, Washington
(2002)
2. Evans, D.: The internet of things: how the next evolution of the internet is changing
everything, vol. 1, pp. 1–11. Cisco Internet Business Solutions Group (IBSG), San
Jose (2011)
3. Gietzelt, M., et al.: Home-centered health-enabling technologies and regional health
information systems an integration approach based on international standards.
Methods Inf. Med. 53, 160–166 (2014)
4. Wu, W., Pirbhulal, S., Sangaiah, A.K., Mukhopadhyay, S.C., Li, G.: Optimization
of signal quality over comfortability of textile electrodes for ECG monitoring in fog
computing based medical applications. Future Gener. Comput. Syst. 86, 515–526
(2018)
5. Schatten, M.: Smart residential buildings as learning agent organizations in the
internet of things. Bus. Syst. Res. 5(1), 34–46 (2014)
6. Brad, B.S., Murar, M.M.: Smart buildings using IoT technologies. Constr. Unique
Build. Struct. 5(20), 15–27 (2014)
7. Qi, J., Yang, P., Min, G., Amft, O., Dong, F., Xu, L.: Advanced internet of things
for personalised healthcare systems: a survey. Pervasive Mob. Comput. 41, 132–149
(2017)
8. Islam, S.R., Kwak, D., Kabir, M.H., Hossain, M., Kwak, K.S.: The internet of
things for health care: a comprehensive survey. IEEE Access 3, 678–708 (2015)
9. Baker, S.B., Xiang, W., Atkinson, I.: Internet of things for smart healthcare: technologies, challenges, and opportunities. IEEE Access 5(C), 26521–26544 (2017)
10. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Context aware computing for the Internet of things: a survey. IEEE Commun. Surv. Tutor. 16(1),
414–454 (2014)
11. Dhanvijay, M.M., Patil, S.C.: Internet of things: a survey of enabling technologies
in healthcare and its applications. Comput. Netw. 153, 113–131 (2019)
12. Bilcke, J., Beutels, P., Brisson, M., Jit, M.: Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.
Med. Decis. Making 31(4), 675–692 (2011)
A. Tissaoui and M. Saidi
– Identification of vulnerabilities at a various level in the network. which work
as entry points for numerous attacks.
– adaptation of trust relationships on the following levels:
• IoT entities;
• data perception (sensor sensibility, preciseness, security, reliability, persistence, data collection efficiency);
• privacy preservation (user data and personal information);
• data fusion and mining;
• data transmission and communication;
• quality of IoT services;
• acceptance of shared standards to cope with the diversity of devices and
applications;
– creation of simulations and models of uncertainty phenomena;
References
1. Knight, F.H.: Risk: Uncertainty and Profit, pp. 224–225. Beard Books, Washington
(2002)
2. Evans, D.: The internet of things: how the next evolution of the internet is changing
everything, vol. 1, pp. 1–11. Cisco Internet Business Solutions Group (IBSG), San
Jose (2011)
3. Gietzelt, M., et al.: Home-centered health-enabling technologies and regional health
information systems an integration approach based on international standards.
Methods Inf. Med. 53, 160–166 (2014)
4. Wu, W., Pirbhulal, S., Sangaiah, A.K., Mukhopadhyay, S.C., Li, G.: Optimization
of signal quality over comfortability of textile electrodes for ECG monitoring in fog
computing based medical applications. Future Gener. Comput. Syst. 86, 515–526
(2018)
5. Schatten, M.: Smart residential buildings as learning agent organizations in the
internet of things. Bus. Syst. Res. 5(1), 34–46 (2014)
6. Brad, B.S., Murar, M.M.: Smart buildings using IoT technologies. Constr. Unique
Build. Struct. 5(20), 15–27 (2014)
7. Qi, J., Yang, P., Min, G., Amft, O., Dong, F., Xu, L.: Advanced internet of things
for personalised healthcare systems: a survey. Pervasive Mob. Comput. 41, 132–149
(2017)
8. Islam, S.R., Kwak, D., Kabir, M.H., Hossain, M., Kwak, K.S.: The internet of
things for health care: a comprehensive survey. IEEE Access 3, 678–708 (2015)
9. Baker, S.B., Xiang, W., Atkinson, I.: Internet of things for smart healthcare: technologies, challenges, and opportunities. IEEE Access 5(C), 26521–26544 (2017)
10. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Context aware computing for the Internet of things: a survey. IEEE Commun. Surv. Tutor. 16(1),
414–454 (2014)
11. Dhanvijay, M.M., Patil, S.C.: Internet of things: a survey of enabling technologies
in healthcare and its applications. Comput. Netw. 153, 113–131 (2019)
12. Bilcke, J., Beutels, P., Brisson, M., Jit, M.: Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.
Med. Decis. Making 31(4), 675–692 (2011)