学位论文简介

Thesis Title : Security Mechanism for critical data in Internet of Things Healthcare system.

IoT technology since it appeared, it has been become a pioneer in many applications like agriculture, transportation, and Health which lead to the name of Industry Internet of Things (IIoT) and contribute the overall application smart city where efficiency and quality of service are the priority. Regarding this application one of them is very essential, especially healthcare also known as Internet of Medical Things(IoMT), IoT play big role in the improvement of Health industry where patients and doctors exercise efficiently their work, by benefiting IoMT features applied  in monitoring, tracking, treating and other services. The data generated by sensors or medical devices can be accessible remotely.

Despite the opportunity brought by IoT in Health care the data in this field are very critical and they have been faced different attack, and based on different statistics  indicate the rise of  the rate of  malicious attack in healthcare systems and the introduction of IoT in this sector will also bring another dimension of security vulnerability. Normally IoT devices have constraint of computing power where data are sent to cloud for processing to offload the node devices,  and this solution is not enough according to characteristic of medical data which need optimum time response. Imagine system which is monitoring remotely the vital sign of patient such as  breathing or blood pressure here the time response matters, any delay may bring worst outcome. This makes security in IoT application in healthcare as priority. In the implementation  of   Internet of Medical Things(IoMT)  architecture like fog layer which contribute in terms of latency  shows the vulnerability, security threats and cyber-attacks. Secondly having information about the traffic of data in network  may lead to the vulnerability of the whole system.

To mitigate these issues  this thesis, propose technic to  address  above challenges faced by IoT in healthcare system :

· Data gathered by biosensors at edged devices are stored on fog layer and copied are available on cloud database to address challenges related to time response. In IoMT data are collected by sensors or medical devices are being sent to fog layer for processing to offload the end devices which has limited resources to improve the performance of the whole system by taking in consideration latency. Secondly issue related to scalability, and centralization are addressed by the approach of fog architecture computing enabled blockchain, and for security of the data public permissioned blockchain based cryptographic hash function using secure hashing have been proposed. In terms of privacy and enhancement of security, the Elliptical Curve Cryptography Digital Signature Algorithm (ECCDSA) for hashing certificate has been developed and used as immutable security technic for fog layer.

· Then, to enforce security in different perspectives by taking into account  detection of the attack  based on network traffic analysis, which has significant role in providing a valuable information about attempt of access of unauthorized user for system. Having the mechanism or tools to manage this kind of threat can be considered as preventive measure for a system, where in healthcare it has significant impact positively. To  implement this approach an intrusion detection system based on combination of Genetic algorithm and Machine learning technic is being proposed for the security of thing intrusion detection system for Smart Healthcare.

· Lastly, this work recognized the challenged introduced by Covid-19 outbreak in healthcare sector  by introducing a  machine learning technics method which can  improve and support to analyze healthcare data of covid19  test to identify the survival rate of patient to mitigate the management of pandemic in smart city and improve healthcare efficiency.

主要学术成果

[1] D. Ngabo, D. Wang, C. Iwendi, J. H. Anajemba, L. A. Ajao and C. Biamba, "Blockchain-Based Security Mechanism for the Medical Data at Fog Computing Architecture of Internet of Things," Electronics, vol. 10, no. 17, 2021.

[2] D. Ngabo, W. Dong, E. Ibeke, C. Iwendi and E. Masabo, "Tackling pandemics in smart cities using machine learning architecture," Mathematical Biosciences and Engineering, vol. 18, no. 6, pp. 8444-8461, 2021.

[3] C. Iwendi, J. H. Anajemba, C. Biamba and D. Ngabo , "Security of Things Intrusion Detection System for Smart Healthcare," Electronics, vol. 10, no. 12, 2021.

[4] E. Twahirwa, K. Mtonga, D. Ngabo and S. Kumaran, "A LoRa enabled IoT-based Air Quality Monitoring System for Smart City," in 2021 IEEE World AI IoT Congress (AIIoT), Seattle, WA, USA, 2021.

[5] J. H. Anajemba, T. Yue, C. Iwendi, P. Chatterjee and D. Ngabo, "A Secure Multiuser Privacy Technique for Wireless IoT Networks Using Stochastic Privacy Optimization," IEEE Internet of Things Journal, vol. 9, no. 4, pp. 2566 - 2577, 2021.