Date of Award

26-6-2023

Document Type

Thesis

School

School of Electrical & Electroncis Engineering

Programme

Ph.D.-Doctoral of Philosophy

First Advisor

Dr.J.Siva

Second Advisor

Dr.R.Sundararaman

Keywords

Field Programmable Gate Array, FPGA, Cyber Security

Abstract

The emerging cyber landscape demands the data to be protected by CIA triad which comprises Confidentiality, Integrity and Availability(CIA). For the swift diagnosis process, a standard patient data representation in the form of EHR (Electronic Health Record) plays a significant role. There exists a necessity to protect this EHR through the information security mechanisms namely encryption, watermarking and intrusion detection system for ensuring application and network layer security. Implementation of medical data protection solution on a reconfigurable hardware platform can further strengthen EHR security. This research work effectively achieves the CIA triad for healthcare cybersecurity at data, application and network layer levels.

The data level security was accomplished using the novel encryption and watermarking techniques. The algorithm was experimented on 155 medical images (consists of different modalities in which CT-50, MRI - 50, PET-40, CR-8 and Ultrasound-2) collected from Ariyalur Medical College, Tamil Nadu, India and 10 customized EPR datasets (Patient information, biometric information and QR code of the Patient ID). The resistance of the proposed encryption algorithm to various attacks in real time data communication scenario was validated through the attack analyses such as statistical analysis, occlusion attack analysis and key sensitivity.

Further, the potency of the watermarking algorithm was evaluated using the imperceptibility and robustness analyses by subjecting the watermarked images to 20 different real time channel and noise attacks variants. In the application layer, security was achieved through three tier user authentication schemes. It incorporates three tier authenticationas a login credentials (dedicated username-password), real time face detection of authorized medical practitioners, reconfigurable hardware-centric one time password (OTP) for the successful authorization. In the network layer, security is assured through the implementation of Detection System to detect the Denial of Service (DoS) attacks. A customized dataset was created through the network traffic by generating the 8264 normal and 3004 abnormal (SYN and ICMP) packets.

Among the 11268 packets, 5 fold cross validation was carried out to estimate the detection capability. It was reported with an accuracy of 99% in identifying the DoS attacks. These proposed solutions were tested on software and hardware platforms to ensure the platform independency. On the whole, the proposed cybersecurity framework ensures the security in all the three levels thereby providing adequate security in real-time scenarios of data communication applications.

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