As the IoMT rapidly expands, severe security risks shadow its profound benefits inpatient monitoring and data management. These devices, integral to critical care like pace-maker shocks and insulin dosing, often sacrifice robust security for functionality due totheir limited capabilities. This critical vulnerability exposes them to exploits that couldhave fatal consequences. This thesis addresses these urgent security gaps by exploring in-novative protection strategies through systematic reviews and simulated penetration testingon a mimicked IoMT environment. Our findings expose pronounced deficiencies withinexisting security frameworks, focusing on Bluetooth LE and Wi-Fi threats, especially theinadequate mechanisms to secure Bluetooth LE connections, commonly used in IoMTdevices and DOS attacks targeted directly to the IoMT devices. In response, two novelsecurity algorithms were designed to enhance the resilience of IoMT systems against cy-ber threats. This algorithm integrates dynamic whitelisting and blacklisting, MAC addressverification, UDID verification, and NFC-based device authentication to curtail unautho-rized access and uphold data integrity. The adopted strategy not only addresses specificsecurity loopholes identified during penetration testing but also establishes a frameworkcapable of adapting to evolving threats. Through this research, we aim to contribute to theongoing discourse on IoMT security, underscoring the critical need for continuous adapta-tion of security measures to protect against emerging vulnerabilities in the rapidly evolvinglandscape of IoT devices. This work aspires to lay the groundwork for future research anddevelopment in IoMT security strategies, fostering a deeper understanding and implemen-tation of adequate security measures within medical technology.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-130450 |
Date | January 2024 |
Creators | Shaban, Ryustem, Husein, Ahmad |
Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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