Risk Evaluation and Attack Detection in Heterogeneous IoMT Devices Using Hybrid Fuzzy Logic Analytical Approach

Area of Science:

• Cybersecurity in Healthcare
• Medical Device Security
• Risk Assessment Methodologies

Background:

• The Internet of Medical Things (IoMT) offers personalized healthcare but introduces significant security vulnerabilities.
• Heterogeneous IoMT devices require comprehensive risk assessment due to diverse functionalities, protocols, and inherent weaknesses.
• Existing security measures may not adequately address the complex threat landscape of interconnected medical devices.

Purpose of the Study:

• To develop and validate a hybrid risk assessment model for IoMT devices using fuzzy logic and the Fuzzy Analytical Hierarchy Process (FAHP).
• To quantify and prioritize security risks associated with different IoMT devices and attack vectors.
• To provide a framework for informed decision-making regarding IoMT security implementation.

Main Methods:

• A hybrid approach combining fuzzy logic and FAHP was employed for risk evaluation.
• Qualitative descriptors including occurrence frequency, consequence severity, and weight factors were defined.
• A case study involving Bluetooth Low Energy (BLE) attacks on an oximeter, smartwatch, and smart peak flow meter was conducted.

Main Results:

• The FAHP method successfully calculated fuzzy weights and risk levels, enabling prioritization of security concerns.
• Smartwatches exhibited a high-risk level of 8.57 for injection attacks, necessitating immediate attention.
• Jamming attacks presented the lowest risk level (1), indicating a lower priority compared to other threats.

Conclusions:

• The proposed FAHP-based risk assessment effectively evaluates IoMT security threats, aiding developers and researchers.
• Findings highlight critical vulnerabilities in specific devices like smartwatches, guiding the implementation of targeted security measures.
• This methodology assists healthcare decision-makers in understanding the relative importance of risk factors for robust IoMT security.