Securing Pacemakers using Runtime Monitors over Physiological Signals

Abstract

Wearable and implantable medical devices (IMDs) are increasingly deployed to diagnose, monitor, and provide therapy for critical medical conditions. Such medical devices are safety-critical cyber-physical systems (CPSs). These systems support wireless features introducing potential security vulnerabilities. Although these devices undergo rigorous safety certification processes, runtime security attacks are inevitable. Based on published literature, IMDs such as pacemakers and insulin infusion systems can be remotely controlled to inject deadly electric shocks and excess insulin, posing a threat to a patient’s life. While prior works based on formal methods have been proposed to detect potential attack vectors using different forms of static analysis, these have limitations in preventing attacks at runtime. This paper discusses a formal framework for detecting cyber-physical attacks on a pacemaker by monitoring its security policies at runtime. We propose a wearable device that senses the Electrocardiogram (ECG) and Photoplethysmogram (PPG) of the body to detect attacks in a pacemaker. To facilitate the design of this device, we map the security policies of a pacemaker w.r.t ECG and PPG, paving the way for designing formal verification monitors for pacemakers for the first time using multiple physiological signals. The proposed monitoring framework allows the synthesis of parallel monitors from a given set of desired security policies, where all the monitors execute concurrently and generate an alarm to the user in the case of policy violation. Our implementation and the performance evaluation results demonstrate the technical feasibility of designing such a wearable device for attack detection in pacemakers. This device is separate from the pacemaker, ensuring no need for re-certification of pacemakers. Our approach is amenable to the application of security patches when new attack vectors are detected, making the approach ideal for runtime monitoring of medical CPSs.