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#Project Title Non-detectable security exploits in healthcare Abstract The deployment of embedded systems in military, healthcare, and commercial environments has seen a considerable surge in recent years. This has opened the door for adversarial parties to exploit security vulnerabilities of these systems to inject malicious processes to degrade their performance, modify their functionality, or extract sensitive data. The current project explores various possible attacks targetting a human fall detection system. The target system utilizes sensory data from a smartwatch to detect the action of human falling using machine learning algorithms. We will explore attacks