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As the drone becomes widespread in numerous crucial applications with many powerful functionalities (e.g., reconnaissance and mechanical trigger), there are increasing cases related to misused drones for unethical even criminal activities. Therefore, it is of paramount importance to identify these malicious drones and track their origins using digital forensics. Traditional drone identification techniques for forensics (e.g., RF communication, ID landmarks using a camera, etc.) require high compliance of drones. However, malicious drones will not cooperate or even spoof these identification techniques. Therefore, we present an exploration for a reliable and passive identification approach based on unique hardware traits in drones directly (e.g., analogous to the fingerprint and iris in humans) for forensics purposes. Specifically, we investigate and model the behavior of the parasitic electronic elements under RF …