Drone delivery is an emerging service that gains growing attention. Authentication is critical to ensure a package is picked up by a legitimate drone (rather than a malicious one) and delivered to the correct receiver (rather than an attacker). As delivery drones are expensive and may carry important packages, a drone should stay away from users until the authentication succeeds. Thus, authentication approaches that require physical contact of drones cannot be applied. Bluetooth can indicate proximity without physical contact but is vulnerable to radio relay attacks. Our work leverages drone noises for authentication. While using sounds for authentication is highly usable, how to handle various attacks that manipulate sounds is an unresolved challenge. It is also unclear whether such a system is robust under various environmental sounds. We address these challenges by exploiting unique characteristics of drone noises. We thereby build an authentication system that does not rely on any sound fingerprints, keeps resilient to attacks, and is robust under environmental sounds. An extensive evaluation demonstrates its security and usability.

翻译：无人机配送是一项新兴服务，正日益受到关注。认证对于确保包裹由合法无人机（而非恶意无人机）提取并送达正确接收者（而非攻击者）至关重要。由于配送无人机成本高昂且可能承载重要包裹，在认证成功前应远离用户，因此需要物理接触无人机的认证方式无法适用。蓝牙虽能通过非接触方式指示接近性，但易受无线电中继攻击。我们的研究利用无人机噪音实现认证。尽管使用声音进行认证具有高度可用性，但如何应对各类声音操控攻击仍是一个未解决的挑战，且此类系统在多种环境噪音下的鲁棒性尚未明确。我们通过挖掘无人机噪音的独特性来应对这些挑战，构建了一套不依赖任何声音指纹、具备攻击抗性且对环境噪音鲁棒的认证系统。大量实验评估验证了其安全性与可用性。