Turning Noises to Fingerprint-Free "Credentials": Secure and Usable Drone Authentication
arxiv(2023)
摘要
Drones have been widely used in various services, such as delivery and
surveillance. Authentication forms the foundation of the security of these
services. However, drones are expensive and may carry important payloads. To
avoid being captured by attackers, drones should keep a safe distance from the
verifier before authentication succeeds. This makes authentication methods that
only work in very close proximity not applicable. 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 how to ensure robustness under
various environmental sounds. Being the first in the literature, we address the
two major challenges by exploiting unique characteristics of drone noises. We
thereby build an authentication system that does not rely on any drone
sound fingerprints, keeps resilient to attacks, and is robust under
environmental sounds. An extensive evaluation demonstrates its security and
usability.
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