Cyber-Physical Fingerprinting for Internet of Things Authentication
In this poster, we expose some of our recent results on authenatication of the Internet of things.
Our results include new machine learning approaches for authenaticating IoT devices based on their environment,
as well as novel ideas to distinguish malicious attacks from normal environmental changes. The poster also
presents some of our related works on IoT jamming and stochastic moving target defense in IoT-like environments.
Our extensive outreach activities within the scope of the GCTC challenge are also presented.
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