Channel Prediction-Based Security Authentication for Artificial Intelligence of Things.

ABSTRACT: The emerging physical-layer unclonable attribute-aided authentication (PLUA) schemes are capable of outperforming traditional isolated approaches, with the advantage of having reliable fingerprints. However, conventional PLUA methods face new challenges in artificial intelligence of things (AIoT) applications owing to their limited flexibility. These challenges arise from the distributed nature of AIoT devices and the involved information, as well as the requirement for short end-to-end latency. To address these challenges, we propose a security authentication scheme that utilizes intelligent prediction mechanisms to detect spoofing attack. Our approach is based on a dynamic authentication method using long short term memory (LSTM), where the edge computing node observes and predicts the t

SUBMITTER: Qiu X 

PROVIDER: S-EPMC10422243 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature