Latent Dirichlet Allocation (LDA) and Variational Inference are applied in near real-time to detect anomalies in ground vehicle network traffic for a ground vehicle network. The technical approach, that utilizes the Natural Language Processing (NLP) technique to detect potential malicious attacks and network configuration issues, is described and the results of a proof of concept implementation are provided. Potential use cases for applying the technique in the aircraft and avionics domain are provided.
Latent Dirichlet Allocation (LDA) for Anomaly Detection in Avionics Networks
2020-10-11
1159986 byte
Conference paper
Electronic Resource
English
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