CONTINUUM detects APT attacks by training a spatial-temporal graph autoencoder on benign provenance graph snapshots and flagging high KNN-distance embeddings as anomalies, optionally under federated learning with homomorphic encryption.
2020 IEEE Symposium on Security and Privacy (SP) , 1172–1189URL: https://api.semanticscholar.org/CorpusID:216263050
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CONTINUUM: Detecting APT Attacks through Spatial-Temporal Graph Neural Networks
CONTINUUM detects APT attacks by training a spatial-temporal graph autoencoder on benign provenance graph snapshots and flagging high KNN-distance embeddings as anomalies, optionally under federated learning with homomorphic encryption.