Nov 14, 2022 · We leverage an approach that uses a provenance graph to obtain execution traces of host nodes in order to detect anomalous behavior. By using ...
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We leverage an approach that uses a provenance graph to obtain execution traces of host nodes in order to detect anomalous behavior. By using the provenance.
Our approach leverages metric learning based detection to classify unknown APT attacks in real time. We use the provenance data to visualize the activity on the ...
Evolving advanced persistent threat detection using provenance graph and metric learning. G Ayoade, KA Akbar, P Sahoo, Y Gao, A Agarwal, K Jee, L Khan, ... 2020 ...
Jun 1, 2020 · We leverage an approach that uses a provenance graph to obtain execution traces of host nodes in order to detect anomalous behavior. By using ...
Jun 3, 2019 · The aim of this work is to evaluate the feasibility of applying advanced machine learning and provenance analysis techniques to automatically ...
May 5, 2024 · Advanced Persistent Threat Detection Using Data Provenance and Metric Learning https://t.co/FvPXjJDHWK APTSHIELD: A Stable, Efficient and ...
In this paper, we propose ConGraph, an APT attack detection method based on a provenance graph and process context in a CPS environment. To construct the ...
Sep 28, 2023 · Yegneswaran,. “Mining Data Provenance to Detect Advanced. Persistent Threats,” in International Workshop on. Theory and Practice of Provenance ...
This work proposes a novel machine learning-based system entitled MLAPT, which can accurately and rapidly detect and predict APT attacks in a systematic way.