Hunting for Insider Threats Using LSTM-Based Anomaly Detection

Insider threats are one of the most difficult problems to solve, given the privileges and information available to insiders to launch different types of attacks. Current security systems can record and analyze sequences from a deluge of log data, potentially becoming a tool to detect insider threats...

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Veröffentlicht in:	IEEE transactions on dependable and secure computing 2023-01, Vol.20 (1), p.451-462
Hauptverfasser:	Villarreal-Vasquez, Miguel, Modelo-Howard, Gaspar, Dube, Simant, Bhargava, Bharat
Format:	Artikel
Sprache:	eng
Schlagworte:	Anomalies Anomaly detection Computational modeling endpoint detection and response (EDR) Hidden Markov models high-dimensional data insider threats long short-term memory (LSTM) Markov chains order-aware recognition (OAR) problem Security systems sequence analysis Sequences Testing Training variable-length system activity event sequences Vocabulary
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