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2018 14th European Dependable Computing Conference (EDCC) (2018)
Ia?i, Romania
Sep 10, 2018 to Sep 14, 2018
ISBN: 978-1-5386-8060-5
pp: 140-143
Recent advances in contextual anomaly detection attempt to combine resource metrics and event logs to uncover unexpected system behaviors at run-time. This is highly relevant for critical software systems, where monitoring is often mandated by international standards and guidelines. In this paper, we analyze the effectiveness of a metrics-logs contextual anomaly detection technique in a middleware for Air Traffic Control systems. Our study addresses the challenges of applying such techniques to a new case study with a dense volume of logs, and finer monitoring sampling rate. Guided by our experimental results, we propose and evaluate several actionable improvements, which include a change detection algorithm and the use of time windows on contextual anomaly detection.
air traffic control, middleware, safety-critical software, software metrics

M. Farshchi et al., "Contextual anomaly detection for a critical industrial system based on logs and metrics," 2018 14th European Dependable Computing Conference (EDCC), Ia?i, Romania, 2018, pp. 140-143.
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