Browsing Computer Science by Subject "Anomaly detection"
Now showing items 1-5 of 5
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DILAF: A framework for distributed analysis of large-scale system logs for anomaly detection
(Wiley, 2019-02)System logs constitute a rich source of information for detection and prediction of anomalies. However, they can include a huge volume of data, which is usually unstructured or semistructured. We introduce DILAF, a framework ... -
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ... -
Incremental analysis of large-scale system logs for anomaly detection
(IEEE, 2019)Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations ... -
On spectral analysis of the Internet delay space and detecting anomalous routing paths
(TÜBİTAK, 2019)Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ... -
Using convolutional neural networks to automate aircraft maintenance visual inspection
(MDPI, 2020-12)Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant ...
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