3 days ago · This study proposes an anomaly detection method for air quality monitoring based on Deep Smooth Random Sampling and Association Attention in Transformer (DSRS- ...

6 days ago · Statistical anomaly detection refers to the problem of recognising and quantifying distributional deviations of a dataset from its nominal expected behaviour.

6 days ago · ... anomaly detection is solved as a two-sample-test, introducing a test statistic that measures the distance between two samples. High energy physics, and in ...

4 days ago · This paper proposes an innovative approach capitalized on the distinctive characteristics of command and control (C&C) beacons, namely, time intervals and ...

2 days ago · In this context, the sampling strategy prioritizes the retention of erroneous traces from dominant processes, thus facilitating the identification and ...

5 days ago · Anomaly detection aims to separate anomalies from normal samples, and the pretrained network is promising for anomaly detection. ... principle for anomaly ...

2 days ago · While existing research in graph anomaly detection predominantly focuses on node-level anomaly detection ... anomalous samples, mitigating the issue of ...

5 days ago · LOF, SCAN, and ANOMALOUS demonstrate lower AUC values, suggesting poorer performance in identifying misbehavior. In summary, OCMLMD is the most effective ...

3 days ago · ... sample is abnormal during the anomaly detection stage. Results from the experiment indicate that this model has extremely high detection accuracy and speed.

2 days ago · Anomaly detection represents the opposite approach, whereby potential attacks are identified by constructing a model of normal behavior and detecting activities ...