… The impact of opportunistic sampling methods, selective sam… The impact of sampling
methods on traffic classification using … Flow-based anomaly detection using sampled traffic is an …

… flow sampling technique to improve anomaly detection in … Park, "Efficient anomaly detection
by modeling privilege flows using … Xiaochun, "Optimizing IP flow classification using feature …

… As Datasets contained both normal and anomalous traffic, to avoid the negative influence
of sample mean and variance, we used median and interquartile range (IQR) to scale the data …

… (PCA) for anomaly detection received a lot of attention from the networking community one
… aware of the established methodology for PCA anomaly detection, which by that time had …

… the control plane creates a new opportunity for the attacker to carry out … samples that are
used for training and testing during our model training. We randomly selected some samples …

… While the smart environment provides convenience to our daily lives, such as … Through
simulation trials, we obtain comparative analysis of different over-sampling and under-sampling …

… stakeholders the opportunity to plan future facilities using a … on whether the sample is
considered an outlier or not. In order … score beyond which the sample is considered an outlier. This …

… For example, in anomaly detection algorithms, sampling schemes degrade the performance
of the anomaly detection algorithms and introduce varying degrees and forms of distortion, …

… samples for FPs per chunk, with the aim to reduce the number of FPs. The proposed anomaly
detection … a detector per cluster, giving more opportunity for the detector to identify local …

… Different models are trained on different subsets, each of which is extracted by sampling
with replacement from the original training set (bootstrap samples/bags); this sampling ensures …