… The rapid growing network brings efficiency and convenience to our life, as well as the … can
be used for network anomaly detection via scientific study of traffic samples, this procedure is …

… a scalable, unsupervised approach for detecting anomalies in the Internet of Things (IoT). …
anomaly detection method that creates a negative sample from the positive, observed sample…

… 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 …

… We aim to proposed an end-to-end neural network to detect irregular samples. Accordingly,
as explained previously, merely D network plays the role of anomaly detector in videos and …

… 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 …

… The boundless Internet connectivity provides tremendous convenience and opportunities for
… Though both datasets contains both normal and abnormal network traffic samples, we only …

… While ICT systems have brought unprecedented convenience, when in abnormal states …
Firstly, we randomly sample the training data from the normal sequence set. Then, we sepa…

… ability to convert any higher dimensional anomaly detection problem to a one-dimensional …
) is recommended for small samples. The default maximum sample size for version 1 is set to …

… In this paper, we propose a new neural network for anomaly detection … Anomaly detection
differs from the traditional classification … to list all possible negative (anomaly) samples. 2) It is a …