Direct marketing campaigns are one of the main fundraising sources for nonprofit
organizations and their effectiveness is crucial for the sustainability of the organizations. The …

The emergence of microservice architecture in Cloud systems poses a new challenges for
the reliability operation and maintenance. Due to numerous services and diverse types of …

In this paper, we analyze the Internet traffic from a different point of view based on Benford's
law, an empirical law that describes the distribution of leading digits in a collection of …

Large backbone networks are regularly affected by a range of anomalies. This paper
presents an online anomaly detection algorithm based on Kernel Density Estimates. The …

Border Gateway Protocol (BGP) is the core component of the Internet's routing infrastructure.
Abnormal routing behavior impairs global Internet connectivity and stability. Hence …

The “locally linear reconstruction”(LLR) provides a principled and k-insensitive way to
determine the weights of k-nearest neighbor (k-NN) learning. LLR, however, does not …

Real-time network traffic anomaly detection is crucial for the confidentiality, integrity, and
security of network information. Machine learning approaches are widely used to distinguish …

This paper addresses the problem of detecting anomalous multivariate co-occurrences
using a limited number of unlabeled training observations. A novel method based on using a …

The automated detection of sequential anomalies in time series is an essential task for many
applications, such as the monitoring of technical systems, fraud detection in high-frequency …

The application of machine learning models to the analysis of network measurement
problems has largely increased in the last decade; however, there is still no clear best …