This is a systematic review of over one hundred research papers about machine learning
methods applied to defensive and offensive cybersecurity. In contrast to previous reviews …

Network and service management encompasses a set of activities, methods, procedures,
and tools, whose ultimate goal is to guarantee the proper functioning of a networked system …

Multivariate time series data can be found in many application domains. Examples include
data from computer networks, healthcare, social networks, or financial markets. Often …

Visualizing communication logs, like NetFlow records, is extremely useful for numerous
tasks that need to analyze network traffic traces, like network planning, performance …

Operation technology networks, ie hard-and software used for monitoring and controlling
physical/industrial processes, have been considered immune to cyber attacks for a long …

Entropy-based traffic metrics have received substantial attention in network traffic anomaly
detection because entropy can provide fine-grained metrics of traffic distribution …

With the pervasive use of information technologies, the increasing availability of data
provides new opportunities for understanding user behaviors. Unearthing anomalies in user …

Technologies are presented for anomaly detection in a cloud environment using a sparsity
measure. In some examples, cloud metric data may be gathered and processed into a …

Designing innovative approaches to detect intrusive network activities is considered as one
of the most significant research topics in network security. Various computational methods …

Monitoring network traffic and detecting anomalies are essential tasks that are carried out
routinely by security analysts. The sheer volume of network requests often makes it difficult …