Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …

Traditionally, applications that are used in large and small enterprises were deployed on
“bare metal” servers installed with operating systems. Recently, the use of multiple virtual …

Context: Run-time detection of system anomalies at the host level remains a challenging
task. Existing techniques suffer from high rates of false alarms, hindering large-scale …

Industrial device scanners allow anyone to scan devices on private networks and the
Internet. They were intended as network security tools, but they are commonly exploited as …

We propose a nature-inspired approach to estimate the probability density function (pdf)
used for data clustering based on the optimum-path forest algorithm (OPFC). OPFC …

Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems
(NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor system …

Traditionally, applications that are used in large and small enterprises were deployed on"
bare metal" servers installed with operating systems. Recently, the use of multiple virtual …

The Insider threat is minimally addressed by current information security practices, yet the
insider poses the most serious threat to organization through various malicious activities …

Anomaly detection is an important problem that has been popularly researched within
diverse research areas and application domains. One of the open problems in anomaly …