The enormous number of network packets transferred in modern networks together with the high speed transmissions hamper implementation successful IT security mechanisms. In addition, virtual create highly dynamic and flexible environments which differ widely from well-known infrastructures past decade. Network forensic investigation that aims at detection covert channels, malware usage or anoma...

Anomaly detection refers to the problem of finding patterns in data that do not conform to expected normal behavior. Anomaly detection is extensively used in a wide variety of applications such as monitoring business news, epidemic or bioterrorism detection, intrusion detection, hardware fault detection, network alarm monitoring, and fraud detection [13]. Anomaly detection in target tracking is...

Anomaly detection is one of the basic issues in data processing that addresses different problems healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis models are required ensure consistency reliability. With rise size dimensionality collected data, deep learning techniques, such as autoencoder (AE), rec...