Now showing items 1-6 of 6
Detecting anomalies by weighted rules
Anomaly detection focuses on modeling the normal behavior and identifying significant deviations, which could be novel attacks. The previously proposed LERAD algorithm can efficiently learn a succinct set of comprehensible ...
Learning rules from system call arguments and sequences for anomaly detection
Many approaches have been suggested and various systems have been modeled to detect intrusions from anomalous behavior of systems calls as a result of an attack. Though these techniques have been shown to be quite effective, ...
Machine learning for host-based anomaly detection
Anomaly detection techniques complement signature based methods for intrusion detection. Machine learning approaches are applied to anomaly detection for automated learning and detection. Traditional host-based anomaly ...
Spatio-temporal anomaly detection for mobile devices
With the increase in popularity of mobile devices, there has been a significant rise in mobile related security problems. The biggest threat for a mobile subscriber is lost or stolen device, which can lead to confidential ...
MORPHEUS: motif oriented representations to purge hostile events from unlabeled sequences
Most of the prevalent anomaly detection systems use some training data to build models. These models are then utilized to capture any deviations resulting from possible intrusions. The efficacy of such systems is highly ...
A representation scheme for finite length strings
This study is an attempt to create a canonical representation scheme for finite length strings to simplify the study of the theory behind different classes of patterns and to ease the understanding of the underlying ...