Now showing items 1-10 of 24
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 ...
PHAD: packet header anomaly detection for identifying hostile network traffic
We describe an experimental packet header anomaly detector (PHAD) that learns the normal range of values for 33 fields of the Ethernet, IP, TCP, UDP, and ICMP protocols. On the 1999 DARPA off-line intrusion detection ...
Trajectory boundary modeling of time series for anomaly detection
We address the problem of online detection of unanticipated modes of mechanical failure given a small set of time series under normal conditions, with the requirement that the anomaly detection model be manually verifiable ...
Improving learning implicit user interest hierarchy with variable length phrases
A continuum of general to specific interests of a user called a user interest hierarchy (UIH) represents a user's interests at different abstraction levels. A UIH can be learned from a set of web pages visited by a user. ...
Identifying variable-length meaningful phrases with correlation functions
Finding meaningful phrases in a document has been studied in various information retrieval systems in order to improve the performance. Many previous statistical phrase finding methods had different aim such as document ...
A machine learning approach to anomaly detection
An analysis of the 1999 DARPA/Lincoln Laboratory evaluation data for network anomaly detection
We investigate potential simulation artifacts and their effects on the evaluation of network anomaly detection systems in the 1999 DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set. A statistical ...
Identifying outliers via clustering for anomaly detection
Detecting known vulnerabilities (Signature Detection) is not sufficient for complete security. This has raised recent interest in Anomaly Detection (AD), in which a model is built from normal behavior and significant ...
Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms
We investigate techniques to automatically determine the number of clusters to return from hierarchical clustering and segmentation algorithms. We propose an efficient algorithm, the L Method, that finds the "knee" in a ...