Now showing items 1-10 of 24
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, ...
A protocol language approach to generating client-server software
Client-server software is becoming more common as the Internet grows. To ease the burden of repeatedly writing low-level communication and protocol code, we seek to design a protocol language, My Simple Protocol Language ...
Enabling mobile agents communication
In this paper, we investigate the need for well-suited remote communication architectures to address communication issues in mobile agent environments. We study the implication of mobility for agent architectures – ...
Learning states and rules for time series anomaly detection
In this paper, we investigate machine learning techniques for discovering knowledge that can be used to monitor the operation of devices or systems. Specifically, we study methods for generating models that can detect ...
Personalized ranking of search results with implicitly learned user interest hierarchies
Web search engines are usually designed to serve all users, without considering the interests of individual users. Personalized web search incorporates an individual user's interests when deciding relevant results to return. ...
Boundary detection in tokenizing network application payload for anomaly detection
Most of the current anomaly detection methods for network traffic rely on the packet header for studying network traffic behavior. We believe that significant information lies in the payload of the packet and hence it is ...
Learning rules for time series anomaly detection
We describe a multi-dimensional time series anomaly detection method in which each point in a test series is required to match the value, slope, and curvature of a point seen in training (with an optional sequential ...
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
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 ...