We present an overview of our research in real time data mining-based intrusion detection
systems (IDSs). We focus on issues related to deploying a data mining-based IDS in a real …

This paper presents a series of studies on probabilistic properties of activity data in an
information system for detecting intrusions into the information system. Various probabilistic …

Assurance technologies for computer security have failed to have significant impacts in the
marketplace, with the result that most of the computers connected to the internet are …

We extend prior research on system call anomaly detection modeling methods for intrusion
detection by incorporating dynamic window sizes. The window size is the length of the …

This paper presents a statistical anomaly detection algorithm based on Markov chains. Our
algorithm can be directly applied for intrusion detection by discovering anomalous activities …

A hybrid model based mostly on a high-order Markov chain and occasionally on a statistical-
independence model is proposed for profiling command sequences of a computer user in …

Immunology as information processing Page 381 Immunology as Information Processing
Stephanie Forrest Steven A. Hofmeyr 1 INTRODUCTION This chapter describes the behavior of …

This paper investigates the use of sequences of system calls for classifying intrusions and
faults induced by privileged processes in Unix. Classification is an essential capability for …

Intrusion detection systems help network administrators prepare for and deal with network
security attacks. These systems collect information from a variety of systems and network …

Intrusion detection is an essential component of computer security mechanisms. It requires
accurate and efficient analysis of a large amount of system and network audit data. It can …