Multisensor Real-Time Risk Assessment Using Continuous-Time Hidden Markov Models

Authors:
Kjetil Haslum;Andr Årnes
Affiliations:
Center for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491 Trondheim, Norway;Center for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491 Trondheim, Norway
Venue:
Computational Intelligence and Security
Year:
2007

Citing 3
Cited 0

A tutorial on hidden Markov models and selected applications in speech recognition

Readings in speech recognition
Real-time risk assessment with network sensors and intrusion detection systems

CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Using hidden markov models to evaluate the risks of intrusions

RAID'06 Proceedings of the 9th international conference on Recent Advances in Intrusion Detection

Quantified Score

Hi-index	0.00

Visualization

Abstract

The use of tools for monitoring the security state of assets in a network is an essential part of network management. Traditional risk assessment methodologies provide a framework for manually determining the risks of assets, and intrusion detection systems can provide alerts regarding security incidents, but these approaches do not provide a real-time high level overview of the risk level of assets. In this paper we further extend a previously proposed real-time risk assessment method to facilitate more flexible modeling with support for a wide range of sensors. Specifically, the paper develops a method for handling continuous-time sensor data and for determining a weighted aggregate of multisensor input.