A Stochastic Model for Quantitative Security Analyses of Networked Systems

Traditional security analyses are often geared toward cryptographic primitives or protocols. Although such analyses are necessary, they cannot address a defender's need for insight into which aspects of a networked system having a significant impact on its security, and how to tune its configur...

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Veröffentlicht in:IEEE transactions on dependable and secure computing 2011-01, Vol.8 (1), p.28-43
Hauptverfasser: Xiaohu Li, Parker, P, Shouhuai Xu
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Parker, P
Shouhuai Xu
description Traditional security analyses are often geared toward cryptographic primitives or protocols. Although such analyses are necessary, they cannot address a defender's need for insight into which aspects of a networked system having a significant impact on its security, and how to tune its configurations or parameters so as to improve security. This question is known to be notoriously difficult to answer, and the state of the art is that we know little about it. Toward ultimately addressing this question, this paper presents a stochastic model for quantifying security of networked systems. The resulting model captures two aspects of a networked system: (1) the strength of deployed security mechanisms such as intrusion detection systems and (2) the underlying vulnerability graph, which reflects how attacks may proceed. The resulting model brings the following insights: (1) How should a defender "tune" system configurations (e.g., network topology) so as to improve security? (2) How should a defender "tune" system parameters (e.g., by upgrading which security mechanisms) so as to improve security? (3) Under what conditions is the steady-state number of compromised entities of interest below a given threshold with a high probability? Simulation studies are conducted to confirm the analytic results, and to show the tightness of the bounds of certain important metric that cannot be resolved analytically.
doi_str_mv 10.1109/TDSC.2008.75
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Although such analyses are necessary, they cannot address a defender's need for insight into which aspects of a networked system having a significant impact on its security, and how to tune its configurations or parameters so as to improve security. This question is known to be notoriously difficult to answer, and the state of the art is that we know little about it. Toward ultimately addressing this question, this paper presents a stochastic model for quantifying security of networked systems. The resulting model captures two aspects of a networked system: (1) the strength of deployed security mechanisms such as intrusion detection systems and (2) the underlying vulnerability graph, which reflects how attacks may proceed. The resulting model brings the following insights: (1) How should a defender "tune" system configurations (e.g., network topology) so as to improve security? (2) How should a defender "tune" system parameters (e.g., by upgrading which security mechanisms) so as to improve security? (3) Under what conditions is the steady-state number of compromised entities of interest below a given threshold with a high probability? 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(2) How should a defender "tune" system parameters (e.g., by upgrading which security mechanisms) so as to improve security? (3) Under what conditions is the steady-state number of compromised entities of interest below a given threshold with a high probability? Simulation studies are conducted to confirm the analytic results, and to show the tightness of the bounds of certain important metric that cannot be resolved analytically.</abstract><cop>Washington</cop><pub>IEEE</pub><doi>10.1109/TDSC.2008.75</doi><tpages>16</tpages></addata></record>
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subjects Analytical models
Authentication
Computer networks
Computer science
Courthouses
Cryptographic protocols
Cryptography
Digital Object Identifier
Exploitation
Graphs
Intrusion
Intrusion detection
Intrusion detection systems
Mathematical analysis
Mathematical models
Network security
Network topology
networked systems
quantitative security analysis
Random variables
Security
security metric
Security modeling
Simulation
Steady-state
Stochastic models
Stochastic systems
Stochasticity
Studies
Tightness
Upgrading
vulnerability graph
title A Stochastic Model for Quantitative Security Analyses of Networked Systems
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