TY - GEN
T1 - A semi-Markov survivability evaluation model for intrusion tolerant database systems
AU - Wang, Alex Hai
AU - Yan, Su
AU - Liu, Peng
PY - 2010
Y1 - 2010
N2 - Survivability modeling and evaluation have gained increasing importance. Most existing models assume that the distributions for transitions between states are exponential. However, this assumption does not hold in many real cases. To address this problem, we propose a novel semi-Markov survivability evaluation model, which allows the transitions between states to follow nonexponential distributions. Novel quantitative measures are also proposed to characterize the capability of a resilient system in surviving intrusions. Model validation, which is possibly the most important step in the life cycle of model development, is largely overlooked in previous research. In this paper, a real intrusion tolerant database system ITDB is implemented to validate the proposed statespace models. Empirical experiments show that the semi-Markov model predicts the system behaviors with high accuracy. Furthermore, in this paper we evaluate the impact of intrinsic system deficiencies and attack behaviors on the survivability of intrusion tolerant database systems.
AB - Survivability modeling and evaluation have gained increasing importance. Most existing models assume that the distributions for transitions between states are exponential. However, this assumption does not hold in many real cases. To address this problem, we propose a novel semi-Markov survivability evaluation model, which allows the transitions between states to follow nonexponential distributions. Novel quantitative measures are also proposed to characterize the capability of a resilient system in surviving intrusions. Model validation, which is possibly the most important step in the life cycle of model development, is largely overlooked in previous research. In this paper, a real intrusion tolerant database system ITDB is implemented to validate the proposed statespace models. Empirical experiments show that the semi-Markov model predicts the system behaviors with high accuracy. Furthermore, in this paper we evaluate the impact of intrinsic system deficiencies and attack behaviors on the survivability of intrusion tolerant database systems.
UR - http://www.scopus.com/inward/record.url?scp=77952347700&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952347700&partnerID=8YFLogxK
U2 - 10.1109/ARES.2010.90
DO - 10.1109/ARES.2010.90
M3 - Conference contribution
AN - SCOPUS:77952347700
SN - 9780769539652
T3 - ARES 2010 - 5th International Conference on Availability, Reliability, and Security
SP - 104
EP - 111
BT - ARES 2010 - 5th International Conference on Availability, Reliability, and Security
T2 - 5th International Conference on Availability, Reliability, and Security, ARES 2010
Y2 - 15 February 2010 through 18 February 2010
ER -