Intrusion Tolerant Database System (ITDB) is a new paradigm for secure database systems that can detect intrusions, isolate attacks, contain damage, and assess and repair damage caused by intrusions. What makes ITDB superior to conventional secure approaches is that it has an ability to reconfigure. Thus, it can yield much more stabilized levels of trustworthiness under environmental changes. However, the reconfiguration faces the problem of finding the best system configuration out of a very large number of configuration sets and under multiple conflicting criteria, which is a NPhard problem. This study focuses on two aspects of addressing adaptation problems in ITDB. First, a rule-based mechanism and neuro-fuzzy technique are proposed to apply to the adaptation model. Second, this study examines the effects of the rule-based adaptive controller and the neuro-fuzzy adaptive controller on the adaptation. The purpose of this is to evaluate which of these techniques can yield higher stabilized levels of trustworthiness, data integrity, and data availability in the face of attacks.
Intrusion Tolerant Database System (ITDB) is a new paradigm for secure database systems that can detect intrusions, isolate attacks, contain damage, and assess and repair damage caused by intrusions. What makes ITDB superior to conventional secure approaches is that it has an ability to reconfigure. Thus, it can yield much more stabilized levels of trustworthiness under environmental changes. However, the reconfiguration faces the problem of finding the best system configuration out of a very large number of configuration sets and under multiple conflicting criteria, which is a NPhard problem. This study focuses on two aspects of addressing adaptation problems in ITDB. First, a rule-based mechanism and neuro-fuzzy technique are proposed to apply to the adaptation model. Second, this study examines the effects of the rule-based adaptive controller and the neuro-fuzzy adaptive controller on the adaptation. The purpose of this is to evaluate which of these techniques can yield higher stabilized levels of trustworthiness, data integrity, and data availability in the face of attacks.
Today's computer systems are running (mostly) one kind of operating system which makes it easy for a new virus to spread rapidly. The author Markus Unterleitner presents in this book the model and...
This thesis presents the case of dynamically and adaptively learning signatures for network intrusion detection using genetic based machine learning techniques. The two major criticisms of...
* Configuring an intrusion detection system (IDS) is very challenging, and if improperly configured an IDS is rendered ineffective
* Packed with real-world tips and practical techniques, this book...
Composite structures are most efficient in performance and production cost when combined with smart materials making them adaptable to changing operational conditions. The specific production...
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