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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.