Accurate recovery from a cyber attack depends on fast and perfect damage as
sessment. For damage assessment, traditional recovery methods require that
the log of an affected database must be scanned starting from the attacking
transaction until the end. This is a time- consuming task. Our objective i
n this research is to provide techniques that can be used to accelerate dam
age appraisal process and produce correct result. In this paper, we have pr
esented a damage assessment model and four data structures associated with
the model. Each of these structures uses dependency relationships among tra
nsactions, which update the database. These relationships are later used to
determine exactly which transactions and exactly which data items are affe
cted by the attacker. A performance comparison analysis obtained using simu
lation is provided to demonstrate the benefit of our model.