Decision support system for zero-day attack response

Regardless of the existence of the various information security safeguards, many companies remain vulnerable to the unknown attack, which is known as the zero-day attack. In this study, we develop the decision support system (DSS) using case-based reasoning (CBR) for zero-day attack response. Also, our proposed system divides the unknown attack into atomic attacks for zeroday attack detection. Then, this proposed system analyzes the similarity between the new zero-day attack pattern and the known attack patterns. Finally, it suggests the most similar cases with applying similarity functions and CBR. The effectiveness of our system is further shown in the empirical test.