It is frequently reported that large volumes of secret data stored online, such as passwords and PINs, leak out. Since most of these incidents resulted from potential vulnerabilities, such as human error, bugs and intentional misconduct, it was not easy to eliminate the underlying causes. In this paper, we focus on the concept of functional safety where the goal is to ensure that systems work correctly in a worst case scenario, such as in the situations referred to above. Our goal is to minimize the impact of information leakage. In this paper, we first present some metrics for evaluating the security of a cloud system where the secret data of several users have been compromised. We also propose a partitioning method to store secret data on the cloud system more securely, thereby making it possible to diminish the impact on the secret data of other users.
['Seira Hidano', 'Shinsaku Kiyomoto']
On Partitioning Secret Data Based on Concept of Functional Safety