Users are required to set passwords that are both complex and not included in leaked lists, with the recent increase in unauthorised access due to password list attacks. When password security is evaluated by the user, the burden on the user is large and impractical due to the increased size of the compromised password list. Therefore, there are methods to evaluate passwords on an external server, but there is a possibility that passwords may be compromised due to eavesdropping by the server administrator. In this paper, we propose, implement and evaluate an outsourcing password evaluation system using Intel SGX, which can prevent passwords from being eavesdropped.

Android applications are digitally signed using developers' signing keys. As each key is associated with a developer, it can be used to establish trust between applications published by the author (that is, apps signed with the same key are allowed to update themselves if package names are identical, or access each other's resources). However, if a digital signature is generated using a weak algorithm such as MD5, then apps signed with the corresponding key are exposed to several risks (such as hijacking apps with fake updates or granting permissions to a malicious app). In this work, we analyze several Android apps to identify the threats caused using weak algorithms. Our study uncovered the following findings: Of the more than one million apps collected from Google Play, 223 and 52,866 were digitally signed using the weak algorithms of 512-bit RSA key and MD5, respectively. We identified the causal mechanisms of generating certificates that employ weak algorithms, and that they can be attributed to app-building frameworks and online app-building services. Based on these findings, we provide guidelines for stakeholders of the Android app distribution ecosystem.

Users want to enjoy online services without sacrificing their security. Although there is a trade-off between the security of a service and its usability, the level of security required will differ depending on the user and the situation. To optimize the balance between security and usability, it can be customized for each user and each online transaction. Yet in order to do that, both users and service providers need to stipulate their security requirements. We have been working on a framework that provides security requirement classifications in multiple dimensions to help users identify and select their security requirements, and then apply these requirements to different dimensions. This paper shows how we implemented this framework and then evaluated it by conducting a user study along with our implementation. The study verifies that ordinary users without any particular technical knowledge prefer to clarify their security requirements using a taxonomy-based selection scheme (our scheme) as opposed to a free-form input scheme. It also discusses the coverage of pre-defined taxonomies and users' requirements. Through this study, we clarify the future direction of our research.