Reputation systems are helpful for our decision making when we have to deal with unfamiliar service providers. However, some of these systems do not preserve privacy of the users, e.g., rating from an individual is obviously shown. Therefore, users may provide dishonest feedback due to the fear of retaliation. Although, some privacy-preserving reputation systems are proposed in the literature, most of them cannot withstand some specific attacks. These attacks include "dishonest queries to similar sets of users" and "collusion between the dishonest querier and all-but-one users". As a result, rating from an individual may be leaked.As the contribution of this work, we propose a novel privacy-preserving reputation system that addresses the aforementioned attacks. The idea is that, the querier firstly specifies a set of users, then the average rating is computed from a random subset of that set. Since the members of the random subset are not known to anyone, the attacks become difficult. We construct our scheme based on a secret sharing technique, specifically ABY3 framework (Mohassel and Rindal, CCS’18) that supports conversion between different data representations. Correctness, security, privacy, and complexity are then discussed, and possible improvements are also suggested. The experiments show that the accuracy of our scheme is similar to the case where privacy is not preserved.

Social networking services (SNS) are often the subject of privacy concerns. Hence users should be careful not to post content with unacceptable privacy risks. In order to correctly determine whether a privacy risk is acceptable, the perceived privacy risk must match the actual privacy risk. One of the objectives of this study is to investigate whether the recognition of privacy risk is consistent with the actual privacy risk. This study investigates the posters ’recognition of privacy risk from postings that infer their attributes and regrets about their actions. On the other hand, privacy information can also be leaked from other people’s posts, to which people respond with "Liking" or "Retweeting." Existing methods for analyzing their posts to suppress their posts may not be effective if personal information is leaked from the responses to the contents of others’ posts. In addition, users may be less likely to perceive the risk of privacy information leakage from responses to the contents of others ’ posts than from their posts. Therefore, this study tests the hypothesis that there is a difference between the users’ recognition of privacy risk in posting by themselves and that caused by responding to contents of others’ posts and evaluates the difficulty of recognizing privacy risk caused by responding compared with that by posting.

As one of the scales which assess the end-user’s security behavior, the security behavior stage model (SeBeST) [1] is a practical approach to characterize similar groups of users (precontemplation, contemplation, preparation, action and maintenance stages) and provide customized remedies to improve their security behavior. For example, in OS update message customization, a group that does not update OS continuously may require a message indicating the ease of OS update; on the other hand, updating users need a message indicating the importance of OS update. In this paper, we propose a personalized OS update message interface based on SeBeST. We conduct two online surveys to evaluate effective appearance and message as the personalized user interface (UI). First, we assess the interface’s appearance individually for the three behavior stages (preparation, action, and maintenance) and then combine the customized messages and the selected impressions for these stages. We confirmed that appropriate appearances are different for each stage. For example, a highlighted red button is efficient for users in the preparation stage. On the other hand, the red background is suitable for users of the action and maintenance stages. We discovered that the combination of the message indicating the disadvantage of the OS update and the UI which is the highlighted red button is suitable for the preparation and action stages. In addition, we confirmed the best combination for users of the maintenance stage is a message indicating the ease of OS update and the UI which is mouse over pop-up representation. Therefore, it is necessary for each user to show the appropriate message and UI.

Seventy percent of smartphone applications employ third party libraries for advertisement and usage analysis. Because the host application and those third party libraries have to be packed into one application package, they share the same set of privileges. This worries users because of the concern that third party libraries might abuse the host application's privileges. This is not a desirable situation for application developers, either, because they are forced to add privileges for advertising libraries that are not necessary for their application, and users tend to avoid applications with sensitive privileges. Although advertising libraries are generally not welcomed by users, mobile advertisements play a key role in a mobile application eco-system that promotes the popularity of free applications. Therefore, we need a solution that will not hamper a mobile advertising agency service while addressing the concerns of users and developers. In this paper, we designed SanAdBox, a privilege separation framework for Android applications and a third party library that will not interfere with the behavior of third party libraries. In SanAdBox, each third party library is installed as an independent application so that it runs in a separate sandbox. In this way, the privileges of applications and libraries are strictly separated, solving the above-mentioned problems. Furthermore, because SanAdBox does not require modification of the Android operating system, we can install it on smartphones with the normal Android operating system.

Monitoring a process and its file I/O behaviors is important for security inspection for a data center server against intrusions, malware infection and information leakage. In the case of the Linux kernel 2.6, a set of hook functions called the Linux Security Module (LSM) has been implemented in order to monitor and control the system calls. By using the LSM we can inspect the activity of unknown malicious processes. However, a sophisticated attacker could breach the kernel configurations using the rootkits. Furthermore since the monitoring results of the malicious process activity are stored as a file on Hard Disk Drive (HDD), it will be easily manipulated by the attacker. In this paper, we propose a secure monitoring scheme that addresses the attacks against the monitoring module and its result for security inspection of the data center server. The monitoring module is implemented as a LSM-based function and protected by the kernel protection technique. The integrity of the monitoring result is guaranteed by using a Mandatory Access Control (MAC) of the Linux kernel and a mechanism of the trusted process invocation. This mechanism can serve as an infrastrucuture of secure inspection platform for data center server because the integrity of the monitoring module and its result is guaranteed.