Dynamic revocation of permissions of installed Android applications has been gaining popularity, because of the increasing concern of security and privacy in the Android platform. However, applications often crash or misbehave when their permissions are revoked, rendering applications completely unusable. Even though Google has officially introduced the new permission mechanism in Android 6.0 to explicitly support dynamic permission revocation, the issue still exists. In this paper, we conduct an empirical study to understand the latest application practice post Android 6.0. Specifically, we design a practical tool, referred to as revDroid, to help us to empirically analyze how often the undesirable side effects, especially application crash, can occur in off-the-shelf Android applications. From the analysis of 248 popular applications from Google Play Store, revDroid finds out that 70% applications and 46% permission-relevant calls do not appropriately catch exceptions caused by permission revocation, while third-party libraries pay much more attention to permission revocation. We also use revDroid to analyze 132 recent malware samples. The result shows that only 27% malwares and 36% permission-relevant API calls of malwares fail to consider the permission revocation. In fact, many of them perform specialized handling of permission revocation to keep the core malicious logic running. Finally, revDroid can be used to help developers uncover the unhandled permission revocations during development time and greatly improve the application quality.

More and more powerful personal smart devices take users, especially the elder, into a disaster of policy administration where users are forced to set personal management policies in these devices. Considering a real case of this issue in the Android security, it is hard for users, even some programmers, to generally identify malicious permission requests when they install a third-party application. Motivated by the popularity of mutual assistance among friends (including family members) in the real world, we propose a novel framework for policy administration, referring to Socialized Policy Administration (SPA for short), to help users manage the policies in widely deployed personal devices. SPA leverages a basic idea that a user may invite his or her friends to help set the applications. Especially, when the size of invited friends increases, the setting result can be more resilient to a few malicious or unprofessional friends. We define the security properties of SPA, and propose an enforcement framework where users' friends can help users set applications without the leakage of friends' preferences with the supports of a privacy preserving mechanism. In our prototype, we only leverage partially homomorphic encryption cryptosystems to implement our framework, because the fully homomorphic encryption is not acceptable to be deployed in a practical service at the moment. Based on our prototype and performance evaluation, SPA is promising to support major types of policies in current popular applications with acceptable performance.

With the support of the Internet of Things (IoT for short) technologies, tracking systems are being widely deployed in many companies and organizations in order to provide more efficient and trustworthy delivery services. Such systems usually support easy-to-use interfaces, by which users can visualize the shipping status and progress of merchandise, according to business data which are collected directly from the merchandise through sensing technologies. However, these business data may include sensitive business information, which should be strongly protected in cross-organizational scenarios. Thus, it is critical for suppliers that the disclosure of such data to unauthorized users is prevented in the context of the open environment of these tracking systems. As business data from different suppliers and organizations are usually associated together with merchandise being shipped, it is also important to support fine-grained confidentiality control. In this paper, we articulate the problem of fine-grained business data confidentiality control in IoT-enabled cross-organizational tracking systems. We then propose a fine-grained confidentiality control mechanism, referred to as xCP-ABE, to address the problem in the context of open environment. The xCP-ABE mechanism is a novel framework which makes suppliers in tracking systems able to selectively authorize specific sets of users to access their sensitive business data and satisfies the confidentiality of transmission path of goods. We develop a prototype of the xCP-ABE mechanism, and then evaluate its performance. We also carry out a brief security analysis of our proposed mechanism. Our evaluation and analysis show that our framework is an effective and efficient solution to ensure the confidentiality of business data in cross-organizational tracking systems.