The emerging, overclocking signal‐based acoustic covert communication technique allows smart devices to communicate (without users’ consent) utilizing their microphones and speakers in ultrasonic side channels, which offers users imperceptible and convenient personalized services, e.g., cross‐device authentication and media tracking. However, microphones and speakers could be maliciously used and pose severe privacy threats to users. In this paper, we propose a novel high‐frequency filtering‐ (HFF‐) based protection model, named UltraFilter, which protects user privacy by enabling users to selectively filter out high‐frequency signals from the metadata received by the device. We also analyze the feasibility of using audio frequencies (i.e., ≤18 kHz) to the acoustic covert communication and carry out the acoustic covert communication system by introducing the auditory masking effect. Experiments show that UltraFilter can prevent users’ private information from leaking and reduce system load and that the audio frequencies can pose threats to user privacy.

No abstract available.

In some special circumstances, e.g. tsunamis, floods, battlefields, earthquakes, etc., communication infrastructures are damaged or non-existent, as well as unmanned aerial vehicle (UAV) cluster. For the communication between people or UAVs, UAVs or mobile smart devices (MSDs) can be used to construct Mobile Ad Hoc Networks (MANETs), and Multipath TCP (MPTCP) can be used to simultaneously transmit in one TCP connection via multiple interfaces of MSDs. However the original MPTCP subpaths creating algorithm can establish multiple subpaths between two adjacent nodes, thus cannot achieve true concurrent data transmission. To solve this issue, we research and improve both the algorithm of adding routing table entries and the algorithm of establishing subpaths to offer more efficient use of multiple subpaths and better network traffic load balancing. The main works are as follows: (1) improve multi-hop routing protocol; (2) run MPTCP on UAVs or MSDs; (3) improve MPTCP subpaths establishment algorithm. The results show that our algorithms have better performance than the original MPTCP in achieving higher data throughput.

In some special circumstances, e.g. tsunamis, floods, battlefields, earthquakes, etc., communication infrastructures are damaged or non-existent, as well as unmanned aerial vehicle (UAV) cluster. For the communication between people or UAVs, UAVs or mobile smart devices (MSDs) can be used to construct Mobile Ad Hoc Networks (MANETs), and Multipath TCP (MPTCP) can be used to simultaneously transmit in one TCP connection via multiple interfaces of MSDs. However the original MPTCP subpaths creating algorithm can establish multiple subpaths between two adjacent nodes, thus cannot achieve true concurrent data transmission. To solve this issue, we research and improve both the algorithm of adding routing table entries and the algorithm of establishing subpaths to offer more efficient use of multiple subpaths and better network traffic load balancing. The main works are as follows: (1) improve multi-hop routing protocol; (2) run MPTCP on UAVs or MSDs; (3) improve MPTCP subpaths establishment algorithm. The results show that our algorithms have better performance than the original MPTCP in achieving higher data throughput.

As the dominant mobile operating system in the markets of smartphones, Android platform is increasingly targeted by attackers. Besides, attackers often produce novel malware to bypass the conventional detection approaches, which are largely reliant on expert analysis to design the discriminative features manually. Therefore, more effective and easy-to-use approaches for detection of Android malware are in demand. In this paper, we design and implement EasyDefense, a lightweight defense system that is integrated with Android OS for easy and effective detection of Android malware utilizing machine learning methods and the ensemble of them. Besides universal static features such as permissions and API calls, EasyDefense also employs the N-gram features of operation codes (opcodes). These N-gram features are extracted and learnt automatically from raw data of applications. Experimental results on 204,650 applications show that users can easily and effectively protect the privacy and security on their smartphones through this system.

Currently, the smartphone has become an essential communication and amusement tool, which has strong computing power and a variety of functions. Especially, the market share of smartphone with android system account for 84% in 2016[1]. Under android system, a large of privacy data (e.g. photos or videos) are stored in external storage (emulated Sdcard storage), which can be accessed by installed apps. This not only results in privacy leakage but also incurs ransomware attack[2] (e.g. simplocker). Therefore, we present Sdguard, an app, can implement fine-grain permission control based on Linux DAC mechanism and detect ransomware which encrypts content of file stored in external storage or lock user screen. To install Sdguard app, we need to ensure that the smartphone has been rooted and use FUSE filesystem on external storage. During installing, sdcard daemon of android (i.e. FUSE daemon) is replaced by our customized sdcard daemon. After rebooting system, the customized daemon is loaded, and each component of Sdguard is running.

Applications in Android often have the ability of accessing sensitive resources on mobile devices. These resources have different levels of security and usage constraint in scenarios which have different requirements for privacy. Therefore, it is in demand for users to have fine-grained privacy protection and resources usage constraint that taking the context information into account, which is not supported by inherent access control mechanism of Android. To address these issues, we designed and implemented an enhanced context-aware adaptive access control system (EasyGuard) in Android to provide adaptive access control automatically when the specific context is detected according to the pre-configured policies. In addition, we developed an application to facilitate users that have little domain knowledge in android to configure policies reasonably. Experimental results show that users can easily protect their privacy, security and save energy of mobile devices through this system.