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RFID (Radio Frequency Identification) computing devices in practical applications often suffer from their poor computing performance in terms of low task throughput (also known as task rate) due to scarce harvested power. For optimizing the task throughput, the basic idea is to choose an optimal processor clock frequency when executing a specific task ($e.g.$e.g., operate sensor) in order to maximize task execution rate. Existing methods are based on the common sense where the frequency and task throughput are directly proportional to each other, meaning that a higher frequency causes a higher task rate. In RFID-scale devices, however, we observe that the relationship between the frequency and task throughput overturns the common sense, in which if the device rises the frequency, the task throughput will increase first and then decrease due to intermittent task execution pattern on such devices. In this article, we present a systematic task throughput model to explain and formulate the non-monotonic relationship between the frequency and task throughput. Based on the throughput model, we further introduce dynamic optimal frequency scaling (DOFS) to calculate the optimal frequency for task execution and thus optimize the task throughput in the RFID-scale devices. The experimental results show that the task throughput can be improved by 45.8% on average compared to the existing best effort.

USB flash drives are widely employed for data storage including sensitive personal or business data. Current defense strategies to protect those data mainly focus on preventing data theft when a USB drive plugs into a host computer that is infected with malware. This paper reveals a threat - attackers can produce spy USB flash drives that are able to leak the stored data via covert wireless communication without triggering security defenses on host computers. In this paper, we present SpyUSB, a USB flash drive implanted with a backscatter-based data theft hardware to demonstrate the threat of covert data theft. SpyUSB collects data from the physical layer of the communication between the host computer and SpyUSB device, which is transparent to the security mechanisms on the host computer. SpyUSB leverages backscatter communication to create a covert wireless channel. Furthermore, we explore the opportunity of covert data theft when the SpyUSB device is disconnected from the host computer using a tiny energy reservoir. Our experiment shows that SpyUSB can achieve a transmission bandwidth of up to 1,600 kbps. After unplugged from a computer, it can maintain standby for over 6 hours or continuously transmit data for 1.9 hours.

The rapid development of IoT applications calls for re-configurable IoT devices that can easily extend new functionality on demand. However, in the current architecture, updating chip functions on the end device is highly coupled with the local microprocessor in both hardware and software aspects, leading to inadequate flexibility. In this paper, we propose LEGO, a lightweight architecture with chip-level plug-and-play capabilities for IoT end devices. To achieve this, we first decoupling the control over heterogeneous chips from end devices to the gateway, and design a novel Unified Chip Description Language (UCDL) to access various types of functional chips uniformly. To supporting chips plug-and-play, we design a novel signal converting circuit on end devices to generate all required underlying signals for chip control. We also design a layered instruction orchestrator and hierarchical scheduler to minimize transmission overhead. The results show that our LEGO system can respond to chips plug-and-play within 0.13 seconds, and the lightweight architecture could reduce 49%$\sim$∼61% of power consumption in practical scenarios compared with traditional IoT end devices that are controlled by a microprocessor. The lightweight and easy-to-deploy features of LEGO makes it helpful to reduce deployment cost, thus conducive to accelerating large-scale applications.