The Internet of Things (IoT) is an industry-recognized next intelligent life solution that increases the level of comfort, efficiency, and automation for citizens through numerous sensors, smart devices, and cloud stations connected physically. As an important application scenario of IoT, the Internet of Vehicles (IoV) plays an extremely critical role in the intelligent transportation field. In fact, the In-Vehicle Network of smart vehicles that are recognized as the core roles in intelligent transportation is currently the Controller Area Network (CAN). However, the In-Vehicle CAN bus protocol has several vulnerabilities without any encryption, authentication, or integrity checking, which severely threatens the safety of drivers and passengers. Once malicious attackers hack the vehicular gateway and obtain the access right of the CAN, they may control the vehicle based on the vulnerabilities of the CAN bus protocol. Given the severe security risk of CAN, we proposed the CANsec, a practical In-Vehicle CAN security evaluation tool that simulates malicious attacks according to major attack models to evaluate the security risk of the In-Vehicle CAN. We also show a usage case of the CANsec without knowing any information from the vehicle manufacturer.
NAND flash memory is widely used in communications, commercial servers, and cloud storage devices with a series of advantages such as high density, low cost, high speed, anti-magnetic, and anti-vibration. However, the reliability is increasingly getting worse while process improvements and technological advancements have brought higher storage densities to NAND flash memory. The degradation of reliability not only reduces the lifetime of the NAND flash memory but also causes the devices to be replaced prematurely based on the nominal value far below the minimum actual value, resulting in a great waste of lifetime. Using machine learning algorithms to accurately predict endurance levels can optimize wear-leveling strategies and warn bad memory blocks, which is of great significance for effectively extending the lifetime of NAND flash memory devices and avoiding serious losses caused by sudden failures. In this work, a multi-class endurance prediction scheme based on the SVM algorithm is proposed, which can predict the remaining P-E cycle level and the raw bit error level after various P-E cycles. Feature analysis based on endurance data is used to determine the basic elements of the model. Based on the error features, we present a variety of targeted optimization strategies, such as extracting the numerical features closely related to the endurance, and reducing the noise interference of transient faults through short-term repeated operations. Besides a high-parallel flash test platform supporting multiple protocols, a feature preprocessing module is constructed based on the ZYNQ-7030 chip. The pipelined module of SVM decision model can complete a single prediction within 37 us.
The Short-range-controlled communication system (RCC) based on a subscriber identity module (SIM) card is a replacement for the standard near-field communication (NFC) system to support near-field payment applications. The RCC uses both the low-frequency (LF) and high-frequency (HF) wireless communication system. The RCC communication distance is controlled under 10 cm. However, current RCCs suffer from compatibility issues, and the LF communication distance is lower than 0.5 cm in some phones with completely metallic shells. In this paper, we propose an improved LF communication system design, including an LF transmitter circuit, LF receiver chip, and LF-HF communication protocol. The LF receiver chip has a rail-to-rail amplifier and a self-correcting clock recovery differential Manchester decoder, which do not have the limitations of accurate gain and high system clock. The LF receiver chip is fabricated in a 0.18 μm CMOS technology platform, with a die size of 1.05 mm × 0.9 mm and current consumption of 41 μA. The experiments show that the improved RCC has better compatibility, and the communication distance reaches to 4.2 cm in phones with completely metallic shells.
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