74 research outputs found

    e-SAFE: Secure, Efficient and Forensics-Enabled Access to Implantable Medical Devices

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    To facilitate monitoring and management, modern Implantable Medical Devices (IMDs) are often equipped with wireless capabilities, which raise the risk of malicious access to IMDs. Although schemes are proposed to secure the IMD access, some issues are still open. First, pre-sharing a long-term key between a patient's IMD and a doctor's programmer is vulnerable since once the doctor's programmer is compromised, all of her patients suffer; establishing a temporary key by leveraging proximity gets rid of pre-shared keys, but as the approach lacks real authentication, it can be exploited by nearby adversaries or through man-in-the-middle attacks. Second, while prolonging the lifetime of IMDs is one of the most important design goals, few schemes explore to lower the communication and computation overhead all at once. Finally, how to safely record the commands issued by doctors for the purpose of forensics, which can be the last measure to protect the patients' rights, is commonly omitted in the existing literature. Motivated by these important yet open problems, we propose an innovative scheme e-SAFE, which significantly improves security and safety, reduces the communication overhead and enables IMD-access forensics. We present a novel lightweight compressive sensing based encryption algorithm to encrypt and compress the IMD data simultaneously, reducing the data transmission overhead by over 50% while ensuring high data confidentiality and usability. Furthermore, we provide a suite of protocols regarding device pairing, dual-factor authentication, and accountability-enabled access. The security analysis and performance evaluation show the validity and efficiency of the proposed scheme

    Intelligent Perception Control System of Railway Level Crossing Gate Based on TRIZ Theory

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    TRIZ theory is an innovative method to analyse problems and solve them, which is widely used in many fields. In this paper, TRIZ theory is used to improve the design of railway crossing guardrail system. The use of nine-screen analysis, functional analysis, cause-effect chain analysis and other tools to analyse the problem of poor manual control effect in the railway crossing guardrail system, the use of technical contradictions, physical contradictions and other tools to improve the system design, effectively reduce the possibility of danger when cars and pedestrians cross railway crossings, improve the traffic safety and traffic order of the railway level crossing, and reduce the work burden of railway crossing caretakers

    KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view Stereo

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    Supervised multi-view stereo (MVS) methods have achieved remarkable progress in terms of reconstruction quality, but suffer from the challenge of collecting large-scale ground-truth depth. In this paper, we propose a novel self-supervised training pipeline for MVS based on knowledge distillation, termed KD-MVS, which mainly consists of self-supervised teacher training and distillation-based student training. Specifically, the teacher model is trained in a self-supervised fashion using both photometric and featuremetric consistency. Then we distill the knowledge of the teacher model to the student model through probabilistic knowledge transferring. With the supervision of validated knowledge, the student model is able to outperform its teacher by a large margin. Extensive experiments performed on multiple datasets show our method can even outperform supervised methods

    Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study

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    The combination of smart home platforms and automation apps introduces much convenience to smart home users. However, this also brings the potential for privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which altogether forms a Filter-and-Fuzz (F&F) process: first, it filters out events unneeded by the IFTTT platform; then, it fuzzes the values and frequencies of the remaining events. We evaluate the F&F process, and the results show that the proposed solution makes IFTTT unable to recognize any of the user's behavior patterns

    Weight-dependent Gates for Differentiable Neural Network Pruning

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    In this paper, we propose a simple and effective network pruning framework, which introduces novel weight-dependent gates to prune filter adaptively. We argue that the pruning decision should depend on the convolutional weights, in other words, it should be a learnable function of filter weights. We thus construct the weight-dependent gates (W-Gates) to learn the information from filter weights and obtain binary filter gates to prune or keep the filters automatically. To prune the network under hardware constraint, we train a Latency Predict Net (LPNet) to estimate the hardware latency of candidate pruned networks. Based on the proposed LPNet, we can optimize W-Gates and the pruning ratio of each layer under latency constraint. The whole framework is differentiable and can be optimized by gradient-based method to achieve a compact network with better trade-off between accuracy and efficiency. We have demonstrated the effectiveness of our method on Resnet34, Resnet50 and MobileNet V2, achieving up to 1.33/1.28/1.1 higher Top-1 accuracy with lower hardware latency on ImageNet. Compared with state-of-the-art pruning methods, our method achieves superior performance.Comment: ECCV worksho

    Current-driven magnetization dynamics and their correlation with magnetization configurations in perpendicularly magnetized tunnel junctions

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    We study spin-transfer-torque driven magnetization dynamics of a perpendicular magnetic tunnel junction (MTJ) nanopillar. Based on the combination of spin-torque ferromagnetic resonance and microwave spectroscopy techniques, we demonstrate that the free layer (FL) and the weak pinned reference layer (RL) exhibit distinct dynamic behaviors with opposite frequency vs. field dispersion relations. The FL can support a single coherent spin-wave (SW) mode for both parallel and antiparallel configurations, while the RL exhibits spin-wave excitation only for the antiparallel state. These two SW modes corresponding to the FL and RL coexist at an antiparallel state and exhibit a crossover phenomenon of oscillation frequency with increasing the external magnetic field, which could be helpful in the mutual synchronization of auto-oscillations for SW-based neuromorphic computing.Comment: 13 pages, 5 figure

    Antiviral signaling by a cyclic nucleotide activated CRISPR protease

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    Funding information: M.G. and J.L.S.B. are funded by the Deutsche Forschungsgemeinschaft under Germany’s Excellence Strategy–EXC2151–390873048. M.F.W. acknowledges a European Research Council Advanced Grant (grant number 101018608) and the China Scholarship Council (REF: 202008420207 to H.C.). G.H. is grateful for funding by the Deutsche Forschungsgemeinschaft (grant number HA6805/6-1).CRISPR defense systems such as the well-known DNA-targeting Cas9 and the RNA-targeting type III systems are widespread in prokaryotes1,2. The latter can orchestrate a complex antiviral response that is initiated by the synthesis of cyclic oligoadenylates (cOAs) upon foreign RNA recognition3-5. Among a large set of proteins that were linked to type III systems and predicted to bind cOAs6,7, a CRISPR associated Lon protease (CalpL) stood out to us. The protein contains a sensor domain of the SAVED (SMODS-associated and fused to various effector domains) family7, fused to a Lon protease effector domain. However, the mode of action of this effector was unknown. Here, we report the structure and function of CalpL and show that the soluble protein forms a stable tripartite complex with two further proteins, CalpT and CalpS, that are encoded in the same operon. Upon activation by cA4, CalpL oligomerizes and specifically cleaves the MazF-homolog CalpT, releasing the extracytoplasmic function (ECF) sigma factor CalpS from the complex. This provides a direct connection between CRISPR-based foreign nucleic acid detection and transcriptional regulation. Furthermore, the presence of a cA4-binding SAVED domain in a CRISPR effector reveals an unexpected link to the cyclic oligonucleotide-based antiphage signaling system (CBASS).PostprintPeer reviewe
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