FuncTeller: How Well Does eFPGA Hide Functionality?

Hardware intellectual property (IP) piracy is an emerging threat to the global supply chain. Correspondingly, various countermeasures aim to protect hardware IPs, such as logic locking, camouflaging, and split manufacturing. However, these countermeasures cannot always guarantee IP security. A malicious attacker can access the layout/netlist of the hardware IP protected by these countermeasures and further retrieve the design. To eliminate/bypass these vulnerabilities, a recent approach redacts the design's IP to an embedded field-programmable gate array (eFPGA), disabling the attacker's access to the layout/netlist. eFPGAs can be programmed with arbitrary functionality. Without the bitstream, the attacker cannot recover the functionality of the protected IP. Consequently, state-of-the-art attacks are inapplicable to pirate the redacted hardware IP. In this paper, we challenge the assumed security of eFPGA-based redaction. We present an attack to retrieve the hardware IP with only black-box access to a programmed eFPGA. We observe the effect of modern electronic design automation (EDA) tools on practical hardware circuits and leverage the observation to guide our attack. Thus, our proposed method FuncTeller selects minterms to query, recovering the circuit function within a reasonable time. We demonstrate the effectiveness and efficiency of FuncTeller on multiple circuits, including academic benchmark circuits, Stanford MIPS processor, IBEX processor, Common Evaluation Platform GPS, and Cybersecurity Awareness Worldwide competition circuits. Our results show that FuncTeller achieves an average accuracy greater than 85% over these tested circuits retrieving the design's functionality.Comment: To be published in the proceedings of the 32st USENIX Security Symposium, 202

A Nomogram to Predict Patients with Obstructive Coronary Artery Disease: Development and Validation

Objective: To develop and validate clinical prediction models for the development of a nomogram to estimate the probability of patients having coronary artery disease (CAD). Methods and Results: A total of 1,025 patients referred for coronary angiography were included in a retrospective, single-center study. Randomly, 720 patients (70%) were selected as the development group and the other patients were selected as the validation group. Multivariate logistic regression analysis showed that the seven risk factors age, sex, systolic blood pressure, lipoprotein-associated phospholipase A 2, type of angina, hypertension, and diabetes were significant for diagnosis of CAD, from which we established model A. We established model B with the risk factors age, sex, height, systolic blood pressure, low-density lipoprotein cholesterol, lipoprotein-associated phospholipase A 2, type of angina, hypertension, and diabetes via the Akaike information criterion. The risk factors from the original Framingham Risk Score were used for model C. From comparison of the areas under the receiver operating characteristic curve, net reclassification improvement, and integrated discrimination improvement of models A, B, and C, we chose model B to develop the nomogram because of its fitness in discrimination, calibration, and clinical efficiency. The nomogram for diagnosis of CAD could be used easily and conveniently. Conclusion: An individualized clinical prediction model for patients with CAD allowed an accurate estimation in Chinese populations. The Akaike information criterion is a better method in screening risk factors. The net reclassification improvement and integrated discrimination improvement are better than the area under the receiver operating characteristic curve in discrimination. Decision curve analysis can be used to evaluate the efficiency of clinical prediction models. </p

Multifunctional, durable and highly conductive graphene/sponge nanocomposites

Porous functional materials play important roles in a wide variety of growing research and industrial fields. We herein report a simple, effective method to prepare porous functional graphene composites for multi-field applications. Graphene sheets were non-chemically modified by Triton®X-100, not only to maintain high structural integrity but to improve the dispersion of graphene on the pore surface of a sponge. It was found that a graphene/sponge nanocomposite at 0.79 wt.% demonstrated ideal electrical conductivity. The composite materials have high strain sensitivity, stable fatigue performance for 20,000 cycles, short response time of 0.401s and fast response to temperature and pressure. In addition, the composites are effective in monitoring materials deformation and acoustic attenuation with a maximum absorption rate 67.78% and it can be used as electrodes for a supercapacitor with capacitance of 18.1 F/g. Moreover, no expensive materials or complex equipment are required for the composite manufacturing process. This new methodology for the fabrication of multifunctional, durable and highly conductive graphene/sponge nanocomposites hold promise for many other applications

Enhancing the Performance of Transformer-based Spiking Neural Networks by Improved Downsampling with Precise Gradient Backpropagation

Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven property. However, state-of-the-art deep SNNs (including Spikformer and Spikingformer) suffer from a critical challenge related to the imprecise gradient backpropagation. This problem arises from the improper design of downsampling modules in these networks, and greatly hampering the overall model performance. In this paper, we propose ConvBN-MaxPooling-LIF (CML), an improved downsampling with precise gradient backpropagation. We prove that CML can effectively overcome the imprecision of gradient backpropagation from a theoretical perspective. In addition, we evaluate CML on ImageNet, CIFAR10, CIFAR100, CIFAR10-DVS, DVS128-Gesture datasets, and show state-of-the-art performance on all these datasets with significantly enhanced performances compared with Spikingformer. For instance, our model achieves 77.64 $\%$ on ImageNet, 96.04 $\%$ on CIFAR10, 81.4$\%$ on CIFAR10-DVS, with + 1.79$\%$ on ImageNet, +1.54$\%$ on CIFAR100 compared with Spikingformer.Comment: 12 page

Review of the Status and Prospects of Fiber Optic Hydrogen Sensing Technology

With the unprecedented development of green and renewable energy sources, the proportion of clean hydrogen (H2) applications grows rapidly. Since H2 has physicochemical properties of being highly permeable and combustible, high-performance H2 sensors to detect and monitor hydrogen concentration are essential. This review discusses a variety of fiber-optic-based H2 sensor technologies since the year 1984, including: interferometer technology, fiber grating technology, surface plasma resonance (SPR) technology, micro lens technology, evanescent field technology, integrated optical waveguide technology, direct transmission/reflection detection technology, etc. These technologies have been evolving from simply pursuing high sensitivity and low detection limits (LDL) to focusing on multiple performance parameters to match various application demands, such as: high temperature resistance, fast response speed, fast recovery speed, large concentration range, low cross sensitivity, excellent long-term stability, etc. On the basis of palladium (Pd)-sensitive material, alloy metals, catalysts, or nanoparticles are proposed to improve the performance of fiber-optic-based H2 sensors, including gold (Au), silver (Ag), platinum (Pt), zinc oxide (ZnO), titanium oxide (TiO2), tungsten oxide (WO3), Mg70Ti30, polydimethylsiloxane (PDMS), graphene oxide (GO), etc. Various microstructure processes of the side and end of optical fiber H2 sensors are also discussed in this review

Gallic Acid Accelerates the Oxidation Ability of the Peracetic Acid/Fe(III) System for Bisphenol A Removal: Fate of Various Radicals

Conveniently and cost-effectively obtained Fe(III) can be utilized for peracetic acid (PAA) activation in the presence of natural polyphenols. However, the effect of polyphenols on the fate of generated reactive oxygen species (ROS) remains unclear. In this study, it was demonstrated that Fe(III) can efficiently trigger PAA oxidation of pollutants with the assistance of gallic acid (GA), a widely distributed natural polyphenol. The GA/Fe(III)/PAA system efficiently removed bisphenol A (BPA) over a wide initial pH range of 4.0–7.0, with a removal rate of >90% over 20 min. Further, •OH played a dominant role in BPA degradation, and O2•– functioned as an intermediate contributing to the partial generation of •OH. The generated organic radicals (R-O•) did not considerably contribute to BPA removal. Apart from GA itself, both the reaction intermediates (phenoxy radicals) of GA with ROS and BPA degradation intermediates were crucial for the regeneration of Fe(II) from Fe(III) and the subsequent enhanced activation of PAA. Notably, further comprehensive analysis revealed an increase in •OH yield, but a decrease in R-O• production as the dosage of GA was increased from 10 to 100 μM. This finding emphasized the importance of properly utilizing GA, considering the reactivity of varied ROS toward different contaminants. R-O• (CH3CO2• and CH3CO3•) was quickly consumed by the GA-Fe(II) complex through single-electron transfer (SET) and/or by GA via H-abstraction (HAA). This study proposes a promising strategy for improving the Fe(III)/PAA process and advances the understanding of the trade-off between radical generation and elimination by polyphenols in PAA-based advanced oxidation processes (AOPs)