Visually Adversarial Attacks and Defenses in the Physical World: A Survey

Although Deep Neural Networks (DNNs) have been widely applied in various real-world scenarios, they are vulnerable to adversarial examples. The current adversarial attacks in computer vision can be divided into digital attacks and physical attacks according to their different attack forms. Compared with digital attacks, which generate perturbations in the digital pixels, physical attacks are more practical in the real world. Owing to the serious security problem caused by physically adversarial examples, many works have been proposed to evaluate the physically adversarial robustness of DNNs in the past years. In this paper, we summarize a survey versus the current physically adversarial attacks and physically adversarial defenses in computer vision. To establish a taxonomy, we organize the current physical attacks from attack tasks, attack forms, and attack methods, respectively. Thus, readers can have a systematic knowledge of this topic from different aspects. For the physical defenses, we establish the taxonomy from pre-processing, in-processing, and post-processing for the DNN models to achieve full coverage of the adversarial defenses. Based on the above survey, we finally discuss the challenges of this research field and further outlook on the future direction

Preventing Unauthorized AI Over-Analysis by Medical Image Adversarial Watermarking

The advancement of deep learning has facilitated the integration of Artificial Intelligence (AI) into clinical practices, particularly in computer-aided diagnosis. Given the pivotal role of medical images in various diagnostic procedures, it becomes imperative to ensure the responsible and secure utilization of AI techniques. However, the unauthorized utilization of AI for image analysis raises significant concerns regarding patient privacy and potential infringement on the proprietary rights of data custodians. Consequently, the development of pragmatic and cost-effective strategies that safeguard patient privacy and uphold medical image copyrights emerges as a critical necessity. In direct response to this pressing demand, we present a pioneering solution named Medical Image Adversarial watermarking (MIAD-MARK). Our approach introduces watermarks that strategically mislead unauthorized AI diagnostic models, inducing erroneous predictions without compromising the integrity of the visual content. Importantly, our method integrates an authorization protocol tailored for legitimate users, enabling the removal of the MIAD-MARK through encryption-generated keys. Through extensive experiments, we validate the efficacy of MIAD-MARK across three prominent medical image datasets. The empirical outcomes demonstrate the substantial impact of our approach, notably reducing the accuracy of standard AI diagnostic models to a mere 8.57% under white box conditions and 45.83% in the more challenging black box scenario. Additionally, our solution effectively mitigates unauthorized exploitation of medical images even in the presence of sophisticated watermark removal networks. Notably, those AI diagnosis networks exhibit a meager average accuracy of 38.59% when applied to images protected by MIAD-MARK, underscoring the robustness of our safeguarding mechanism

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Preparation and Performance of Sintered Fe-2Cu-2Mo-0.8C Materials Containing Different Forms of Molybdenum Powder

Fe-2Cu-2Mo-0.8C powder mixtures were prepared by mixing Fe, Cu and C elemental powders with different forms of Mo-containing powder (pure Mo powder, prealloyed Mo-Fe powder and mechanically alloyed Mo-Fe powder, respectively). The powder mixtures were warm pressed under different pressures and temperatures. Properties of the green compacts and the sintered parts were tested to investigate the effects of the different ways of introducing molybdenum. The test results show that a green density of 7.32 g/cm3 was obtained for Fe-2Cu-2Mo-0.8C powder mixtures containing mechanically alloyed Mo-Fe powders, under a warm compaction pressure of 800 MPa and warm pressing temperature of 120 °C, respectively. The sintered Fe-2Cu-2Mo-0.8C specimens added with mechanically alloyed Mo-Fe powders had a density of 7.31 g/cm3, a hardness of 95 HRB and a tensile strength of 618 MPa, respectively. Compared with the sintered samples, added Mo in the forms of pure Mo and prealloyed Mo-Fe powder, the sintered parts added with mechanically alloyed Mo-Fe powders had more uniform microstructure, better mechanical and wear-resistant properties

Does Agricultural Credit Mitigate the Effect of Climate Change on Cereal Production? Evidence from Sichuan Province, China

This study attempts to investigate the effects of global climate change (via temperature and rainfall) on cereal production in Sichuan over the 1978–2018 period, whether agricultural credit combining with technical progress (i.e., mechanical farming rate) mitigate the effect of climate change. The present study empirically analyzed the short-term and long-term interrelation among all the considered variables by using the autoregressive distributed lag (ARDL) model. The results of the ARDL bounds testing revealed that there is a long-term cointegration relationship between the variables. The findings showed that temperature significantly negatively affected cereal production, while rainfall significantly contributed to cereal production in the context of Sichuan province, China. Agricultural credit, especially in the long run, significantly improved cereal production, implying that agricultural credit is used to invest in climate mitigation technologies in cereal production. Findings further indicated that the mechanical farming rate significantly enhanced cereal production, indicating that technical progress has been playing a vital role. This study suggests that the policymakers should formulate more comprehensive agricultural policies to meet the financial needs of the agricultural sector and increase support for production technology

Continuous WCu functional gradient material from pure W to WCu layer prepared by a modified sedimentation method

The thermal stress between W plasma-facing material (PFM) and Cu heat sink in fusion reactors can be significantly reduced by using a WCu functionally graded material (WCu FGM) interlayer. However, there is still considerable stress at the joining interface between W and WCu FGM in the W/WCu FGM/Cu portions. In this work, we fabricate W skeletons with continuous gradients in porosity by a modified sedimentation method. Sintering densification behavior and pore characteristics of the sedimented W skeletons at different sintering temperatures were investigated. After Cu infiltration, the final WCu FGM was obtained. The results indicate that the pore size and porosity in the W skeleton decrease gradually with the increase of sintering temperature, but the increase of skeleton sintering temperature does not reduce the gradient range of composition distribution of the final prepared WCu FGM. And WCu FGM with composition distribution from pure W to W-20.5wt.% Cu layer across the section was successfully obtained. The thickness of the pure W layer is about one-fifth of the whole sample thickness. In addition, the prepared WCu FGM has a relative density of 94.5 % and thermal conductivity of 185 W/(m • K). The WCu FGM prepared in this work may provide a good solution to alleviate the thermal stress between W PFM and Cu heat sink in the fusion reactors

Recent progress in research on bonding technologies of W/Cu monoblocks as the divertor for nuclear fusion reactors

Divertor components with excellent comprehensive performance are a new research focus for nuclear fusion reactors. However, the excessive mismatch in the coefficient of thermal expansion (CTE) between W and Cu poses a challenge for their application in the divertor. This paper provides a review of the recent progress in the bonding technologies of W/Cu monoblocks, where the W/Cu monoblock refers to any monoblock assembly with a direct W to Cu interface. The bonding technologies of W/Cu monoblocks with bonding interface materials (brazing and diffusion bonding) and W/Cu monoblocks with bonding interface structures (surface nanosizing technologies of W, coating, and explosive welding) are described in detail. The advantages and limitations of each technology are commented upon. Furthermore, the preparation of W/Cu monoblocks with a W-Cu gradient interlayer and W-Cu functionally graded materials (W-Cu FGMs) with full composition distribution is reviewed. These approaches aim to improve the performance of the W/Cu monoblocks. The mechanical, high heat flux (HHF) resistance, and irradiation resistance performance of the W/Cu monoblocks are summarized and evaluated. These performances are crucial for the successful application of W/Cu monoblocks in the divertor. Finally, based on the comprehensive review, future developments and potential research challenges for W/Cu monoblocks are proposed. This provides insights into the direction of future research in this field