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KubeFuzzer: Automating RESTful API Vulnerability Detection in Kubernetes

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Computers, materials and Continua 2024年第1期81卷 1595-1612页

作者： Zheng, Tao tang, Rui Chen, Xingshu Shen, Changxiang school of Cyber science and engineering Sichuan University Chengdu 610065 China Cyber science Research Institute Sichuan University Chengdu 610065 China Key Laboratory of Data Protection and Intelligent Management (Sichuan university) Ministry of Education Chengdu 610065 China

RESTful API fuzzing is a promising method for automated vulnerability detection in Kubernetes platforms. Existing tools struggle with generating lengthy, high-semantic request sequences that can pass Kubernetes API gateway checks. To address this, we propose KubeFuzzer, a black-box fuzzing tool designed for Kubernetes RESTful APIs. KubeFuzzer utilizes Natural Language Processing (NLP) to extract and integrate semantic information from API specifications and response messages, guiding the generation of more effective request sequences. Our evaluation of KubeFuzzer on various Kubernetes clusters shows that it improves code coverage by 7.86% to 36.34%, increases the successful response rate by 6.7% to 83.33%, and detects 16.7% to 133.3% more bugs compared to three leading techniques. KubeFuzzer identified over 1000 service crashes, which were narrowed down to 7 unique bugs. We tested these bugs on 10 real-worldKubernetes projects, including major providers likeAWS (EKS),Microsoft Azure (AKS), and AlibabaCloud (ACK), and confirmed that these issues could trigger service crashes. We have reported and confirmed these bugs with the Kubernetes community, and they have been addressed. © 2024 The Authors. Published by Tech science Press.

关键词： Kubernetes RESTful APIs API fuzzing black-box fuzzing

Effect of Continuous Cooling Conditions on Microstructure and Mechanical Properties of High Carbon Steel Rod

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International Journal of Minerals,Metallurgy and materials 1999年第4期13卷 277-280页

作者： QingWu Cai1 Yumei Pu2 Di tang1 Zhenli Mi1 Yuzhou Zhu2(l Material science and engineering school, university of science and Technology Beijing, Beijing 100083, china2 Maanshan iron and Steel Co. Ltd., Maanshan 243000, china) Univ Sci & Technol Beijing Sch Mat Sci & Engn Beijing 100083 Peoples R China Maanshan Iron & Steel Co Ltd Maanshan 243000 Peoples R China

The effect of cooling rate and austenitizing condition on the mechanical properties of high carbon steel (SWRH82B) has beeninvestigated. Specimens were made of high carbon steel rod and heat-treated by Gleeble-2000 to produce a wide variation in prior austenite size. Different cooling rates were carried out, and then pearlite interlaminar spacing and mechanical properties were measured andtested respectively. According to the results, it could be found that under the continuous cooling with the increase of cooling rate, tensilestrength greatly increases and reduction in area exhibits a slightly increase for an equivalent value of prior austenite grain size. Whenprior austenite size increases, reduction in area decreases, and tensile strength increases slightly for an equivalent value of pearlite interlaminar spacing. It is concluded that prior austenite size primarily controls ductility and pearlite interlaminar spacing controls tensilestrength. Mathematical formulae are given for these relations.

关键词： high carbon steel continuous cooling, interlaminar spacing ofpearlite, austenite grain size.

Mural Anomaly Region Detection Algorithm Based on Hyperspectral Multiscale Residual Attention Network

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Computers, materials and Continua 2024年第1期81卷 1809-1833页

作者： Guo, Bolin Qiu, Shi Zhang, Pengchang tang, Xingjia Key Laboratory of Spectral Imaging Technology CAS Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an 710119 China school of Optoelectronics University of Chinese Academy of Sciences Beijing 100408 China Institute of Culture and Heritage Northwest Polytechnic University Xi'an 710072 China

Mural paintings hold significant historical information and possess substantial artistic and cultural ***, murals are inevitably damaged by natural environmental factors such as wind and sunlight, as well as by human activities. For this reason, the study of damaged areas is crucial formural restoration. These damaged regions differ significantly from undamaged areas and can be considered abnormal targets. Traditional manual visual processing lacks strong characterization capabilities and is prone to omissions and false detections. Hyperspectral imaging can reflect the material properties more effectively than visual characterization methods. Thus, this study employs hyperspectral imaging to obtain mural information and proposes a mural anomaly detection algorithm based on a hyperspectral multi-scale residual attention network (HM-MRANet). The innovations of this paper include: (1) Constructing mural painting hyperspectral datasets. (2) Proposing a multi-scale residual spectral-spatial feature extraction module based on a 3D CNN (Convolutional Neural Networks) network to better capture multiscale information and improve performance on small-sample hyperspectral datasets. (3) Proposing the Enhanced Residual Attention Module (ERAM) to address the feature redundancy problem, enhance the network's feature discrimination ability, and further improve abnormal area detection accuracy. The experimental results show that theAUC(AreaUnderCurve), Specificity, andAccuracy of this paper's algorithmreach 85.42%, 88.84%, and 87.65%, respectively, on this dataset. These results represent improvements of 3.07%, 1.11% and 2.68% compared to the SSRN algorithm, demonstrating the effectiveness of this method for mural anomaly detection. © 2024 The Authors. Published by Tech science Press.

关键词： Convolutional neural networks

A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode

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Computers, materials & Continua 2024年第5期79卷 2277-2293页

作者： Zhigao Zeng Aoting tang Shengqiu Yi Xinpan Yuan Yanhui Zhu school of Computer Hunan University of TechnologyZhuzhou412007China Hunan Key Laboratory of Intelligent Information Perception and Processing Technology Zhuzhou412007China

Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for *** has received great attention due to its huge application prospects in recent *** can know that the number of features selected by the existing radiomics feature selectionmethods is basically about *** this paper,a heuristic feature selection method based on frequency iteration and multiple supervised training mode is *** on the combination between features,it decomposes all features layer by layer to select the optimal features for each layer,then fuses the optimal features to form a local optimal group layer by layer and iterates to the global optimal combination *** with the currentmethod with the best prediction performance in the three data sets,thismethod proposed in this paper can reduce the number of features fromabout ten to about three without losing classification accuracy and even significantly improving classification *** proposed method has better interpretability and generalization ability,which gives it great potential in the feature selection of radiomics.

关键词： Radiomics feature selection machine learning metaheuristic

A Unified Model Fusing Region of Interest Detection and Super Resolution for Video Compression

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Computers, materials & Continua 2024年第6期79卷 3955-3975页

作者： Xinkun tang Feng Ouyang Ying Xu Ligu Zhu Bo Peng school of Computer and Cyber sciences Communication University of ChinaBeijing100024China Cable Television Technology Research Institute Academy of Broadcasting ScienceBeijing100866China

High-resolution video transmission requires a substantial amount of *** this paper,we present a novel video processing methodology that innovatively integrates region of interest(ROI)identification and super-resolution *** method commences with the accurate detection of ROIs within video sequences,followed by the application of advanced super-resolution techniques to these areas,thereby preserving visual quality while economizing on data *** validate and benchmark our approach,we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical *** proposed model architecture leverages the transformer network framework,guided by a carefully designed multi-task loss function,which facilitates concurrent learning and execution of both ROI identification and resolution enhancement *** unified deep learning model exhibits remarkable performance in achieving super-resolution on our custom *** implications of this research extend to optimizing low-bitrate video streaming *** selectively enhancing the resolution of critical regions in videos,our solution enables high-quality video delivery under constrained bandwidth *** results demonstrate a 15%reduction in transmission bandwidth compared to traditional super-resolution based compression methods,without any perceivable decline in visual *** work thus contributes to the advancement of video compression and enhancement technologies,offering an effective strategy for improving digital media delivery efficiency and user experience,especially in bandwidth-limited *** innovative integration of ROI identification and super-resolution presents promising avenues for future research and development in adaptive and intelligent video communication systems.

关键词： Super resolution region of interest detection video compression

MSC-YOLO:Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

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Computers, materials & Continua 2024年第4期79卷 983-1003页

作者： Xiangyan tang Chengchun Ruan Xiulai Li Binbin Li Cebin Fu school of Computer science and Technology Hainan UniversityHaikou570228China Hainan Blockchain Technology engineering Research Center Hainan UniversityHaikou570228China school of Cyberspace Security(school of Cryptology) Hainan UniversityHaikou570228China

Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in thefield of small object detection on unmanned aerial vehicles(UAVs).This task is challenging due to variations inUAV flight altitude,differences in object scales,as well as factors like flight speed and motion *** enhancethe detection efficacy of small targets in drone aerial imagery,we propose an enhanced You Only Look Onceversion 7(YOLOv7)algorithm based on multi-scale spatial *** build the MSC-YOLO model,whichincorporates an additional prediction head,denoted as P2,to improve adaptability for small *** replaceconventional downsampling with a Spatial-to-Depth Convolutional Combination(CSPDC)module to mitigatethe loss of intricate feature details related to small ***,we propose a Spatial Context Pyramidwith Multi-Scale Attention(SCPMA)module,which captures spatial and channel-dependent features of smalltargets acrossmultiple *** module enhances the perception of spatial contextual features and the utilizationof multiscale feature *** the Visdrone2023 and UAVDT datasets,MSC-YOLO achieves remarkableresults,outperforming the baseline method YOLOv7 by 3.0%in terms ofmean average precision(mAP).The MSCYOLOalgorithm proposed in this paper has demonstrated satisfactory performance in detecting small targets inUAV aerial photography,providing strong support for practical applications.

关键词： Small object detection YOLOv7 multi-scale attention spatial context

Three types of promising functional building units for designing metal halide nonlinear optical crystals

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Chinese Journal of Structural Chemistry 2024年第6期43卷 8-11页

作者： Jiajing Wu Ru-Ling tang Sheng-Ping Guo school of Chemistry and Chemical engineering Yangzhou UniversityYangzhou225002PR China Yunnan Key Laboratory of Electromagnetic materials and Devices National Center for International Research on Photoelectric and Energy MaterialsSchool of Material and EnergyYunnan UniversityKunming650000PR China

Nonlinear optical(NLO)crystal materials greatly extend the tunable range of laser by frequency conversion,which promotes the rapid development of laser technology and plays an important role in many civil and military *** excellent and famous NLO crystals from the ultraviolet(UV)to visible to near infrared(NIR)regions have been developed,such as borates(KBe_(2)BO_(3)F_(2),β-BaB_(2)O_(4)),phosphates(KH_(2)PO_(4),KTiOPO_(4)),chalcogenides(AgGaS_(2),AgGaSe_(2))and so on[1,2].

关键词： optical tunable designing

Data-driven discovery of formation ability descriptors for high-entropy rare-earth monosilicates

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Journal of Materiomics 2024年第3期10卷 738-747页

作者： Hong Meng Peng Wei Zhongyu tang Hulei Yu Yanhui Chu school of materials science and engineering South China University of TechnologyGuangzhou510641China

Herein we establish formation ability descriptors of high-entropy rare-earth monosilicates(HEREMs)via the data-driven discovery based on the high-throughput solid-state reaction and machine learning(ML)***,adequate high-quality data are generated with 132 samples synthesized by the self-developed high-throughput solid-state reaction apparatuses,and 30 potential descriptors are considered in ML *** classifications are proposed to study the phase formation of HEREMs via the ML approach combined with the genetic algorithm:(Ⅰ)to distinguish pure HEREMs(X)from other phases and(Ⅱ)to categorize the detail phases of HEREMs(X2,X1,or X2+X1).Four formation ability descriptors(r_(Me),EF,d_(Eg),and d_(Z*))with a high validation accuracy(96.2%)are proposed as the optimal combination for Classification I,where a smaller r_(Me)is determined to have the most significant influence on the formation of *** ClassificationⅡ,a 100%validation accuracy is achieved by using only two formation ability descriptors(rion and d_(Z*)),where the rion is analyzed to be the dominant feature and a lower rion is beneficial to the formation of *** on our established formation ability descriptors,6,045 unreported multicomponent silicates are explored,and 3,478 new HEREMs with 2,700 X2-and 423 X1-HEREMs are predicted.

关键词： High-entropy rare-earth monosilicates Formation ability descriptors High-throughput experiments Machine learning

Enhancing the anti-corrosion performance and biocompatibility of AZ91D Mg alloy by applying roughness pretreatment and coating with in-situ Mg(OH)_(2)/Mg-Al LDH

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Journal of Magnesium and Alloys 2024年第6期12卷 2520-2533页

作者： Zexi Shao Pubo Li Chao Zhang Bintao Wu Chan tang Mangmang Gao school of materials and New Energy Ningxia Key Laboratory of Photovoltaic MaterialsNingxia UniversityYinchuan750021PR China Department of Gastroenterology The Third Xiangya HospitalCentral South UniversityChangsha410000PR China

Corrosion-resistant and biocompatible films were fabricated on AZ91D Mg alloy substrates by varying their roughness levels using met-allographic preparation and subsequent hydrothermal *** coated films comprised a mixed structure of Mg(OH)_(2)and Mg-Al layered double hydroxides(LDH)and exhibited excellent *** film thickness increased with decreasing surface *** resistance was evaluated using potentiodynamic polarization and electrochemical impedance *** pretreat-ment influenced the chemical activity of the Mg alloy surface and helped modulate the dissolution rate of the Mg_(17)Al_(12)phase during the hydrothermal *** decreasing roughness of the Mg substrate,the Al^(3+)concentration gradually increased,accelerating the in-situ formation of the Mg(OH)_(2)/LDH composite coating and improving its crystallinity.A thick and dense Mg(OH)_(2)/LDH coating was synthesized on the Mg substrate with the least roughness,substantially improving the corrosion resistance of the AZ91D *** lowest corrosion current density((5.73±2.75)×10^(−8)A·cm^(−2))was achieved,which was approximately three orders of magnitude less than that of bare ***,the coating demonstrated biocompatibility with no evident cytotoxicity,cellular damage,and hemolytic *** study provides an effective method for preparing coatings on Mg alloy surfaces with excellent corrosion resistance and biocompatibility.

关键词： Magnesium alloy Roughness Corrosion resistance Layered double hydroxides Biocompatibility