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Unstructured Big Data Threat Intelligence Parallel Mining Algorithm
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作者 Zhihua Li xinye yu +1 位作者 Tao Wei Junhao Qian 《Big Data Mining and Analytics》 EI CSCD 2024年第2期531-546,共16页
To efficiently mine threat intelligence from the vast array of open-source cybersecurity analysis reports on the web,we have developed the Parallel Deep Forest-based Multi-Label Classification(PDFMLC)algorithm.Initial... To efficiently mine threat intelligence from the vast array of open-source cybersecurity analysis reports on the web,we have developed the Parallel Deep Forest-based Multi-Label Classification(PDFMLC)algorithm.Initially,open-source cybersecurity analysis reports are collected and converted into a standardized text format.Subsequently,five tactics category labels are annotated,creating a multi-label dataset for tactics classification.Addressing the limitations of low execution efficiency and scalability in the sequential deep forest algorithm,our PDFMLC algorithm employs broadcast variables and the Lempel-Ziv-Welch(LZW)algorithm,significantly enhancing its acceleration ratio.Furthermore,our proposed PDFMLC algorithm incorporates label mutual information from the established dataset as input features.This captures latent label associations,significantly improving classification accuracy.Finally,we present the PDFMLC-based Threat Intelligence Mining(PDFMLC-TIM)method.Experimental results demonstrate that the PDFMLC algorithm exhibits exceptional node scalability and execution efficiency.Simultaneously,the PDFMLC-TIM method proficiently conducts text classification on cybersecurity analysis reports,extracting tactics entities to construct comprehensive threat intelligence.As a result,successfully formatted STIX2.1 threat intelligence is established. 展开更多
关键词 unstructured big data mining parallel deep forest multi-label classification algorithm threat intelligence
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Regulating droplet impact symmetry by surface engineering 被引量:1
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作者 Zhipeng Zhao Huizeng Li +7 位作者 Quan Liu An Li Luanluan Xue Renxuan yuan xinye yu Rujun Li Xiao Deng Yanlin Song 《Droplet》 2023年第2期27-45,共19页
Droplet impact on solid surfaces is essential both in nature and industry.Precisely regulating the dynamic behavior of droplet impact is of great significance for energy harvesting,anti-icing,inkjet printing,pesticide... Droplet impact on solid surfaces is essential both in nature and industry.Precisely regulating the dynamic behavior of droplet impact is of great significance for energy harvesting,anti-icing,inkjet printing,pesticide spraying,and many other fields.Various rebounding behaviors(deposition,rebounding,rotation,instability control,and so on)and rebounding intrinsic parameters(such as contact time)after droplets impacting on solid surfaces can be regulated by surface engineering.This paper reviews the advances in regulating droplet impact behavior from the perspective of symmetry by modifying solid surfaces from the following aspects:chemical modification and physical structure regulation,in which the symmetry is discussed from mirror symmetry and rotational symmetry.Firstly,the symmetry of the droplet impact dynamics and its influencing factors are introduced.Then the modulation of droplet impact symmetry,using homogeneous and heterogeneous chemically modified solid surfaces,is summarized.The following presents the influence of physical structures,from micro to macro scale compared to the droplet size,on the droplet impact symmetry.Finally,the future challenges and opportunities of the droplet impact behavior regulation are discussed。 展开更多
关键词 SYMMETRY summarized ROTATION
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