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Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning 被引量:1
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作者 Zibo Wang Chaobin Huo +5 位作者 Yaofang Zhang Shengtao Cheng Yilu Chen Xiaojie Wei Chao Li Bailing Wang 《Computers, Materials & Continua》 SCIE EI 2023年第5期2957-2979,共23页
With the growing discovery of exposed vulnerabilities in the Industrial Control Components(ICCs),identification of the exploitable ones is urgent for Industrial Control System(ICS)administrators to proactively forecas... With the growing discovery of exposed vulnerabilities in the Industrial Control Components(ICCs),identification of the exploitable ones is urgent for Industrial Control System(ICS)administrators to proactively forecast potential threats.However,it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods.To address these challenges,we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph(KG)in which relation paths contain abundant potential evidence to support the reasoning.The reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical paths.The proposed method consists of three primary building blocks:KG construction,relation path representation,and query relation reasoning.A security-oriented ontology combines exploit modeling,which provides a guideline for the integration of the scattered knowledge while constructing the KG.We emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate reasoning.In order to acquire a high-quality representation,the entity and relation embeddings take advantage of their local structure and related semantics.Some critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation validity.In particular,similarity calculation is introduced into a critical path selection algorithm,which improves search and reasoning performance.Meanwhile,the proposed algorithm avoids redundant paths between the given pairs of entities.Experimental results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy. 展开更多
关键词 Path-based reasoning representation learning attention mechanism vulnerability knowledge graph industrial control component
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Shanghai Car Parts and Components Industry
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作者 Liu Xiaoming State Economic and Trade Commission 《China's Foreign Trade》 1994年第12期52-52,共1页
Shanghai Santana cars had produced a total of 270,000 cars by the end of 1993, and undergone SKD, CKD and localization stages. The car industry will soon become a pillar industry in Shanghai. During its development, t... Shanghai Santana cars had produced a total of 270,000 cars by the end of 1993, and undergone SKD, CKD and localization stages. The car industry will soon become a pillar industry in Shanghai. During its development, the Shanghai car industry has always given special attention to localization, thus the localization rate of car parts and components has increased year by year. In 1988, Shanghai Santanacars produced 15,000 units, with 13,08 percent of 展开更多
关键词 SKD Shanghai Car Parts and components industry
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Trace metals in atmospheric fine particles in one industrial urban city: Spatial variations, sources, and health implications 被引量:25
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作者 Shengzhen Zhou Qi Yuan +3 位作者 Weijun Li Yaling Lu Yangmei Zhang Wenxing Wang 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2014年第1期205-213,共9页
Trace metals in PM2.5 were measured at one industrial site and one urban site during September, 2010 in Ji'nan, eastern China. Individual aerosol particles and PM2.5 samples were collected concurrently at both sites.... Trace metals in PM2.5 were measured at one industrial site and one urban site during September, 2010 in Ji'nan, eastern China. Individual aerosol particles and PM2.5 samples were collected concurrently at both sites. Mass concentrations of eleven trace metals (i.e., Al, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Sr, Ba, and Pb) and one metalloid (i.e., As) were measured by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The result shows that mass concentrations of PM2.5 (130μg/m3) and trace metals (4.03 μg/m3) at the industrial site were 1.3 times and 1.7 times higher than those at the urban site, respectively, indicating that industrial activities nearby the city can emit trace metals into the surrounding atmosphere. Fe concentrations were the highest among all the measured trace metals at both sites, with concentrations of 1.04 ixg/m 3 at the urban site and 2.41 Itg/m3 at the industrial site, respectively. In addition, Pb showed the highest enrichment factors at both sites, suggesting the emissions from anthropogenic activities existed around the city. Correlation coefficient analysis and principal component analysis revealed that Cu, Fe, Mn, Pb, and Zn were originated from vehicular traffic and industrial emissions at both sites; As, Cr, and part of Pb from coal-fired power plant; Ba and Ti from natural soil. Based on the transmission electron microscopy analysis, we found that most of the trace metals were internally mixed with secondary sulfate/organic particles. These internally mixed trace metals in the urban air may have different toxic abilities compared with externally mixed trace metals. 展开更多
关键词 trace metals PM2.5 enrichment factors principal component analysis (PCA) industrial sources
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