Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHS...Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHSAS is developed for national backbone network,large network operators,large enterprises and other large-scale network.This paper describes its architecture and key technologies:Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis,Knowledge Representation and Management of Super Large-Scale Network Security,Multi-Level,Multi-Granularity and Multi-Dimensional Network Security Index Construction Method,Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology,and so on.The performance tests show that YHSAS has high real-time performance and accuracy in security situation analysis and trend prediction.The system meets the demands of analysis and prediction for large-scale network security situation.展开更多
ENSO-driven extreme weather events such as droughts and floods can cause significant damage to agricultural production and different intensities of ENSO events make uncertain changes to rural residents'welfare in ...ENSO-driven extreme weather events such as droughts and floods can cause significant damage to agricultural production and different intensities of ENSO events make uncertain changes to rural residents'welfare in different regions.To emphasize this uncertainty,the stochastic CGE model is constructed by imbedding a stochastic parameter into the production module to analyze the impacts of ENSO on the welfare of rural residents in various regions of China and the volatility of uncertain ENSO events on the welfare of residents.The role of agricultural technology in improving welfare stability and transfer payments in reducing welfare losses from ENSO are also examined.The results show that weak ENSO events have little effect on the welfare of rural residents while strong ENSO events cause the welfare of rural residents a significant decline,and the largest decrease appears separately in the southwest region and the smallest one in the northeast.The uncertainty of ENSO events seriously affects the stability of the welfare of the residents,with the average fluctuation level of 200%in the change of the rural residents'welfare in all regions under El Ni o.Technically improving the anti-risk ability of agriculture can effectively reduce the fluctuation of residents'welfare.Besides,if the government increases the transfer payment to the rural resident for disaster relief,the welfare would increase,and the higher the payment,the greater the improvement of the welfare.展开更多
[Objectives]The paper was to study the impacts of sand and dust storms(SDS)on regional economy.[Methods]In this paper,we combined the computable general equilibrium(CGE)model and the Monte Carlo method to examine the ...[Objectives]The paper was to study the impacts of sand and dust storms(SDS)on regional economy.[Methods]In this paper,we combined the computable general equilibrium(CGE)model and the Monte Carlo method to examine the impact of SDS on the regional economy,with a focus on GDP,price index,employment rate,industrial structure and output,income and expenditure.We extended the standard CGE model,introduced the stochastic parameters into the production module,which had significant impact on economic output,and inserted the rate of change of the total labor supply and the expenditure share of early warning and protective measures into the income and expenditure module.[Results]SDS had significant impacts on regional GDP,employment rate,and industrial output from a macro perspective,and can reduce the income of residents and enterprises and increase expenditures from a micro perspective.The impact can be reduced by taking early warning and protective measures.[Conclusions]The protective measures taken for different grades of SDS have different effects.展开更多
Penetration testing is an important method for discovering hidden vulnerabilities and attack paths in network systems, which is of great significance for evaluating network security. However, traditional penetration t...Penetration testing is an important method for discovering hidden vulnerabilities and attack paths in network systems, which is of great significance for evaluating network security. However, traditional penetration testing methods can only be carried out by security analysts, and the results are unstable, requiring extra time and money. Automated penetration testing can effectively reduce reliance on manual efforts. Automated attack planning,as one of the most critical components, has garnered widespread attention from researchers.Although previous studies have explored a variety of methods to mine attack paths, most of them require prior knowledge of the network topology, which contradicts reality and thus lacks application value. To automatically find the best potential attack path in complex and unknown networks from the hacker's perspective, this paper proposes ShotFlex: a reinforcement learning-based method that uses a quantifiable method to evaluate host and obtain rewards, which guides the agent to choose the best response action to discover attack paths from the intruder's perspective. ShotFlex also introduces a pruning strategy based on prior knowledge to accelerate path generation. Experimental results reveal that ShotFlex can combine current information to provide an effective decision and significantly improve the efficiency of penetration testing.展开更多
Users of social media sites can use more than one account. These identities have pseudo anonymous properties, and as such some users abuse multiple accounts to perform undesirable actions, such as posting false or mis...Users of social media sites can use more than one account. These identities have pseudo anonymous properties, and as such some users abuse multiple accounts to perform undesirable actions, such as posting false or misleading re- marks comments that praise or defame the work of others. The detection of multiple user accounts that are controlled by an individual or organization is important. Herein, we define the problem as sockpuppet gang （SPG） detection. First, we analyze user sentiment orientation to topics based on emo- tional phrases extracted from their posted comments. Then we evaluate the similarity between sentiment orientations of user account pairs, and build a similar-orientation network （SON） where each vertex represents a user account on a so- cial media site. In an SON, an edge exists only if the two user accounts have similar sentiment orientations to most topics. The boundary between detected SPGs may be indistinct, thus by analyzing account posting behavior features we propose a multiple random walk method to iteratively remeasure the weight of each edge. Finally, we adopt multiple community detection algorithms to detect SPGs in the network. User ac- counts in the same SPG are considered to be controlled by the same individual or organization. In our experiments on real world datasets, our method shows better performance than other contemporary methods.展开更多
基金This work is funded by the National Natural Science Foundation of China under Grant U1636215the National key research and development plan under Grant Nos.2018YFB0803504,2016YFB0800303.
文摘Network Security Situation Awareness System YHSAS acquires,understands and displays the security factors which cause changes of network situation,and predicts the future development trend of these security factors.YHSAS is developed for national backbone network,large network operators,large enterprises and other large-scale network.This paper describes its architecture and key technologies:Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis,Knowledge Representation and Management of Super Large-Scale Network Security,Multi-Level,Multi-Granularity and Multi-Dimensional Network Security Index Construction Method,Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology,and so on.The performance tests show that YHSAS has high real-time performance and accuracy in security situation analysis and trend prediction.The system meets the demands of analysis and prediction for large-scale network security situation.
基金Supported by National Natural Science Foundation of China:Randomization Improvement of CGE Model Based on the Perspective of Bearing Capacity of Water Environment and Optimization of Applicable Tax Amount for Water Pollutants(71864027)National Natural Science Foundation of China:Research on Impact Path and Space-time Simulation Evaluation of Carbon Trading Mechanism on Ecological Efficiency of High Energy-consuming Industries(72263025)+2 种基金Inner Mongolia Natural Science Foundation Project:Research on the Selection Mechanism of Optimal Tax Rate in Environmental Protection Tax Areas:Based on the Perspective of General Equilibrium(2019LH07004)Humanities and Social Sciences Project of the Ministry of Education:Research on the Optimization Mechanism of Regional Fixed Tax Rates of Environmental Protection Taxation:A General Equilibrium Analysis Based on Environmental Self-Purification Ability and Economic Activity(19YJA790023)Inner Mongolia Natural Science Foundation Project:Research on the Evaluation Mechanism and Uncertainty of Economic Loss of Sand and Dust Disasters Based on Stochastic CGE Model(2020LH07001).
文摘ENSO-driven extreme weather events such as droughts and floods can cause significant damage to agricultural production and different intensities of ENSO events make uncertain changes to rural residents'welfare in different regions.To emphasize this uncertainty,the stochastic CGE model is constructed by imbedding a stochastic parameter into the production module to analyze the impacts of ENSO on the welfare of rural residents in various regions of China and the volatility of uncertain ENSO events on the welfare of residents.The role of agricultural technology in improving welfare stability and transfer payments in reducing welfare losses from ENSO are also examined.The results show that weak ENSO events have little effect on the welfare of rural residents while strong ENSO events cause the welfare of rural residents a significant decline,and the largest decrease appears separately in the southwest region and the smallest one in the northeast.The uncertainty of ENSO events seriously affects the stability of the welfare of the residents,with the average fluctuation level of 200%in the change of the rural residents'welfare in all regions under El Ni o.Technically improving the anti-risk ability of agriculture can effectively reduce the fluctuation of residents'welfare.Besides,if the government increases the transfer payment to the rural resident for disaster relief,the welfare would increase,and the higher the payment,the greater the improvement of the welfare.
基金Supported by National Natural Science Foundation of China"Research on the Improvement of CGE Model Randomization and the Optimization of Applicable Tax for Water Pollutants Based on the Perspective of Water Environmental Carrying Capacity(71864027)Study on the Impact Path and Spatio-temporal Simulation Evaluation of Carbon Trading Mechanism on Eco-efficiency of Energy-intensive Industries(72263025)+1 种基金Research on the Optimization Mechanism of Fixed Tax Rate in Environmental Protection Tax Regions"Based on the General Equilibrium Analysis of Environmental Self-cleaning Capacity and Economic Activities"(19YJA790023)Inner Mongolia Natural Science Foundation Project"Study on Economic Loss Evaluation Mechanism and Uncertainty of Dust Disaster Based on Stochastic CGE Model"(2020LH07001).
文摘[Objectives]The paper was to study the impacts of sand and dust storms(SDS)on regional economy.[Methods]In this paper,we combined the computable general equilibrium(CGE)model and the Monte Carlo method to examine the impact of SDS on the regional economy,with a focus on GDP,price index,employment rate,industrial structure and output,income and expenditure.We extended the standard CGE model,introduced the stochastic parameters into the production module,which had significant impact on economic output,and inserted the rate of change of the total labor supply and the expenditure share of early warning and protective measures into the income and expenditure module.[Results]SDS had significant impacts on regional GDP,employment rate,and industrial output from a macro perspective,and can reduce the income of residents and enterprises and increase expenditures from a micro perspective.The impact can be reduced by taking early warning and protective measures.[Conclusions]The protective measures taken for different grades of SDS have different effects.
基金supported by the Major Key Project of PCL(Grant No.PCL2024A05-3)
文摘Penetration testing is an important method for discovering hidden vulnerabilities and attack paths in network systems, which is of great significance for evaluating network security. However, traditional penetration testing methods can only be carried out by security analysts, and the results are unstable, requiring extra time and money. Automated penetration testing can effectively reduce reliance on manual efforts. Automated attack planning,as one of the most critical components, has garnered widespread attention from researchers.Although previous studies have explored a variety of methods to mine attack paths, most of them require prior knowledge of the network topology, which contradicts reality and thus lacks application value. To automatically find the best potential attack path in complex and unknown networks from the hacker's perspective, this paper proposes ShotFlex: a reinforcement learning-based method that uses a quantifiable method to evaluate host and obtain rewards, which guides the agent to choose the best response action to discover attack paths from the intruder's perspective. ShotFlex also introduces a pruning strategy based on prior knowledge to accelerate path generation. Experimental results reveal that ShotFlex can combine current information to provide an effective decision and significantly improve the efficiency of penetration testing.
文摘Users of social media sites can use more than one account. These identities have pseudo anonymous properties, and as such some users abuse multiple accounts to perform undesirable actions, such as posting false or misleading re- marks comments that praise or defame the work of others. The detection of multiple user accounts that are controlled by an individual or organization is important. Herein, we define the problem as sockpuppet gang （SPG） detection. First, we analyze user sentiment orientation to topics based on emo- tional phrases extracted from their posted comments. Then we evaluate the similarity between sentiment orientations of user account pairs, and build a similar-orientation network （SON） where each vertex represents a user account on a so- cial media site. In an SON, an edge exists only if the two user accounts have similar sentiment orientations to most topics. The boundary between detected SPGs may be indistinct, thus by analyzing account posting behavior features we propose a multiple random walk method to iteratively remeasure the weight of each edge. Finally, we adopt multiple community detection algorithms to detect SPGs in the network. User ac- counts in the same SPG are considered to be controlled by the same individual or organization. In our experiments on real world datasets, our method shows better performance than other contemporary methods.
