Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affect...Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.展开更多
Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend o...Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.展开更多
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
The paper investigates applicability of the developed high-level model and technology for solution of diverse problems in large distributed dynamic systems which can provide sufficient awareness of their structures,or...The paper investigates applicability of the developed high-level model and technology for solution of diverse problems in large distributed dynamic systems which can provide sufficient awareness of their structures,organization,and functionalities.After the review of meanings of awareness and existing approaches for its expression and support,the paper shows application of the Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)for very practical awareness solutions in large distributed dynamic systems,with obtaining any knowledge from any point inside or outside the system.The self-evolving,self-replicating,and self-recovering scenario code in SGL can effectively supervise distributed systems under any circumstances including rapidly changing number of their elements.Examples are provided in SGL for distributed networked systems showing how in any node any information about other nodes and links,including the whole system,can be obtained by using network requesting patterns based on recursive scenarios combining forward and backward network matching and coverage.The returned results may be automatically organized in networked patterns too.The presented exemplary solutions are parallel and fully distributed,without the need of using vulnerable centralized resources,also very compact.This can be explained by fundamentally different philosophy and ideology of SGT which is not based on traditional partitioned systems representation and multiple agent communications.On the contrary,SGT and its basic language supervise and control distributed systems by holistic self-spreading recursive code in wavelike,virus-like,and even“soul-like”mode.展开更多
The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to researc...The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.展开更多
Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This l...Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness.展开更多
The existing network security management systems are unable either to provide users with useful security situation and risk assessment, or to aid administrators to make right and timely decisions based on the current ...The existing network security management systems are unable either to provide users with useful security situation and risk assessment, or to aid administrators to make right and timely decisions based on the current state of network. These disadvantages always put the whole network security management at high risk. This paper establishes a simulation environment, captures the alerts as the experimental data and adopts statistical analysis to seek the vulnerabilities of the services provided by the hosts in the network. According to the factors of the network, the paper introduces the two concepts： Situational Meta and Situational Weight to depict the total security situation. A novel hierarchical algorithm based on analytic hierarchy process （AHP） is proposed to analyze the hierarchy of network and confirm the weighting coefficients. The algorithm can be utilized for modeling security situation, and determining its mathematical expression. Coupled with the statistical results, this paper simulates the security situational trends. Finally, the analysis of the simulation results proves the algorithm efficient and applicable, and provides us with an academic foundation for the implementation in the security situation展开更多
Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the per...Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.展开更多
Network security situation awareness is an important foundation for network security management,which presents the target system security status by analyzing existing or potential cyber threats in the target system.In...Network security situation awareness is an important foundation for network security management,which presents the target system security status by analyzing existing or potential cyber threats in the target system.In network offense and defense,the network security state of the target system will be affected by both offensive and defensive strategies.According to this feature,this paper proposes a network security situation awareness method using stochastic game in cloud computing environment,uses the utility of both sides of the game to quantify the network security situation value.This method analyzes the nodes based on the network security state of the target virtual machine and uses the virtual machine introspection mechanism to obtain the impact of network attacks on the target virtual machine,then dynamically evaluates the network security situation of the cloud environment based on the game process of both attack and defense.In attack prediction,cyber threat intelligence is used as an important basis for potential threat analysis.Cyber threat intelligence that is applicable to the current security state is screened through the system hierarchy fuzzy optimization method,and the potential threat of the target system is analyzed using the cyber threat intelligence obtained through screening.If there is no applicable cyber threat intelligence,using the Nash equilibrium to make predictions for the attack behavior.The experimental results show that the network security situation awareness method proposed in this paper can accurately reflect the changes in the network security situation and make predictions on the attack behavior.展开更多
In recent years,probabilistic tracking methods have been becoming increasingly popular for solving the multi-target tracking problem in Space Situational Awareness(SSA).Bayesian frameworks have been used to describe t...In recent years,probabilistic tracking methods have been becoming increasingly popular for solving the multi-target tracking problem in Space Situational Awareness(SSA).Bayesian frameworks have been used to describe the objects’of interest states and cardinality as point processes.The inputs of the Bayesian framework filters are a probabilistic description of the scene at hand,the probability of clutter during the observation,the probability of detection of the objects,the probability of object survival and birth rates,and in the state update,the measurement uncertainty and process noise for the propagation.However,in the filter derivation,the assumptions of Poisson distributions of the object prior and the clutter model are made.Extracting the first-order moments of the full Bayesian framework leads to a so-called Probability Hypothesis Density(PHD)filter.The first moment extraction of the PHD filter process is extremely sensitive to both the input parameters and the measurements.The specifics of the SSA problem and its probabilistic description are illustrated in this paper and compared to the assumptions that the PHD filter is based on.As an example,this paper shows the response of a Cardinality only PHD filter(only the number of objects is estimated,not their corresponding states)to different input parameterizations.The very simple Cardinality only PHD filter is chosen in order to clearly show the sole effects of the model mismatch that might be blurred with state estimation effects,such as non-linearity in the dynamical model,in a full PHD filter implementation.The simulated multi-target tracking scenario entails the observation of attitude stable and unstable geostationary objects.展开更多
To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-sel...To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.展开更多
In response to the COVID-19,social media big data has played an important role in epidemic warning,tracking the source of infection,and public opinion monitoring,providing strong technical support for China’s epidemi...In response to the COVID-19,social media big data has played an important role in epidemic warning,tracking the source of infection,and public opinion monitoring,providing strong technical support for China’s epidemic prevention and control work.The paper used Sina Weibo posts related to COVID-19 hashtags as the data source,and built a BERT-CNN deep learning model to perform fine-grained and high-precision topic classificationon massive social media posts.Taking Shenzhen as a region of interest,we mined the“epidemic data bulletin”and“daily life impact”posts during the epidemic for spatial analysis.The results show that the confirmed communities and designated hospitals in Shenzhen as a whole present the characteristics of“sparse east and dense west”,and there is a strong positive spatial correlation between the number of confirmed cases and social media response.Specifically,Nanshan District,Futian District and Luohu District have more confirmed cases due to large population movements and dense transportation networks,and social media has responded more violently,and people’s lives have been greatly affected.However,Yantian District,Pingshan District and Dapeng New District showed opposite characteristics.The case study results further show that using deep learning methods to mine text information in social media is scientifically feasible for improving situational awareness and decision support during the COVID-19.展开更多
The paper introduces the Endsley＇ s situation model into network security to describe the network security situation, and improves Endsley＇s data processing to suit network alerts. The proposed model contains the in...The paper introduces the Endsley＇ s situation model into network security to describe the network security situation, and improves Endsley＇s data processing to suit network alerts. The proposed model contains the information of incident frequency, incident time and incident space. The HoneyNet dataset is selected to evaluate the proposed model in the evaluation. The paper proposes three definitions to depict and predigest the whole situation extraction in detail, and a fusion component to reduce the influence of alert redundancy on the total security situation. The less complex extraction makes the situation analysis more efficient, and the fine-grained model makes the analysis have a better expansibility. Finally, the situational variation curves are simulated, and the evaluation results prove the situation model applicable and efficient.展开更多
In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanne...In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanned system coordinative region control operation as an example,this paper combines knowledge representation with probabilistic decisionmaking and proposes a role-based Bayesian decision model for autonomous unmanned systems that integrates scene cognition and individual preferences.Firstly,according to utility value decision theory,the role-based utility value decision model is proposed to realize task coordination according to the preference of the role that individual is assigned.Then,multi-entity Bayesian network is introduced for situation assessment,by which scenes and their uncertainty related to the operation are semantically described,so that the unmanned systems can conduct situation awareness in a set of scenes with uncertainty.Finally,the effectiveness of the proposed method is verified in a virtual task scenario.This research has important reference value for realizing scene cognition,improving cooperative decision-making ability under dynamic scenes,and achieving swarm level autonomy of unmanned systems.展开更多
Microelectronic technology and communication technology are developed in deep manner;the computing mode has been transferred from traditional computer-centered to human centered pervasive.So,the concept of Internet o...Microelectronic technology and communication technology are developed in deep manner;the computing mode has been transferred from traditional computer-centered to human centered pervasive.So,the concept of Internet of things(IoT)is gradually put forward,which allows people to access information about their surroundings on demand through different terminals.The library is the major public space for human to read and learn.How to provide a more comfortable library environment to better meet people’s learning requirements is a place where the Internet of things plays its role.The purpose of this paper is to solve the difference between the data fusion of library environment and the data fusion of other environments by the method of data fusion oriented to library.This paper presents a general technical framework of situational awareness for smart library system which includes a data fusion middleware.It can process data and inform the upper module of the changed library environment after deploying the smart library system in a library,including data collection and processing,how to judge whether events are triggered,how the system reacts,and the acquisition and update of user preferences.This paper presents a situational awareness recommendation method based on an effective data fusion model and algorithm for library after conducting experimental in service of library,which give more accurate of book recommendation than traditional method and good learning service environment of library for readers.展开更多
Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding di...Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding diagnosis of the jamming signals are essential to normal opera-tions and the innovations in anti-jamming equipment.This paper demonstrates a comprehensive survey on jamming monitoring algorithms and applications.The methods in dealing with jamming signals are summarized primarily.Subsequently,the jamming detection,identification,and direc-tion finding techniques are addressed separately.Based on the established studies,we also provide some potential trends of the demonstrated jamming monitoring issues.展开更多
The real-time of network security situation awareness(NSSA)is always affected by the state explosion problem.To solve this problem,a new NSSA method based on layered attack graph(LAG)is proposed.Firstly,network is div...The real-time of network security situation awareness(NSSA)is always affected by the state explosion problem.To solve this problem,a new NSSA method based on layered attack graph(LAG)is proposed.Firstly,network is divided into several logical subnets by community discovery algorithm.The logical subnets and connections between them constitute the logical network.Then,based on the original and logical networks,the selection of attack path is optimized according to the monotonic principle of attack behavior.The proposed method can sharply reduce the attack path scale and hence tackle the state explosion problem in NSSA.The experiments results show that the generation of attack paths by this method consumes 0.029 s while the counterparts by other methods are more than 56 s.Meanwhile,this method can give the same security strategy with other methods.展开更多
基金National Natural Science Foundation of China High Speed Rail Joint Fund(U2268217)。
文摘Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.
基金funded by the Science and Technology Project of China Southern Power Grid(YNKJXM20210175)the National Natural Science Foundation of China(52177070).
文摘Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.
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.
文摘The paper investigates applicability of the developed high-level model and technology for solution of diverse problems in large distributed dynamic systems which can provide sufficient awareness of their structures,organization,and functionalities.After the review of meanings of awareness and existing approaches for its expression and support,the paper shows application of the Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)for very practical awareness solutions in large distributed dynamic systems,with obtaining any knowledge from any point inside or outside the system.The self-evolving,self-replicating,and self-recovering scenario code in SGL can effectively supervise distributed systems under any circumstances including rapidly changing number of their elements.Examples are provided in SGL for distributed networked systems showing how in any node any information about other nodes and links,including the whole system,can be obtained by using network requesting patterns based on recursive scenarios combining forward and backward network matching and coverage.The returned results may be automatically organized in networked patterns too.The presented exemplary solutions are parallel and fully distributed,without the need of using vulnerable centralized resources,also very compact.This can be explained by fundamentally different philosophy and ideology of SGT which is not based on traditional partitioned systems representation and multiple agent communications.On the contrary,SGT and its basic language supervise and control distributed systems by holistic self-spreading recursive code in wavelike,virus-like,and even“soul-like”mode.
基金supported by the National Natural Science Foundation of China(61305133)the Aeronautical Science Foundation of China grant number 2020Z023053002.
文摘The status of an operator’s situation awareness is one of the critical factors that influence the quality of the missions.Thus the measurement method of the situation awareness status is an important topic to research.So far,there are lots of methods designed for the measurement of situation awareness status,but there is no model that can measure it accurately in real-time,so this work is conducted to deal with such a gap.Firstly,collect the relevant physiological data of operators while they are performing a specific mission,simultaneously,measure their status of situation awareness by using the situation awareness global assessment technique(SAGAT),which is known for accuracy but cannot be used in real-time.And then,after the preprocessing of the raw data,use the physiological data as features,the SAGAT’s results as a label to train a fuzzy cognitive map(FCM),which is an explainable and powerful intelligent model.Also,a hybrid learning algorithm of particle swarm optimization(PSO)and gradient descent is proposed for the FCM training.The final results show that the learned FCM can assess the status of situation awareness accurately in real-time,and the proposed hybrid learning algorithm has better efficiency and accuracy.
基金supported by the National Natural Sci-ence Foundation of China(No.52077195).
文摘Facing constraints imposed by storage and bandwidth limitations,the vast volume of phasor meas-urement unit(PMU)data collected by the wide-area measurement system(WAMS)for power systems cannot be fully utilized.This limitation significantly hinders the effective deployment of situational awareness technologies for systematic applications.In this work,an effective curvature quantified Douglas-Peucker(CQDP)-based PMU data compression method is proposed for situational awareness of power systems.First,a curvature integrated distance(CID)for measuring the local flection and fluc-tuation of PMU signals is developed.The Doug-las-Peucker(DP)algorithm integrated with a quan-tile-based parameter adaptation scheme is then proposed to extract feature points for profiling the trends within the PMU signals.This allows adaptive adjustment of the al-gorithm parameters,so as to maintain the desired com-pression ratio and reconstruction accuracy as much as possible,irrespective of the power system dynamics.Fi-nally,case studies on the Western Electricity Coordinat-ing Council(WECC)179-bus system and the actual Guangdong power system are performed to verify the effectiveness of the proposed method.The simulation results show that the proposed method achieves stably higher compression ratio and reconstruction accuracy in both steady state and in transients of the power system,and alleviates the compression performance degradation problem faced by existing compression methods.Index Terms—Curvature quantified Douglas-Peucker,data compression,phasor measurement unit,power sys-tem situational awareness.
基金Supported by the High Technology Research and Development Programme of China （No. 2003AA142160） and the National Natural Science Foundation of China （No. 60605019）.
文摘The existing network security management systems are unable either to provide users with useful security situation and risk assessment, or to aid administrators to make right and timely decisions based on the current state of network. These disadvantages always put the whole network security management at high risk. This paper establishes a simulation environment, captures the alerts as the experimental data and adopts statistical analysis to seek the vulnerabilities of the services provided by the hosts in the network. According to the factors of the network, the paper introduces the two concepts： Situational Meta and Situational Weight to depict the total security situation. A novel hierarchical algorithm based on analytic hierarchy process （AHP） is proposed to analyze the hierarchy of network and confirm the weighting coefficients. The algorithm can be utilized for modeling security situation, and determining its mathematical expression. Coupled with the statistical results, this paper simulates the security situational trends. Finally, the analysis of the simulation results proves the algorithm efficient and applicable, and provides us with an academic foundation for the implementation in the security situation
基金This work was supported by the National Natural Science Foundation of China(61690210,61690213).
文摘Space-based optical(SBO)space surveillance has attracted widespread interest in the last two decades due to its considerable value in space situation awareness(SSA).SBO observation strategy,which is related to the performance of space surveillance,is the top-level design in SSA missions reviewed.The recognized real programs about SBO SAA proposed by the institutions in the U.S.,Canada,Europe,etc.,are summarized firstly,from which an insight of the development trend of SBO SAA can be obtained.According to the aim of the SBO SSA,the missions can be divided into general surveillance and space object tracking.Thus,there are two major categories for SBO SSA strategies.Existing general surveillance strategies for observing low earth orbit(LEO)objects and beyond-LEO objects are summarized and compared in terms of coverage rate,revisit time,visibility period,and image processing.Then,the SBO space object tracking strategies,which has experienced from tracking an object with a single satellite to tracking an object with multiple satellites cooperatively,are also summarized.Finally,this paper looks into the development trend in the future and points out several problems that challenges the SBO SSA.
基金This research was supported in part by the National Natural Science Foundation of China under grant numbers 61672206,61572170.
文摘Network security situation awareness is an important foundation for network security management,which presents the target system security status by analyzing existing or potential cyber threats in the target system.In network offense and defense,the network security state of the target system will be affected by both offensive and defensive strategies.According to this feature,this paper proposes a network security situation awareness method using stochastic game in cloud computing environment,uses the utility of both sides of the game to quantify the network security situation value.This method analyzes the nodes based on the network security state of the target virtual machine and uses the virtual machine introspection mechanism to obtain the impact of network attacks on the target virtual machine,then dynamically evaluates the network security situation of the cloud environment based on the game process of both attack and defense.In attack prediction,cyber threat intelligence is used as an important basis for potential threat analysis.Cyber threat intelligence that is applicable to the current security state is screened through the system hierarchy fuzzy optimization method,and the potential threat of the target system is analyzed using the cyber threat intelligence obtained through screening.If there is no applicable cyber threat intelligence,using the Nash equilibrium to make predictions for the attack behavior.The experimental results show that the network security situation awareness method proposed in this paper can accurately reflect the changes in the network security situation and make predictions on the attack behavior.
文摘In recent years,probabilistic tracking methods have been becoming increasingly popular for solving the multi-target tracking problem in Space Situational Awareness(SSA).Bayesian frameworks have been used to describe the objects’of interest states and cardinality as point processes.The inputs of the Bayesian framework filters are a probabilistic description of the scene at hand,the probability of clutter during the observation,the probability of detection of the objects,the probability of object survival and birth rates,and in the state update,the measurement uncertainty and process noise for the propagation.However,in the filter derivation,the assumptions of Poisson distributions of the object prior and the clutter model are made.Extracting the first-order moments of the full Bayesian framework leads to a so-called Probability Hypothesis Density(PHD)filter.The first moment extraction of the PHD filter process is extremely sensitive to both the input parameters and the measurements.The specifics of the SSA problem and its probabilistic description are illustrated in this paper and compared to the assumptions that the PHD filter is based on.As an example,this paper shows the response of a Cardinality only PHD filter(only the number of objects is estimated,not their corresponding states)to different input parameterizations.The very simple Cardinality only PHD filter is chosen in order to clearly show the sole effects of the model mismatch that might be blurred with state estimation effects,such as non-linearity in the dynamical model,in a full PHD filter implementation.The simulated multi-target tracking scenario entails the observation of attitude stable and unstable geostationary objects.
文摘To effectively perceive network security situation under IOT environment, an Immunity-based IOT Environment Security Situation Awareness (IIESSA) model is proposed. In IIESSA, some formal definitions for self, non-self, antigen and detector are given. According to the relationship between the antibody-concentration of memory detectors and the intensity of network attack activities, the security situation evaluation method under IOT environment based on artificial immune system is presented. And then according to the situation time series obtained by the mentioned evaluation method, the security situation prediction method based on grey prediction theory is presented for forecasting the intensity and security situation of network attack activities that the IOT environment will be suffered in next step. The experimental results show that IIESSA provides a novel and effective model for perceiving security situation of IOT environment.
基金Science&Technology Department of Sichuan Province(No.21ZDYF2090)。
文摘In response to the COVID-19,social media big data has played an important role in epidemic warning,tracking the source of infection,and public opinion monitoring,providing strong technical support for China’s epidemic prevention and control work.The paper used Sina Weibo posts related to COVID-19 hashtags as the data source,and built a BERT-CNN deep learning model to perform fine-grained and high-precision topic classificationon massive social media posts.Taking Shenzhen as a region of interest,we mined the“epidemic data bulletin”and“daily life impact”posts during the epidemic for spatial analysis.The results show that the confirmed communities and designated hospitals in Shenzhen as a whole present the characteristics of“sparse east and dense west”,and there is a strong positive spatial correlation between the number of confirmed cases and social media response.Specifically,Nanshan District,Futian District and Luohu District have more confirmed cases due to large population movements and dense transportation networks,and social media has responded more violently,and people’s lives have been greatly affected.However,Yantian District,Pingshan District and Dapeng New District showed opposite characteristics.The case study results further show that using deep learning methods to mine text information in social media is scientifically feasible for improving situational awareness and decision support during the COVID-19.
基金Supported by the National Natural Science Foundation of China （No. 60605019） and the National High Technology Research and Development Programe of China （No. 2003AA142160）.
文摘The paper introduces the Endsley＇ s situation model into network security to describe the network security situation, and improves Endsley＇s data processing to suit network alerts. The proposed model contains the information of incident frequency, incident time and incident space. The HoneyNet dataset is selected to evaluate the proposed model in the evaluation. The paper proposes three definitions to depict and predigest the whole situation extraction in detail, and a fusion component to reduce the influence of alert redundancy on the total security situation. The less complex extraction makes the situation analysis more efficient, and the fine-grained model makes the analysis have a better expansibility. Finally, the situational variation curves are simulated, and the evaluation results prove the situation model applicable and efficient.
基金the Military Science Postgraduate Project of PLA(JY2020B006).
文摘In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanned system coordinative region control operation as an example,this paper combines knowledge representation with probabilistic decisionmaking and proposes a role-based Bayesian decision model for autonomous unmanned systems that integrates scene cognition and individual preferences.Firstly,according to utility value decision theory,the role-based utility value decision model is proposed to realize task coordination according to the preference of the role that individual is assigned.Then,multi-entity Bayesian network is introduced for situation assessment,by which scenes and their uncertainty related to the operation are semantically described,so that the unmanned systems can conduct situation awareness in a set of scenes with uncertainty.Finally,the effectiveness of the proposed method is verified in a virtual task scenario.This research has important reference value for realizing scene cognition,improving cooperative decision-making ability under dynamic scenes,and achieving swarm level autonomy of unmanned systems.
基金funded by the National Social Science Fund of China(No.19BTQ045).Haixu Xi received the grant and the URLs to sponsors’websites is http://fund.cssn.cn/skjj/。
文摘Microelectronic technology and communication technology are developed in deep manner;the computing mode has been transferred from traditional computer-centered to human centered pervasive.So,the concept of Internet of things(IoT)is gradually put forward,which allows people to access information about their surroundings on demand through different terminals.The library is the major public space for human to read and learn.How to provide a more comfortable library environment to better meet people’s learning requirements is a place where the Internet of things plays its role.The purpose of this paper is to solve the difference between the data fusion of library environment and the data fusion of other environments by the method of data fusion oriented to library.This paper presents a general technical framework of situational awareness for smart library system which includes a data fusion middleware.It can process data and inform the upper module of the changed library environment after deploying the smart library system in a library,including data collection and processing,how to judge whether events are triggered,how the system reacts,and the acquisition and update of user preferences.This paper presents a situational awareness recommendation method based on an effective data fusion model and algorithm for library after conducting experimental in service of library,which give more accurate of book recommendation than traditional method and good learning service environment of library for readers.
基金supported by the National Key Research and De-velopment Program of China(2020YFB0505601)。
文摘Complicated electromagnetic environments of the space situational awareness facilities(i.e.,satellite navigation systems,radar)would significantly impact normal operations.Effective monitoring and the corresponding diagnosis of the jamming signals are essential to normal opera-tions and the innovations in anti-jamming equipment.This paper demonstrates a comprehensive survey on jamming monitoring algorithms and applications.The methods in dealing with jamming signals are summarized primarily.Subsequently,the jamming detection,identification,and direc-tion finding techniques are addressed separately.Based on the established studies,we also provide some potential trends of the demonstrated jamming monitoring issues.
基金National Natural Science Foundation of China(No.61772478)
文摘The real-time of network security situation awareness(NSSA)is always affected by the state explosion problem.To solve this problem,a new NSSA method based on layered attack graph(LAG)is proposed.Firstly,network is divided into several logical subnets by community discovery algorithm.The logical subnets and connections between them constitute the logical network.Then,based on the original and logical networks,the selection of attack path is optimized according to the monotonic principle of attack behavior.The proposed method can sharply reduce the attack path scale and hence tackle the state explosion problem in NSSA.The experiments results show that the generation of attack paths by this method consumes 0.029 s while the counterparts by other methods are more than 56 s.Meanwhile,this method can give the same security strategy with other methods.
