Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is ...Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is still a high rate of false negatives in detecting these complex attack patterns.To solve this problem,we use interval temporal logic formulae to describe concurrent attacks and piecewise attacks.On this basis,we formalize a novel algorithm for intrusion detection based on model checking interval temporal logic.Compared with the method based on model checking linear temporal logic,the new algorithm can find unknown succinct attacks.The simulation results show that the new method can effectively reduce the false negative rate of concurrent attacks and piecewise attacks.展开更多
Geo-data is a foundation for the prediction and assessment of ore resources, so managing and making full use of those data, including geography database, geology database, mineral deposits database, aeromagnetics data...Geo-data is a foundation for the prediction and assessment of ore resources, so managing and making full use of those data, including geography database, geology database, mineral deposits database, aeromagnetics database, gravity database, geochemistry database and remote sensing database, is very significant. We developed national important mining zone database （NIMZDB） to manage 14 national important mining zone databases to support a new round prediction of ore deposit. We found that attention should be paid to the following issues： ① data accuracy： integrity, logic consistency, attribute, spatial and time accuracy; ② management of both attribute and spatial data in the same system;③ transforming data between MapGIS and ArcGIS; ④ data sharing and security; ⑤ data searches that can query both attribute and spatial data. Accuracy of input data is guaranteed and the search, analysis and translation of data between MapGIS and ArcGIS has been made convenient via the development of a checking data module and a managing data module based on MapGIS and ArcGIS. Using AreSDE, we based data sharing on a client/server system, and attribute and spatial data are also managed in the same system.展开更多
基金supported by National Natural Science Foundation of China under Grant No. 61003079
文摘Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is still a high rate of false negatives in detecting these complex attack patterns.To solve this problem,we use interval temporal logic formulae to describe concurrent attacks and piecewise attacks.On this basis,we formalize a novel algorithm for intrusion detection based on model checking interval temporal logic.Compared with the method based on model checking linear temporal logic,the new algorithm can find unknown succinct attacks.The simulation results show that the new method can effectively reduce the false negative rate of concurrent attacks and piecewise attacks.
基金This paper is financially supported by the National I mportant MiningZone Database ( No .200210000004)Prediction and Assessment ofMineral Resources and Social Service (No .1212010331402) .
文摘Geo-data is a foundation for the prediction and assessment of ore resources, so managing and making full use of those data, including geography database, geology database, mineral deposits database, aeromagnetics database, gravity database, geochemistry database and remote sensing database, is very significant. We developed national important mining zone database （NIMZDB） to manage 14 national important mining zone databases to support a new round prediction of ore deposit. We found that attention should be paid to the following issues： ① data accuracy： integrity, logic consistency, attribute, spatial and time accuracy; ② management of both attribute and spatial data in the same system;③ transforming data between MapGIS and ArcGIS; ④ data sharing and security; ⑤ data searches that can query both attribute and spatial data. Accuracy of input data is guaranteed and the search, analysis and translation of data between MapGIS and ArcGIS has been made convenient via the development of a checking data module and a managing data module based on MapGIS and ArcGIS. Using AreSDE, we based data sharing on a client/server system, and attribute and spatial data are also managed in the same system.
